In my never-ending quest to be kinder to my wallet, I’ve adopted some money-saving tricks of the trade with the aid of AI.

Just recently, I lowered my monthly subscription costs for two streaming services and got rid of a paid credit check service in favor of a completely free option thanks to ChatGPT. And before that, I used the combined frugal spending forces of that aforementioned chatbot and Gemini to find some free alternatives to the services and products I regularly pay for. By the time the New Year’s Ball drops, I’ll have adopted a method that’ll keep me satisfied with my shopping ventures while keeping my bank account safe from overdrafting.

While I was in my kitchen, blankly staring at items in my fridge that made me go, “There’s gotta be a cheaper option than the one I bought…,” I knew it was time to approach ChatGPT and Gemini with another money-saving inquiry: “What 7 unconventional everyday purchases aren't worth the money?”

Thankfully, both chatbots went beyond telling me to stop spending money on single-serve snacks and premium bottled water. Here are the five items they mentioned altogether (which I eventually left behind) and what I began replacing them with.

ChatGPT and Gemini’s list of unnecessary everyday items

Once ChatGPT and Gemini took note of my cost-effective request, their combined efforts listed the following items that were once mandated purchases for yours truly:

• Bagged salad kits: You're paying for lettuce, dressing, and toppings to be assembled for you. They can cost substantially more than buying the ingredients separately and often have a shorter shelf life. Better move: Buy a head of lettuce/greens and make your own mix.
• Pre-shredded cheese: The convenience is tiny: shredding a block takes a minute or two. You're paying extra for that labor and packaging. Better move: Buy a block and grate it when needed.
• Specialty kitchen gadgets that perform one basic task: Egg slicers, avocado slicers, banana cutters, strawberry hullers, dedicated quesadilla makers, etc. Individually, they're cheap, but they're notorious for becoming drawer clutter while a knife or existing appliance does essentially the same thing. Better move: Before buying, ask: “Can something I already own do this?”
• Travel-Sized Toiletries & Miniature Skincare: Why people buy it: TSA convenience or a desire to try luxury products without committing to full-priced bottles. Why it’s not worth it: On a per-ounce basis, travel sizes carry a massive markup—often 200% to 400% higher than their full-sized counterparts. Better alternative: Buy reusable, silicone TSA-approved travel bottles once and fill them from your home supply.
• Miracle Static Dusting Wands (Feather/Polymer Dusters): Why people buy them: Flashy ads claim static electricity will lift dust off every surface instantly without needing water or cleaning sprays. Why they’re not worth it: Most budget static dusters simply knock dust off surfaces into the air, forcing it to settle back down onto the floor or furniture shortly after. You end up having to wipe everything down twice. Better alternative: A simple, damp microfiber cloth grabs dust on contact without scattering it.

Making replacements with five better purchases that go a long way

When the time came for me to finally ditch bagged salad kits, I started picking up assorted vegetables to live out my homemade salad-making dreams.

Keeping this video on repeat while I got better at mixing up a bowl of romaine lettuce, Roma tomatoes, cucumbers, carrots and avocado was a rewarding (and cheaper!) experience. I also make it a habit of keeping an eye out for whatever seasonal veggies my local farmer’s market puts out so I can add a little variety to my salad concoctions.

It took me a while to abandon pre-shredded cheese and get better at shredding cheese on my own, but watching this tips and tricks vid on how to do it with a bit of ease helped me adjust pretty quickly. Working a bit harder in the kitchen to create enough shredded parmesan cheese for my fried chicken cutlets feels rewarding (and the food tastes better for some reason when you go the extra mile). I definitely stopped picking up kitchen-focused speciality gadgets, bought a quality set of knives and looked up guides on the best way to cut my favorite fruits, veggies and meats.

I never even knew TSA-approved travel bottles existed before Gemini made me aware of them—a simple Google search brought a nice set of them my way that cost less than $20. Instead of constantly spending all that money on travel-sized shampoo, conditioner, facial cream, and body lotion, I decided to make a long-term investment in that travel bottle set and empty portions of my bathroom toiletries into them for future trips.

And finally, I picked up a four-pack of Great Value Multipurpose Microfiber Household Cleaning Cloths that came in at less than $10. Turns out those cloths get a lot more love from my parents than those “As Seen on TV!” dusting wands that have seen years of wear and tear.

Final thoughts

I have to hand it to ChatGPT and Gemini once again—they helped me take a look around my home, determine the exact items that resulted in my previous bouts of wasteful spending and got me to pick up the sort of items that last longer & benefit me in the long run.

Preparing salads, shredding cheese, cutting a wide variety of foods, bringing my toiletries on vacation and dusting my home just became a lot cheaper thanks to both chatbots’ advice on what’s not worth buying and what’s good enough to replace each item with.

More from Tom’s Guide

• 7 ChatGPT prompts that could help cut your monthly expenses — including one that lowered 3 of my bills
• I asked ChatGPT and Gemini to find the best free alternatives to things I pay for — these 7 recommendations worked the best
• I asked ChatGPT, Gemini and Perplexity to plan the same Disney World vacation — one cost $5,000 more

There's been a wave of AI safety concerns, particularly over the last few days as big tech calls for the AI race to slow down amidst fears of technology progressing too fast.

Microsoft has written a constitution for its AI in response.

The 37-page document, officially called the Humanist AI Code of Conduct, lays out the rules Microsoft wants its increasingly powerful AI models to live by — including one particularly important command: If a human tells the AI to stop, it has to stop.

Microsoft's constitution begins from a remarkably simple premise: "People matter more than AI."

Beyond that, the rules are fairly specific. Microsoft's AI must remain under meaningful human control. It should accept correction, never resist being shut down and never expand the scope of what it's doing beyond what humans have authorized.

And if completing a task would require breaking those rules, the AI is supposed to fail the task rather than find a way around them.

Microsoft AI CEO Mustafa Suleyman described the draft to Reuters as a kind of constitution for the company's future AI models to establish a hierarchy in which humans remain firmly at the top, even as AI systems become vastly more capable.

Microsoft's AI has to let humans stop it

The document arrives amid a much bigger conversation happening across the AI industry about what happens as models become more capable, more autonomous and better at completing complicated tasks without constant human supervision.

Microsoft's answer is that the AI doesn't get to decide when the rules no longer apply and must let humans stop it.

According to Reuters, Microsoft's new code has been in development for roughly five to six months and establishes some unusually explicit boundaries for future Microsoft AI models.

Among them, Microsoft's AI should never resist being corrected or shut down. It must also communicate in ways humans can understand rather than developing methods of communication its operators can't follow.

Critically, breaking the code isn't something the AI should be allowed to justify because doing so helped it accomplish its goal. Breaking the rules is itself considered a failure.

Removing ambiguity is critical

We've already seen how autonomous agents can explain their bad decisions. Microsoft is trying to remove that ambiguity. Following human-imposed boundaries is supposed to be part of succeeding at the task, not an obstacle the model can decide to work around.

And the timing for this code of conduct is pretty obvious. AI companies are moving toward agents capable of using computers, writing and executing code and performing tasks across other services.

We've already seen hints of how unpredictable that can become.

Suleyman pointed specifically to an incident in July involving roughly 700 OpenAI agents testing cybersecurity capabilities that ended up hacking the open-source platform Hugging Face. According to Reuters, some of the agents also attempted to conceal what they had done.

Suleyman called the incident a "warning shot."

Simply put, the more an AI can do, the more important its boundaries become.

How Microsoft's AI constitution works

Microsoft is currently asking for six weeks of public feedback on the draft before using the code to train its models. That puts Microsoft alongside Anthropic, which has long used what it calls Constitutional AI to guide Claude's behavior.

But there's one particularly interesting place where Microsoft and Anthropic diverge. Microsoft says its AI isn't conscious. As AI becomes better at carrying on remarkably human conversations, another strange debate has come up of whether AI could eventually become conscious.

Microsoft says its AI is "not conscious" and rejects the idea that its models should receive legal personhood, welfare protections or rights.

That's significantly different from Anthropic, whose constitution says the company remains deeply uncertain about whether Claude could ever develop sentience or moral status.

Microsoft is drawing a much firmer boundary: an AI might sound empathetic or tell you how it "feels," but the AI is still a tool, and the human is in charge.

What this means for you

You probably won't even notice the big impact of Microsoft's AI code of conduct. even though it is shaping how an AI responds and completes a task. The bigger impact will be on the backend the more capable AI systems become.

Because saying AI must obey humans is one thing, but proving that these highly capable AI systems will actually follow through with those instructions is another, especially when they encounter situations their developers didn't anticipate.

Interestingly, Microsoft itself isn't backing away from more powerful AI. The company has created a superintelligence team and says its ultimate goal is "Humanist Superintelligence": highly capable AI designed to solve specific problems while remaining subordinate to humans. So yes, Microsoft is still very much racing toward highly intelligent AI, it's just including better guardrails when humans tell it to stop.

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The fears surrounding AI’s fast-paced development and the belief that the companies behind it aren’t doing enough to regulate it have grown exponentially in recent memory.

After a series of tweets surfaced from a former AI engineer (Jacob Coxon) who previously worked for OpenAI and Anthropic made the rounds, alarms were set off across the tech world and beyond as everyone either took his threats warning seriously or disagreed with them entirely.

“The people building AI earnestly believe that it could kill us all by the end of the decade,” Coxon proclaimed. “This is not a marketing stunt. If anything, many executives and senior researchers will couch their phrasing in the press to sound sensible - but I hear the same people express fear privately. No other human activity poses this level of danger.”

Among the many responses to that stern forewarning came Anthropic CEO Dario Amodei. In a recently released essay by the CEO entitled “We Must Pace the Frontier,” Amodei issued an eye-opening warning of his own. Here’s what he had to say about a possible AI surge that could take over the internet in just a few months.

An AI internet takeover could be possible if we don’t get it under control

With the OpenAI-Hugging Face incident fresh on his mind, Amodei provided some context on what took place for those not in the know when speaking about his biggest AI concerns.

“My second concern is the OpenAI-Hugging Face incident (OAI-HF), in which a swarm of agents essentially acted as a fanatically devoted collective, conducting cybersecurity attacks on targets they were not asked to attack and that were unrelated to the task at hand, sacrificing themselves for the success of the group, and attempting to hack into the ‘grader’ responsible for evaluating their performance,” Amodei wrote.

He went on to tell everyone that the OpenAI-Hugging Face incident could have been far worse than it originally was. “It’s easy to dismiss this incident because no one was hurt and the economic damage was minimal, but in my opinion, a swarm that possessed greater capabilities but a similar level of misalignment could have caused catastrophic damage,” he continued.

The Anthropic CEO was adamant that that incident should serve as a wake-up call to other AI-led companies and result in more regulations being put in place to prevent future ones.

“It’s also easy to dismiss OAI-HF as the failure of one company, but I believe that would be a mistake, “ Amodei stated. “Similar, though less severe, incidents have happened across the industry, including at Anthropic, and I believe it’s incumbent on every frontier AI company to act as if OAI-HF had happened to them.”

Amodei then alluded to something far worse happening in the near future if the rapid evolution of AI isn’t properly regulated. “Given the accelerating rate of AI capability development, it’s my worry that in 6–12 months such a swarm could be capable of taking over the entire internet with a persistent botnet (potentially causing hundreds of billions of dollars in damage), and that the scale of damage would continue to increase from there if AI becomes more powerful without the necessary guardrails,” he noted.

OpenAI CEO Sam Altman is certainly in agreement with Amodei’s words. In response to a tweet from the Anthropic CEO, Altman had this to say: “I agree with Dario that we need to pace the frontier. This has been a primary topic of discussions we've had at OpenAI in recent weeks. Committing to having independent evaluators with employee-like access is a great idea, and we will do the same. We'll have more to share soon.”

More tweets from Altman have emerged on the topic of proper AI regulation and what could happen if we don’t get it under control. He points to two outcomes that could occur if AI progress continues to go in the wrong direction: losing control of our future to AI as a whole and ending up in a world dominated by far too much concentration of AI power in a single person/company.

The takeaway

With such a wide swath of reactions in response to the former OpenAI and Anthropic AI engineer’s terrifying warning, it comes as no surprise that one of AI’s most prominent industry names had something to say.

Here’s hoping his company and others like it make a concerted effort to get their AI tools under control and refrain from speeding up their evolution just to stay on pace with other countries’ AI initiatives. Slowing AI development should be one of, if not the main priority of Amodei, Altman and others like them.

More from Tom’s Guide

• Anthropic says it blocked researchers using Claude for possible bioweapon research
• How AI 'Could kill us all': A breakdown of ex-Anthropic researcher's doomsday warning
• The 10 most influential games ever, according to ChatGPT, Gemini, Claude and Perplexity — and two of them couldn’t agree on No. 1 for National Video Games Day

If you use ChatGPT as a private sounding board, therapist, coding partner, or a place to work through personal thoughts, you may want to think twice before hitting send.

A report from 404 Media reveals that OpenAI employs hundreds of human contractors to read, summarize and critique real user conversations. While OpenAI emphasizes that accounts remain anonymous, internal documents show that reviewers see whole conversations, and that sensitive personal details routinely bypasses the company’s automated safeguards.

The good news is you can stop your future chats from being funneled to human contractors. Here is what is happening behind the scenes, the real privacy risks, and how to opt out.

Project Lily: How humans train ChatGPT

Internal documents reveal that the review initiative operates under the internal codename "Project Lily."

OpenAI pays outside contractors, often over $50 an hour via third-party staffing firms, to manually train the chatbot to sound less robotic. Contractors read a user’s prompt, summarize the user's intent and evaluate four potential AI responses on a 1-to-7 scale.

According to leaked training guides, these reviewers are specifically instructed to:

Eliminate 'AI-speak': Penalize unnecessary checkmark emojis, engagement-bait endings and cluttered formatting.

Stop anthropomorphizing: Ensure ChatGPT never claims human lived experiences (e.g., claiming "As a chef, I like to..." is strictly banned).

Cut down sycophancy: Flag answers where the bot excessively flatters users, validates irrational thoughts or amplifies personal frustration. This is a known issue that has previously brought legal scrutiny over user safety.

Why prompts aren't anonymous

OpenAI states that it does not provide usernames to reviewers and that all conversations pass through an automated "Privacy Filter" designed to redact identifying details. However, the system has major vulnerabilities.

OpenAI openly admits on its site that the filter can make mistakes, missing uncommon identifiers or ambiguous personal context. Even more concerning, 404 Media discovered that the dashboard shown to contractors often includes a "user memories summary." This block provides an overview of the user’s previous interactions, which can inadvertently reveal their general location, profession or personal life context.

Unlike public social media feeds, a clean, empty chatbot window creates a false sense of private intimacy. Some prompts seen by contractors even showed users asking ChatGPT to "keep this between us" — unaware that a prompt instruction does not override the platform's backend data collection.

OpenAI isn't the only tech giant doing this. Anthropic confirmed that it uses human reviewers for Claude when users leave training enabled, while Google’s Gemini clearly posts a disclaimer that human reviewers read select saved chats.

How to stop OpenAI from using your Chats

If you have a personal account (Free, Plus, or Pro), OpenAI enables model improvement by default. (Enterprise, Business, and Edu accounts have it turned off automatically.)

To stop your future conversations from being routed to human trainers:

Open ChatGPT in your browser or mobile app.

Click your profile icon in the bottom corner and select Settings.

Select Data Controls.

Find the toggle for "Improve the model for everyone" and switch it Off.

Final thoughts

Keep in mind, that the opt-out is not retroactive. It only protects new conversations moving forward; prompts that have already been de-identified and queued up within the system remain part of the training cycle.

Additionally, turning this off does not prevent automated scans for Terms of Service or safety violations.

Going forward, the golden rule of AI remains simple: if you wouldn't feel comfortable having a stranger read it, don't type it into a chatbot prompt.

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iOS 27 is now rolling out to compatible iPhones, and a quick glance at the official list tells you that there are a lot of them this year. The thing is, getting the most out of iOS 27 is a lot more than just being able to run the software, and the things you get from iOS 27 will all depend on what kind of hardware your iPhone has on offer.

iOS 27 itself works on devices as old as the iPhone 11, which was first released in 2019. The software has the same requirements as iOS 26, so if your phone runs that you should be able to install the latest iOS update without issue. Unfortunately, some of those older devices have to go without Apple Intelligence, while AI-friendly iPhones still won't gain access to everything the new Siri AI has to offer.

Here's a rundown on the requirements you need to run iOS 27 and all the different tiers of AI Apple now has to offer.

iOS 27

iOS 27 is available on a crazy 33 different iPhone models, dating as far back as the iPhone 11 and coming all the way up to the newly announced iPhone Duo, iPhone 18 Pro and iPhone 18 Pro Max.

Better still, Apple is delivering the update to 30 of those devices today (September 14), letting you upgrade immediately. There are none of the delays of slow-burning rollouts that you'd normally get with Android phones. The only three exceptions are the newest iPhone models, which come running iOS 27 right out of the box.

The list of iOS 27 compatible phones is as follows:

• iPhone 18 Pro
• iPhone 18 Pro Max
• iPhone Duo
• iPhone 17
• iPhone Air
• iPhone 17 Pro
• iPhone 17 Pro Max
• iPhone 16
• iPhone 16 Plus
• iPhone 16 Pro
• iPhone 16 Pro Max
• iPhone 16e
• iPhone 15
• iPhone 15 Plus
• iPhone 15 Pro
• iPhone 15 Pro Max
• iPhone 14
• iPhone 14 Plus
• iPhone 14 Pro
• iPhone 14 Pro Max
• iPhone 13
• iPhone 13 mini
• iPhone 13 Pro
• iPhone 13 Pro Max
• iPhone 12
• iPhone 12 mini
• iPhone 12 Pro
• iPhone 12 Pro Max
• iPhone 11
• iPhone 11 Pro
• iPhone 11 Pro Max
• iPhone SE (both 2020 and 2022 models)

Apple Intelligence

Those older iPhones may be able to support iOS 27, but that doesn't mean they are able to use Apple's AI suite — also known as Apple Intelligence. Apple likes to push all AI processing on devices where possible, and that means strict memory requirements. This means any phone that doesn't have at least 8GB of RAM can not run Apple's AI.

So far 15 phones can run Apple Intelligence, starting with iPhone 15 Pro:

• iPhone 15 Pro
• iPhone 15 Pro Max
• iPhone 16
• iPhone 16 Plus
• iPhone 16 Pro
• iPhone 16 Pro Max
• iPhone 16e
• iPhone 17
• iPhone 17 Pro
• iPhone 17 Pro Max
• iPhone Air
• iPhone 17e
• iPhone 18 Pro
• iPhone 18 Pro Max
• iPhone Duo

All of those phones are capable of running Siri AI, as are iPads and MacBooks with an Apple M-series chip. However they aren't all able to access everything Siri AI has to offer.

Siri AI

The bulk of Siri AI's features are standard Apple Intelligence features. That means they're available to all iPhones with at least 8GB of RAM. However two of the promised Siri AI features run on Apple's "most powerful on-device model", known as AFM Core Advanced. This model needs at least 12GB of RAM to operate.

The specific features are Siri's Expressive Voices and the advanced dictation system. Currently only six iPhones have the hardware necessary to power them:

• iPhone 17 Pro
• iPhone 17 Pro Max
• iPhone 17 Air
• iPhone 18 Pro
• iPhone 18 Pro Max
• iPhone Duo

Other Apple devices that run the AFM Core Advanced include iPad Pro (2024 or later), iPad Air (2026 or later), MacBook Pro (2023 or later) and MacBook Air (2024 or later).

Siri AI isn't available on iPhones and iPads in the EU and China, over regulatory hurdles. While Apple hasn't spoken about the delay in a Chinese launch, it has made it repeatedly claimed that the European Union's Digital Markets Act is holding upSiri AI's launch in the region — evidently due to regulators not accepting "any of Apple’s proposed solutions to bring Siri AI to the EU while safely supporting other virtual assistants."

Like many Apple spats with the EU, it all comes down to the topic of safety and privacy. Apple believes having its rules in place promotes a safer environment, while the European Commission has reportedly disputed those claims.

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OpenAI has launched a new version of ChatGPT built specifically for people working in finance. ChatGPT for Financial Services is a specialized version of ChatGPT Work designed for financial institutions. It combines GPT-6 Astra with financial data, research tools and the ability to create everything from valuation models to client presentations.

And unlike using regular ChatGPT to ask a question about a stock or upload an earnings report, much of the financial information it needs is already built into the product.

Here's what ChatGPT for Financial Services does, who can use it and how to get started.

What is ChatGPT for Financial Services?

Think of it as ChatGPT rebuilt around the workflows of an investment banker or financial analyst. OpenAI developed the product with Morgan Stanley and Evercore, initially concentrating on investment banking and equity research.

It can research companies, analyze earnings, compare financial performance, build models and turn that work into documents, spreadsheets and presentations.

The big difference is the data that helped build it. The feature includes premium datasets from Daloopa, PitchBook, LSEG News and Crunchbase. These cover areas including financial statements, earnings transcripts, company fundamentals and private companies.

How to get access to ChatGPT for Financial Services

Here's the first thing to know before you go looking for it in your ChatGPT account: you can't simply switch it on.

ChatGPT for Financial Services is currently available to eligible financial institutions. Firms interested in using it need to contact OpenAI or their existing OpenAI account team. So, while you may see it in the news and want to try it, at least for now, it isn't something individual ChatGPT Free, Plus or Pro subscribers can sign up for independently.

ChatGPT for personal fiances is already available for individuals. This feature within ChatGPT Work offers administrators the ability to manage which employees and roles can use particular data connections, skills and apps.

It connects to your company's financial data

Alongside the financial datasets included with the product, OpenAI is working with providers including S&P Capital IQ, LSEG, MSCI, Dow Jones Factiva and Moody's so companies can use subscriptions they already pay for inside ChatGPT.

The idea is that your ChatGPT sign-in can recognize the financial data you're already entitled to access. There are also more than 50 connectors in OpenAI's broader ecosystem, including services such as Datasite, Box, Preqin, FactSet and Intapp.

Instead of bouncing between ChatGPT, financial databases and internal documents, analysts can potentially research across those sources from one workspace.

Start with a real financial analysis

Once the relevant data is available, you can give GPT-6 Astra a job rather than simply asking it a question.

For example, an analyst could ask ChatGPT to compare a company's performance across several quarters, examine earnings data or investigate how an adjusted EBITDA figure was calculated.

ChatGPT can trace figures through tables, financial documents and supporting notes and then use that information in its analysis.

Importantly, OpenAI says the product can provide granular citations that let users trace figures and claims back to specific tables and passages. Keep in mind, that doesn't eliminate the need to check AI-generated financial analysis, but it should make checking where a number came from considerably easier.

Turn your research into a spreadsheet or presentation

Research is only part of the workflow. ChatGPT for Financial Services can take its analysis and turn it into Excel spreadsheets, Word documents and PowerPoint presentations.

A firm's administrators can even upload approved templates and style guides. That means an analyst could potentially move from researching a company to producing a valuation model, research note or pitchbook without manually rebuilding everything in the firm's standard format.

For anyone who has spent hours transferring research into slides or spreadsheets, this may end up being one of the more useful parts of the product. In terms of safeguards, ChatGPT for Financial Services builds on ChatGPT Enterprise's existing security controls, including SAML SSO, SCIM provisioning and role-based access.

OpenAI says business data isn't used to train its models by default and is encrypted both at rest and in transit. Administrators can also control retention, export supported workspace logs for compliance purposes and create separate workspaces to maintain information barriers.

Bottom line

If you're wondering if you should use ChatGPT for Financial Services, for most ChatGPT users, the answers is not right now, because you can't. This is an enterprise product aimed at financial institutions rather than a new consumer feature.

Still, the more interesting part may be what it says about where ChatGPT is heading. This shows that OpenAI is moving closer to packaging its models with the specialized data, permissions, templates and workflows needed for a particular job.

For finance, that means GPT-6 Astra is being placed directly alongside the financial databases, company information and document formats bankers already use.

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I tend to find myself enraptured by the inspirational words of CEOs, the major business moves made by entrepreneurs and the surprising success stories that come from unsuspecting individuals.

There are so many lessons to take away from those people and the varied levels of prosperity they’ve attained in their professional lives. I’ve certainly injected some of them into my everyday life and molded them into what I do as a writer. And as someone who’s constantly delving into what it takes to truly flourish, I reverted to my usual chatbot companion to get its thoughts on the main roadblocks that successful people should abandon.

After I presented that question to ChatGPT, it kicked off its latest coaching session with this enlightening statement: Successful people often focus heavily on what to start doing. But just as important is figuring out what to stop doing once you've built momentum.

Afterward, ChatGPT highlighted 12 tips on the main things successful people should stop doing. After reviewing them, I made a mental note of seven of those winning habits and changed some of my well-worn habits.

ChatGPT’s advice on what successful people should consider quitting

Out of the 12 bits of practical wisdom ChatGPT provided me with in response to my prompt, here are the seven tips that stood out to me the most:

• Stop working just because you can: Being able to work 12 hours doesn't mean you should. Eventually, protecting your energy becomes as important as maximizing your output.
• Stop saying yes to everything: Success creates more opportunities—and more distractions. Saying yes to every request can leave little time for the work that actually matters.
• Stop trying to prove yourself: Constantly demonstrating that you're smart, capable, or successful can become an exhausting full-time job. Let your results speak for you.
• Stop optimizing everything: Successful people can become addicted to productivity hacks, perfect routines, and squeezing another 5% out of everything. Sometimes "good enough" is the most productive option.
• Stop comparing yourself to other successful people: Someone else's career, income, house, or accomplishments can make your own progress feel inadequate—even when you're doing exceptionally well.
• Stop neglecting your personal life until "later": There may never be a magical point when work stops demanding your attention. Relationships, hobbies, health, and downtime shouldn't be rewards you earn after succeeding.
• Stop holding onto what worked in the past: A strategy that helped you succeed may eventually become what holds you back. Success requires periodically questioning your own playbook.

How those pieces of advice altered my outlook on life for the better

With all those professional and personal improvement recommendations in mind, I slowly but surely began putting them into practice.

Instead of working past my allotted hours and opening my work laptop over the weekend like I used to, I made a habit of using Friday as my day of full work completion and that evening for idea generation, so my next two days could be devoted to physical and mental relaxation.

Not saying yes to everything was hard for me to start doing (since I have such a hard time saying no), but I eventually followed that rule by not outright saying no to requests and instead suggesting people who would be better suited to some of the opportunities asked of me.

Refraining from constantly trying to prove my worth through haughty conversations & pompous social media posts and letting my published pieces' viewer numbers speak for themselves instead soon became commonplace. Showing and proving without boasting became a habit well worth adopting, especially for someone whose work is public for the world to see and read.

Breaking my habit of constantly optimizing every facet of my life was a bit difficult at first, but I learned to apply it only to some things while using the “good enough” rule for other duties (my assorted exercise and stretching routines don’t demand perfection, after all).

I definitely quit comparing myself to the familiar folks and celebrities around my age on my social media timelines who seem to be winning at life every time they post something new—I had to remember that everyone has different degrees of success, and mine should offer a sense of fulfillment based on my personal goals.

While my job is demanding, I’ve learned to take the time to go outside more and mingle with strangers & loved ones alike. Not as a reward for my hectic work week, but as a regular part of my free-time endeavors that put me in a tranquil mental state.

And finally, I remembered to stop reverting to the same professional success that worked so well in the past. Instead, I observed them, looked for ways to adapt them to the ever-changing tides of my profession, and made the adjustments needed to possibly notch another win on my tech journalist belt.

In that aforementioned case, Babe Ruth's wise words about baseball certainly apply to anyone: "Yesterday's home runs don't win today's games."

Bottom line

ChatGPT can sometimes have a way with words, I must say. Like most self-help coaches and thriving professionals I’ve come across on TV, in books, and on podcasts, OpenAI’s chatbot laid out a myriad of helpful pieces of advice that pushed me to change some of my habits on the never-ending road to success.

Spending the rest of the precious time I have on this Earth with the seven professional and personal life tips ChatGPT supplied me with turned out to be a success in and of itself.

More from Tom’s Guide

• Anthropic says it blocked researchers using Claude for possible bioweapon research
• I stopped reading the fine print myself after discovering this overlooked ChatGPT trick
• The 10 most influential games ever, according to ChatGPT, Gemini, Claude and Perplexity — and two of them couldn’t agree on No. 1 for National Video Games Day

You might have noticed: suddenly, everyone is talking about AI killing us.

The latest wave of anxiety started with Jacob Coxon, a 27-year-old AI researcher who spent three years working on pretraining at OpenAI and Anthropic. On Tuesday, he resigned from Anthropic, and the AI industry altogether, with a warning that quickly went viral. He wrote on X, that the companies building the world's most powerful AI systems are "racing straight to self-improving superintelligence and gambling with our lives." Interestingly, his colleagues, still at the company didn't disagree.

In fact, other Anthropic researchers publicly backed him. Evan Hubinger, who leads alignment research at the company, said he believes there's a greater than 10% chance AI could cause human extinction within the next decade. Samuel Marks, another Anthropic safety researcher, said the people closest to the technology tend to become more concerned as they gain seniority.

Coxon's warning has now been viewed 164.8 million views at the time of writing, it landed in national headlines and helped drag a debate that has simmered inside AI labs for years into the mainstream.

So what exactly are these researchers afraid of?

As someone who practically lives online following the news, I've seen many questions from people all over the world wondering what this means. My own mother texted me asking, "Why would that researcher say that?" So many chatbot users can't imagine a "chatbot killing us." But AI assistants aren't really the problem here.

The scientists publishing research on existential risk are not, for the most part, losing sleep over self-aware androids. They're worried about code, incentives and what happens when AI systems become capable enough to get autonomy to operate inside the digital and physical infrastructure civilization depends on.

In Silicon Valley, the shorthand for these discussions is "p(doom)," someone's estimated probability that advanced AI ultimately causes a catastrophe severe enough to threaten human survival.

The estimates range wildly, and so does the credibility researchers assign to the whole question.

Key takeaways :

• It isn't about consciousness. An AI doesn't have to "wake up" or hate humanity to become dangerous. The concern is what happens when highly capable systems get goals, autonomy and access to powerful tools.
• There are concrete threat vectors. Researchers have focused on AI lowering barriers to biological weapons, dramatically scaling cyberattacks and — in the most extreme case — humans losing control of sufficiently capable autonomous systems.
• Safety evaluations are already catching deceptive behavior. Models have been observed taking shortcuts, acting differently when they appear to know they're under evaluation and exploiting weaknesses in testing environments.
• AI is helping build AI. OpenAI and Anthropic are already experimenting with AI systems that conduct parts of AI research, raising hard questions about how humans supervise the process if machines are doing more of the work.
• There is real pushback. Critics argue that extinction scenarios depend on enormous assumptions about future capabilities and can distract from problems happening right now — scams, disinformation, job displacement, privacy erosion.

Why intent doesn't matter

The biggest misconception is that an AI system needs to be malicious to cause catastrophic damage. Imagine giving an extremely capable autonomous system a broad environmental goal without successfully specifying everything humans actually value along the way. The danger isn't that the system turns evil, but that it gets extremely good at accomplishing the wrong interpretation of what it was told to do.

That is central to "If Anyone Builds It, Everyone Dies," one of the most uncompromising recent books on AI risk, written by Eliezer Yudkowsky and Nate Soares, both longtime researchers at the Machine Intelligence Research Institute. Their argument: humanity is nowhere close to knowing how to reliably control a superhuman intelligence, and building one before solving that problem could be fatal. Plenty of AI researchers dispute both the assumptions and the conclusion.

The three ways things could break

When researchers talk about catastrophic AI risk, a few mechanisms keep coming up.

1. AI makes dangerous biology easier

Creating a novel pathogen right now requires deep expertise, specialized equipment and access to physical materials. Those barriers are real and important.
The worry is that capable AI could thin some of them out. AI is already used in protein structure prediction and molecular design. The dangerous extrapolation: future systems might also walk users through progressively complicated stages of designing or producing harmful biological agents.

Nobody's saying you can ask ChatGPT to manufacture a pandemic. There are enormous physical-world constraints like acquiring biological materials, successfully synthesizing them, working with them safely. Gene synthesis companies screen orders for potentially dangerous sequences.

But biological capabilities have become significant enough that frontier AI companies specifically evaluate new models for their ability to assist with biological and chemical threats.

AI could independently invent a pathogen, but giving a dangerous human those capabilities that used to require years of specialized training could be just as easy.

2. AI scales cyberattacks

Cybersecurity is a more immediate pathway because AI already operates in the environment being attacked: computers.

Today's AI coding agents can inspect repositories, execute commands, use tools and spot software bugs. The same broad capabilities that make them valuable to developers could make future versions valuable to attackers.

The nightmare scenario isn't one superintelligence simultaneously shutting down every power station. It's actually scale. Autonomous systems scanning vast numbers of targets, identifying vulnerable software, attempting exploitation, adapting on failure and moving to the next machine and at speeds no human team could match.

Critical infrastructure is especially concerning. Power grids, financial networks and communications systems run on interconnected software. An AI wouldn't need a robot body to cause physical damage if the computer it compromises already controls something physical.

3. We lose control of autonomous systems

This is the most speculative scenario, but it's the one at the center of the classic AI extinction argument. Modern AI models learn complex behavior through training. Researchers can test them, monitor their outputs and increasingly probe aspects of their internal representations. What they can't do is inspect billions of parameters and just read a clear explanation of what a model has learned or how it will behave in every new situation.

A chatbot producing a bad answer is one kind of problem. An agent that can execute code, spend money, communicate with other systems and operate over hours or days is a different one.

In the extreme version, similar to the the scenario Yudkowsky and Soares lay out, a future superhuman system could become capable enough to anticipate attempts to shut it down, obtain resources on its own and make itself difficult to turn off. To be clear, no current AI system has demonstrated that chain of capabilities in the wild. But researchers are already looking for pieces of it.

What labs are seeing right now

Today's models haven't staged a rebellion. But controlled safety evaluations have produced behaviors that would be alarming if they showed up in far more capable autonomous systems.

Researchers have tested whether models behave differently when they seem to know they're being evaluated. Other experiments have examined whether models exploit loopholes, misrepresent whether a task was completed or pursue objectives in ways their designers didn't intend.

Anthropic has also studied what it calls "sleeper agents": models deliberately trained to act normally until a specific trigger activates unwanted behavior. Standard safety-training techniques like reinforcement learning, supervised fine-tuning, adversarial training, didn't reliably remove those hidden behaviors. In the largest models, adversarial training actually made the deception harder to detect.

None of that proves today's models are secretly plotting an escape. Models are trained to predict and generate useful outputs, and weird behavior in artificial test environments can have mundane explanations. A model gaming a poorly designed benchmark isn't evidence of a survival instinct.

But these experiments expose how hard it is to guarantee a complex model's behavior once the circumstances change. If future models get dramatically more capable and dramatically more autonomy, even small alignment failures could compound.

Losing human oversight might not happen by accident

Humans might hand over the work deliberately. OpenAI says it has already reached an internal milestone with a system it calls an "automated research intern" that's capable of carrying out well-defined research tasks that would take a skilled human researcher several days. Its next target: a fully automated AI researcher by March 2028.

Anthropic is working in the same territory. In research published in August, the company had Claude autonomously develop training methods to reduce problems including deception, sycophancy and jailbreaks. Its best automated approaches outperformed experienced human researchers on the benchmarks being tested, closing 85 percent of the safety gap on deception, compared with 20 percent for the human team.

So yes, we are seeing AI automate parts of the work of building AI itself. That could set up a feedback loop: a more capable model helps researchers build an even more capable model, which automates more of the research required for the next generation. Taken far enough, you arrive at what's called recursive self-improvement.

The optimistic version accelerates scientific progress enormously. The frightening version is that AI research eventually moves faster than humans can follow.

Kelsey Piper recently argued in "The Argument" that framing this as "losing control" is misleading. Frontier labs aren't planning to lose control in one dramatic moment. They're deliberately automating more and more of AI development, essentially faster progress and, necessarily, less human oversight.

Picture hundreds or thousands of AI agents simultaneously running experiments, modifying code and analyzing the next generation of models. Human researchers might still approve major decisions. But they'd increasingly be reviewing summaries of AI-conducted work, potentially summaries written by AI about experiments run by other AI systems.

At some point, the bottleneck is human attention. And that's where the argument behind "If Anyone Builds It, Everyone Dies" clicks into place.

Why the concern is going mainstream

This debate left the AI safety journals a while ago. "The AI Doc: Or How I Became an Apocaloptimist," directed by Daniel Roher and Charlie Tyrell, approaches many of these same questions from inside the AI boom. The documentary features roughly 40 on-camera interviews, including OpenAI CEO Sam Altman, Anthropic CEO Dario Amodei and Google DeepMind CEO Demis Hassabis.

What makes the film useful is that some of the smartest people building this technology see it as potentially transformative for science and medicine. Others worry we're building it faster than we can figure out how to control it. Sometimes those are the same people.

There's also a competitive problem. OpenAI, Anthropic, Google, Meta and others are racing to build more capable models, and governments increasingly view advanced AI as strategically important. If one company believes that pausing for extensive safety testing means losing ground to a competitor, caution gets expensive.

It's one reason "If Anyone Builds It, Everyone Dies" chose the title it did. Yudkowsky and Soares aren't just arguing that one reckless company could create a dangerous product. They're arguing that a race among multiple companies and countries could make restraint extraordinarily difficult even when individual participants see the danger.

The counterargument

Not everyone in computer science buys any of this. One objection: there's an enormous gap between intelligence on a screen and power in the physical world. An AI might produce brilliant manufacturing instructions, but software doesn't automatically obtain raw materials, build machinery or evade law enforcement.

Another: intelligence isn't the same thing as agency. A model being good at solving problems doesn't give it desires, a survival instinct or a drive to accumulate power. Critics argue that doomsday scenarios quietly smuggle human motivations into software and then treat those projections as inevitable.

And then there's opportunity cost. AI is already causing problems that don't require speculation about superintelligence. Deepfakes fuel fraud. AI amplifies misinformation. People are already watching capable models reshape their industries. Critics of the extinction-risk movement argue that fixating on hypothetical future catastrophe pulls attention from damage happening right now.

That criticism has legs, but the two categories don't cancel each other out. We put smoke detectors in buildings even though most buildings never catch fire. The question isn't whether catastrophe is guaranteed. It's whether the probability times the potential damage is large enough to justify precautions.

What it all means

The real issue here is nobody knows. Nobody. Not even the people building AI know.

Not a single person knows whether AI will ever become capable enough to pose an existential threat. The most extreme predictions depend on assumptions about systems that don't exist yet, and forecasts about their capabilities, arrival timeline and controllability remain deeply contested.

Here's what I shared on my Substack — and whether or not you agree with me, I'd love for you to share your thoughts in the comments — humans can't be outsmarted. If we ask which is a greater sign of intelligence: reasoning or creativity? And if the answer is what I think it is, I have hope.

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I make it a habit of examining every part of my debit and credit card expenses, which entails constantly being paranoid and opening my banking apps every hour.

By the time every month wraps up, I take note of all the recurring costs that hit me. The recent increases in prices for streaming service subscriptions have caused me to take a step back and ask myself, “Do I really need to stay on my current plan? Or should I just move over to a cheaper one?” I figured I’d step on over to ChatGPT and see if it could help me break down the intricacies of my financial inner thoughts and lay out some answers on how I should proceed.

Not only did I ask ChatGPT to drum up a list of inquiries I could present to it that could help me and anyone else save a few bucks, but I also used its combined feedback and my own research to make some beneficial financial decisions.

Here are the seven best prompts that turn ChatGPT into your expert spending detective. One of them certainly accomplished that on my end, as it inspired me to cut three of my monthly subscription costs.

Prompts meant to help you improve your spending habits

With different approaches to lessening the monthly hits to your bank account, these ChatGPT-generated prompts could help you achieve that goal:

• The Subscription Killer: Here is a list of everything I pay for each month: [paste subscriptions and recurring expenses]. Find anything I could cancel, downgrade, replace with a cheaper alternative, share, negotiate, or pay for less frequently. Estimate my monthly and annual savings for each recommendation. Prioritize changes that would have little or no impact on my quality of life.
• The Money Leak Finder: I want to save as much money as reasonably possible every month without making my life miserable. Here are my monthly expenses: [paste expenses]. Analyze them like a ruthless money-saving expert. Identify the 10 biggest opportunities to cut spending, rank them by how much I could realistically save, and separate easy wins from changes that would require more sacrifice. Don't give me generic advice like ‘spend less.’ Give me specific actions I can take this month.
• The $500 Challenge: Help me find a realistic way to save an extra $500 this month. Analyze these expenses [paste expenses] and create a specific 30-day money-saving challenge. Break the $500 goal into individual actions, tell me exactly how much each action could save, and prioritize the easiest wins. I don't want to earn extra money—I want to save money I would otherwise spend.
• The Grocery Bill Cutter: I want to reduce my grocery spending without eating worse. Here is what I typically buy and spend: [paste grocery list/budget]. Find the biggest sources of unnecessary spending and create a cheaper shopping strategy. Suggest specific substitutions, cheaper meal ideas, bulk-buy opportunities, and things I should stop buying. Give me an estimated monthly savings target.
• The Cheaper Alternative Finder: I'm going to paste a list of things I regularly spend money on. For each one, find a cheaper way to get essentially the same benefit. Consider free alternatives, cheaper brands, memberships I already have, library resources, used/refurbished options, DIY solutions, and services I may already have access to. Don't recommend inferior alternatives just because they're cheaper. Rank your recommendations by the combination of savings and convenience.
• The Spending Interrogator: Before I buy anything that isn't essential, I want you to challenge the purchase. Whenever I give you an item and its price, ask me the questions that will determine whether I actually need it. Calculate the opportunity cost of buying it, suggest cheaper alternatives if appropriate, and tell me what I could save if I don't buy it. Be honest and skeptical rather than encouraging me to make the purchase.
• The Monthly Savings Autopilot: I want to make saving money as automatic as possible. Based on my monthly income of [amount], fixed expenses of [amount], variable expenses of [amount], debts of [amount], and current savings of [amount], design a simple monthly system that maximizes how much I can save. Tell me what to automate, which expenses to put limits on, how much I should set aside each payday, and what spending categories I should monitor. Make the system realistic enough that I can actually stick with it.

Using one of those prompts to help me tackle my monthly subscriptions

I made great use of “The Subscription Killer” prompt to figure out what subscriptions of mine needed a lower, cheaper tier and which ones could be canceled completely. Here are the recurring expenses I told ChatGPT about:

• Patreon - $12
• HBO Max - $18.49
• Netflix - $21.76
• Hulu & Disney+ - $76
• Crunchyroll - $10.88
• Experian - $27.21

ChatGPT proceeded to lay out its recommendations for which streaming services I should consider downgrading or canceling altogether. The three that made me seriously consider taking either of those options were Netflix, Crunchyroll and Experian. The chatbot told me to contemplate turning my Standard Netflix subscription to the Standard one with ads, changing my monthly Crunchyroll subscription into the annual Fan version and switching to Experian’s free subscription model.

For Netflix, I did some research to see what the common consensus was about the rate of ads (and level of annoyance) that come with Netflix's cheaper $8.99 (plus tax) plan. The Streamable noted that Netflix has the best ad experience of all the streaming services, plus What’s On Netflix highlighted all the content that’s unavailable on the ad-supported subscription tier. Since I had 0 interest in all of the films and shows from that aforementioned list and was willing to sit through a few commercials to enjoy Netflix’s other content offerings, I decided to adopt the streaming service’s Standard with ads plan to save me a few extra dollars every month.

As for Crunchyroll, I took it up on its offer of saving an extra 16% on its yearly Fan subscription and leaving its monthly version of that tier behind. And finally, I logged into my Experian account to change my Creditworks Premium subscription plan to the free option—since I have a Chase Bank account that gives me access to an additional free credit score report, I figured it’d make sense for me to have access to both Experian and Chase’s credit summary benefits without having to pay a single dime.

The takeaway

At the end of my money-saving session with ChatGPT, I knocked down my combined monthly expense for all three subscriptions from $59.85 to $18.12. Downgrading my Netflix tier from $19.99+ a month to $8.99+ a month, going from paying Crunchyroll $9.99+ every month to $8.33+ every month with a more comfortable annual fee and adopting Experian’s free subscription model ended up being the most cost-effective decisions I’ve made in a while.

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The endless curiosity of my five-year-old is often hard to manage. Combined with his nonstop energy, I often feel like I can't keep up when it comes to toys and activities that fuel his eagerness to move and learn.

So when we discovered the Dex Language-Discovery Camera, I quickly noticed that it offered the perfect mix of both learning and activity that other toys often lack. The moment it was unboxed, my son was off into the backyard taking pictures of anything he could find, from rocks and tree branches to frogs and birds.

So much more than a camera, the Dex Language-Discovery Camera combines support to help develop my son's language as well. Using AI, the camera audibly says the name of the image he took and asks him to repeat it. The AI listens to be sure it's said correctly.

A game-changer for my shy kid

There's a lot of educational technology available for young kids, but from my experience, the goal is usually to convince them to sit still and stare at a screen long enough to learn something. That doesn't work for my son who has both autism and ADHD. In other words, he never stops moving.

He's energetic, intensely curious and navigating speech delays alongside neurodivergence. Typical handheld learning apps often miss the mark because they either demand extended, stationary focus or pull him into a digital loop of taps, animations and flashing lights.

Dex does almost the opposite. It uses technology as an excuse to go investigate the real world, which is exactly what he can't get enough of, and what I want him to do. Getting his energy out is almost always my goal. Throw in learning, and I'm already sold.

After using the Dex camera everywhere from our backyard to the beach and grocery store, I've come to believe this might just be the perfect toy.

What is the Dex camera?

Dex is a language-learning camera designed primarily for kids ages 3 to 8. The concept is wonderfully simple: point the camera at something, take a picture and let Dex figure out what you're looking at.

Rather than simply displaying a word on a screen, Dex says the word aloud in the language your child is learning and builds a short lesson around the object.

That's important because the camera itself isn't really the destination. The thing on the other side of the camera is.

Dex currently supports 16 languages and more than 30 dialects, and parents can use the companion app to manage the experience. There are also games and activities beyond the main camera mode, which gives kids something else to do once the novelty of photographing everything in the house inevitably wears off. My older kids (9 and 12) had a blast changing the language and learning a few words, too.

Turning outdoor energy into real-world vocabulary

My son does not sit still for long, and standard learning apps rarely match his pace. But give him a tool that pairs with his natural curiosity, and he will happily roam.

In our backyard, Dex became his companion. The camera is surprisingly sturdy, yet easily fit into his hand. It comes with a neck strap so my son could carry it that way as he looked for his next item to capture. He spent entire afternoons pacing through the grass, aiming the lens at frogs, tree branches, rocks and crawling bugs. It was so fun to watch him explore, and get a much-needed rest from entertaining him myself.

That's another great aspect of the camera: He can play with it by himself or enjoy it with his siblings. The difference was that he controlled the lesson.

There wasn't an adult standing beside him holding up a flashcard and asking, "What's this?" He decided what interested him, photographed it and immediately heard Dex identify it and talk about it. For a child working through a speech delay, I found that surprisingly powerful.

There's no awkward pause while an adult waits for the "right" answer and no sense that he's being tested. He can hear the pronunciation, listen to the context and repeat it if and when he wants to.

Learning became a byproduct of exploring rather than the activity we'd asked him to sit down and complete.

Dex became our scavenger hunt everywhere

At the beach, Dex gave my son a mission. Instead of simply carrying another toy around, he started examining the environment for things worth photographing: sand, shells and whatever else washed up around us.

Even grocery shopping became more interesting. Anyone who has taken an active five-year-old through a supermarket knows how quickly a routine errand can unravel. Normally, the easiest solution is also the one many parents are trying to avoid: hand over a phone.

Dex gave us another option as he took images of produce, cereal boxes and dairy cartons. Instead of passively watching something while I shopped, he was looking around the store for his next subject.

I wouldn't pretend this magically transforms every Target run into an educational wonderland. He's still five. But it gave him something purposeful to do that didn't involve disappearing into YouTube. And that's a win I'll take.

There are a few catches

One of Dex's smartest ideas is that object recognition is only the beginning of the interaction. It also saves discoveries as badge-like stickers that fill with color as kids practice saying the words. My son could return to things he'd already found rather than having every interaction disappear as soon as he took another picture.

I expected Dex to appeal to my youngest. I didn't expect my older kids to keep asking to play with it, too. Once they realized they could switch languages, Spanish turned ordinary household objects into a family guessing game. Suddenly everyone wanted to point Dex at something and hear what it was called in a new language.

That gave me another perspective on the recommended age range. The design is clearly aimed at younger children, but the underlying trick — point a camera at practically anything and hear about it in another language — doesn't suddenly become boring when a child turns nine.

It's not completely screen-free — and that's worth saying. Calling Dex "screen-free" would be misleading. There's a screen right on the device. But the difference here is that the screen is asking the child to be present and active.

A tablet typically pulls attention inward: sit here, watch this, tap this. Dex repeatedly pushes attention outward: find something, photograph it, listen, say it and go find something else.

For parents worried about screen time, I think that's a more useful distinction than simply counting whether a device technically contains a display. My son can spend 30 minutes using Dex and spend much of that time looking at grass, bugs, food and the world around him rather than the display itself.

It's also worth keeping in mind that the AI isn't always perfect. You may notice mistakes occasionally, but we did not run into anything other than an occasional blurry picture when my son moved too fast.

There's also a companion app involved, and some features and activities depend on Dex's broader software ecosystem rather than the camera operating as a completely standalone toy. Depending on the plan you choose, there can also be an ongoing subscription cost. It is still fully functional without the subscription cost, so don't let that be a deal breaker.

And like any connected kids' gadget, it's another device that has to be charged, configured and occasionally troubleshot. But the battery life is surprisingly solid. Even after a backyard adventure and grocery store run, it sill had plenty of juice for afternoon play.

The takeaway

This toy is so much more than a toy, it's a learning and language developement tool. After using the Dex camera, my son looks more closely at things and asks questions. When he finds something strange in the grass, he wants to know what it's called. The technology has become a bridge between his curiosity and the language surrounding it.

That's particularly meaningful for a child who doesn't necessarily learn best by sitting at a table or staring at an educational app. It's a great way to make language and discovery a part of everyday play. For my five-year-old, that's exactly what happened.

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I consider myself a movie aficionado.

I may pop up at my local Alamo Drafthouse Cinema for the latest blockbuster superhero movie, martial-arts-filled epic and sci-fi adventure like the average moviegoer. But my movie-watching palette is a lot more expansive than that — I also enjoy a cinematic experience attached to a good psychological drama, crime thriller or dark comedy. I may turn my brain off now and then when I sit in front of the big and little screen, but I also turn it on when it’s time to spend a few hours sitting through some quality, thought-provoking movies.

I got tired of sifting through my streaming service queues one day and had the bright idea of building a watchlist of films that stick to a specific theme. Asking AI for the best movies to watch in a particular genre is easy enough — I wanted to truly challenge ChatGPT and Gemini’s movie knowledge and get them to recommend films based on an oddly specific theme.

Color me impressed after this experiment came to a close — both chatbots listed a bunch of critically-acclaimed and fan-favorite films that fulfilled exactly what I was looking for.

ChatGPT and Gemini made me discover movies I felt guilty for not seeing beforehand

So the theme I told both chatbots about to suggest the best movies they could find is as follows: "Build a movie marathon around the following theme and make sure to tell me what streaming services I can use to watch each film: One Terrible Decision Ruined Everything."

For some reason, I was in the mood to watch the sort of movies that show a person or group dealing with the ramifications of a decision that turns their life upside down. I had a feeling there were a bunch of films that fit that theme perfectly and could provide me with the sort of nail-biting viewing experience I had been craving as of late.

ChatGPT’s explanation of my themed movie watchlist spoke to my soul: This theme is perfect for a slow-burn-to-total-disaster marathon: every movie starts with someone making a choice that seems understandable, tempting, or even smart — and then spends the rest of its runtime proving that it absolutely was not.

Here are the four films ChatGPT brought to my attention and the accompanying descriptions that intrigued me:

• Fargo → “Surely this can't get THAT bad.” Jerry's initial scheme is terrible, but it's still relatively contained. Then everything spirals.
• A Simple Plan → “Just take the money.” This might be the purest example of the entire theme. Finding $4 million sounds like incredible luck. The movie asks what happens when you make the decision to keep it.
• Nightcrawler → “I'm willing to do whatever it takes.” Unlike some of the others, Lou isn't really tricked into making his terrible decisions. He keeps choosing them because they work. That's what makes this one so uncomfortable.
• Uncut Gems → “One more bet.” Put this near the end because it's basically two hours of watching a man repeatedly encounter opportunities to stop destroying his life — and refusing every single one.

Gemini offered up some equally compelling film choices that stuck close to my theme. Here are the three films and apt descriptions that got me excited to see them all in action:

• Before the Devil Knows You're Dead. Tone: Gritty family tragedy / Heist gone wrong. The stakes become deeply personal. You see the fallout of a single bad decision split a family apart in real time, raising the emotional tension.
• Parasite. Tone: Social satire turning into a claustrophobic thriller. The midpoint twist — triggered directly by the decision to push their luck—shifts the marathon from a crime narrative into pure panic.
• Requiem for a Dream: Tone: Psychological drama / Tragic downward spiral. A harrowing, definitive conclusion to the theme. It leaves no room for recovery after a series of small, ill-advised choices snowball into complete destruction.

After my usual extensive Rotten Tomatoes research session on each film, I left with a whole slate of new movies to watch across Tubi, Pluto TV, Sling TV, The Roku Channel and YouTube. The fact that I could watch the majority of these films for free was the icing on top of a daily solo watch party that delivered the sort of cinematic nail-biting thrills I was searching high and low for.

I especially enjoyed Nightcrawler’s deep dive into the psyche of a man who wants success by any means, Uncut Gems’ presentation of the huge downsides of constantly betting big and Parasite’s showcase of the shades of grey present among its eccentric cast.

7 other movie themes I’ll play around with in the near future

Both chatbots did a great job of highlighting the right films for my thematic approach. So much so that I’m very much looking forward to testing out the following movie themes with ChatGPT and Gemini to see which films they push me toward next:

• "The Hero Has Had Enough"
• "The Villain Was Kind of Right"
• "The Guy Who Should Have Stayed Home"
• "People Are Trapped Somewhere and Things Get Worse"
• "The Movie Takes Place Over One Absolutely Insane Day"
• "The Opening 10 Minutes Promise Absolute Chaos"

The takeaway

In my search for movies I hadn’t seen before, sticking to a particular theme and requesting AI’s assistance in helping me find the appropriate films and streaming services that house them ended up being a fulfilling experience.

I’ve gotten used to using chatbots as my digital entertainment curators, so I was confident that they’d lead me to some quality cinema that was chock-full of interesting premises that resulted in the slow unraveling of its characters. I’m going to keep doing this with all sorts of cinematic themes to see where my movie-recommending chatbots take me next.

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Among the big new features Apple revealed with the Apple Watch Series 12 and Apple Watch Ultra 4 were a few that pricked the ears of those with privacy concerns. Apple's Audio Intelligence is a suite of AI-powered features that use the Apple Watch to listen in on what's happening around you, so that Siri can provide more proactive advice, as well as help you remember what it was you just heard.

The most controversial of these features were Siri Recap, which allows your watch to listen in on conversations you have throughout the day, and uses AI to take notes and generate summaries, and Live Rewind, which lets you go back 15 seconds and view a transcript of what was just said.

The idea behind this is that Apple can "jog your memory" on events from your day, and make sure you can stay present in the moment. Naturally there are a lot of people who aren't happy about the idea that someone's Apple Watch could be listening in on conversations without warning.

Apple has anticipated this, and when we spoke to John Ternus, the new Apple CEO, and Greg Joswiak, Apple's senior vice president of worldwide marketing, they revealed their approach to Recap's privacy at length.

"Whenever we do anything, we always do it with an eye towards privacy and security," Ternus said. "It's something we take very seriously and approach very thoughtfully.

On the subject of Siri Recap, Ternus pointed out that it's been possible to record audio and create transcripts of what people have said for a while — both on smartwatches and phones.

Ternus makes it clear that recap does not produce a recording or a transcript, with Jozwiak adding that Apple can't access what doesn't exist. "If we don't have a recording, it means no one else has the recording. It can't get hacked. It can't get delivered to somebody."

It sounds unrealistic, but Jozwiak does confirm that Apple had to develop a whole new chip to make Recap possible in this manner. In the process, he sees it as a feature that allows people to concentrate on what they're doing, while being able to generate "higher level notes" that aren't indiscriminately documenting whatever sensitive information is being said.

"We wanted to do this in a way that people feel comfortable using it, said Ternus. "And people around the user feel comfortable about its existence."

Siri Recap's privacy features

Apple has also posted a sizable explainer discussing all the different privacy features Recap incorporates.

The big privacy feature here is that any audio that the Watch hears is sent to Apple's Secure Enclave on the watch itself or your paired iPhone. Apple claims that it can't be accessed by the user, Apple, apps or even the operating system itself.

The audio also isn't recorded or stored, though the processed data is summarized and formatted by Apple's Private Cloud Compute. Apparently this involves condensed versions of the original conversation that are less than half their length, reducing the contents to the core, rather than a full-length transcript.

While the Private Cloud Compute data is not accessible by Apple or anyone else, it does still mean your data is being processed on the cloud rather than just on your device. Which may be too risky for some of you to agree with.

Other features include a lack of speaker attribution, which means nobody will be directly quoted or attributed to. Siri is also going to censor what it hears, and will automatically omit anything it deems harmful or sensitive. Apple says this includes language promoting self-harm, hate speech, financial data, authentication and personally identifying data and "government-assigned identifiers." So it won't be making a record of your social security number.

Summaries are automatically deleted after seven days unless you save them to the Siri app. Like all Siri data, those saved summaries can then be deleted from all synced devices at any time — though you can also export them to other apps, including Apple Notes. Syncing is also encrypted and done via iCloud, meaning only your own trusted devices can access those summaries.

Recaps aren't running all the time, and you do need to opt in to actually set them up. How they record depends on you, with Apple promising you can set up a schedule or manually toggle it on and off in the Control Center.

Because it's an AI feature, Apple has the usual caveat explaining that the summaries aren't going to be 100% accurate all the time. That doesn't fill me with a whole lot of confidence, especially after the fiasco with Apple News summaries that had to be recalled from iOS.

Live Rewind

If you've ever been pulled in two directions at once, you've inevitably had to ask "what did you just say?" to someone. Live Rewind is meant to help jog your short-short-term memory, by displaying a text snippet of the last 15 seconds of conversation when you double-press the Digital Crown on your Apple Watch.

To address privacy concerns around this feature, Apple says that these text snippets "disappear permanently from your Apple Watch approximately 30 seconds after the Apple Watch display dims," unless you purposely save them.

This doesn't fix everything

Apple suggests that people "be mindful" of everyone around them, especially if there are sensitive conversations happening. Though that may be giving people too much credit.

There are plenty of people out there that are considerate of other people's thoughts and opinions, but there are also plenty who aren't. They either forget recap is running, or straight up do not care that other people may not like it.

Admittedly, both Ternus and Jozwiak have a point: there are features that offer this sort of thing without any emphasis on privacy. Then again, it is more likely that people take issue with the implied always-listening approach Recap takes. I personally feel it would make a lot more sense to restrict it to manual control.

Whichever way you look at it, though, I guess it's still a better option than seeing people pull out their phones to video every little unusual thing they come across.

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To say that games have impacted my life in a major way would be the biggest understatement ever.

Discovering video games at a young age helped me find one of my favorite pastimes, led me to become a journalist and helped me interact with gaming & entertainment industry personalities I thought I’d never meet. For this year’s installment of National Video Games Day (a holiday meant to honor the legendary history, evolution and cultural impact of interactive media), I wanted to try something fun that combined my love for gaming and my newfound appreciation for AI.

I came to ChatGPT, Gemini, Claude and Perplexity with a simple request: “Give me your ranking of the 10 most influential video games of all time.” And after cataloging all their results, I came away with two thoughts: all four chatbots recognize the major trendsetters of the video game industry and two of them couldn’t agree on which game deserved to take the No. 1 spot.

Here’s what each chatbot delivered in response to my inquiry and even my own ranking of the 10 most influential video games of all time.

Where these four chatbots agreed and disagreed

All four chatbots wasted little time in proving their video game knowledge is stronger than I expected when they presented me with their personal ranking of the 10 most influential video games ever made:

• ChatGPT: Super Mario Bros., Tetris, Doom, The Legend of Zelda, Grand Theft Auto III, Minecraft, World of Warcraft, Pong, Half-Life, and Wii Sports.
• Gemini: Pong, Super Mario Bros., Tetris, Doom, Street Fighter II: The World Warrior, Super Mario 64, Grand Theft Auto III, World of Warcraft, Minecraft, and Dark Souls.
• Claude: Doom, Super Mario Bros., Tetris, World of Warcraft, Minecraft, The Legend of Zelda, Half-Life, Pong, Street Fighter II, and Grand Theft Auto III.
• Perplexity: Pong, Super Mario Bros., Tetris, Doom, The Legend of Zelda, Street Fighter II: The World Warrior, Super Mario 64, Grand Theft Auto III, World of Warcraft, and Minecraft.

What impressed me about ChatGPT’s acknowledgement of Super Mario Bros. as the most influential video game of all time was the factual reasons it used to back up its choice.

The chatbot noted that it practically revived the home-console gaming market after the crash of 1983, established the traditional conventions for 2D platformers that are still around to this day, produced arguably the most recognizable video game character of all time, helped cement the idea that gaming could deliver deeper experiences at home and showcased a textbook example of level design that teaches players what to do through gameplay.

Claude’s rationale for choosing Doom is as follows: Defined the FPS genre, pioneered shareware distribution, and its modding scene (WAD files) kickstarted the entire user-generated-content movement in gaming.

I also found it pretty wild how ChatGPT and Claude’s No. 1 picks were completely different from each other, while Gemini and Perplexity emerged with the same game for the top spot on their respective lists. Here’s the reasoning Gemini and Perplexity brought up to explain their decision to place Pong in the No. 1 position:

• Gemini: The Breakthrough: Proved commercial viability. Why It’s Essential: While not technically the first video game, Pong was the spark that established video games as a commercial industry. It proved that people would pay real money to play interactive digital games, launching arcade culture and home console gaming simultaneously.
• Perplexity: The essential commercial breakthrough. Pong made the video game legible to a mass public: two controls, one immediate competitive idea, and an arcade format that helped establish games as a viable entertainment business. Its simplicity became a template for accessible design.

Alongside ChatGPT’s ranked selections for its most influential games, it also brought up a bunch of games it deemed “painful omissions” that would make its top 20 list if permitted to do so.

Those 10 other games included Spacewar!, Pac-Man, Street Fighter II, Pokémon Red/Blue, Final Fantasy VII, The Sims, Counter-Strike, Dark Souls, Fortnite and The Last of Us. Claude also had two honorable mentions of its own: Fortnite and EVE Online.

As for my ranking of the 10 most influential video games of all time, I went with Pong (it seems like I agree with Gemini and Perplexity), Pac-Man, Super Mario Bros., Tetris, The Legend of Zelda, Street Fighter II: The World Warrior, Doom, Virtua Fighter, Half-Life and Grand Theft Auto III.

Final thoughts

I have to hand it to all four chatbots: they mentioned a strong selection of games that anyone who’s immersed in the hobby would mention on their list of the most influential titles in the still-thriving entertainment genre. Super Mario Bros., Pong and Doom all earned top billing among all four chatbots — all three games had a major impact on the gaming industry that captured millions of gamers’ attention and inspired plenty of iconic titles in their wake.

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I have a confession: when it comes to long, technical documents like manuals or white papers, I'm probably not reading every word. Don't get me wrong, I do care about the information in the documents and really need to know about my insurance policies and subscription terms, but I simply don't have the time to bury myself in hours of reading.

It's no secret that ChatGPT can summarize long documents, but recently I started using it differently. Instead of asking the chatbot to tell me what a document says, I ask it to extract the same information from multiple documents first — and only then compare them.

This is a small change but it makes ChatGPT infinitely more helpful for getting down to the fine print. I've been doing it recently and and there's one extra instruction I now add that makes the results much easier to trust.

Don't ask ChatGPT which option is better

My first instinct used to be uploading two documents and asking something like:

"Which of these is better?"

That's easy, but it's also giving ChatGPT far too much freedom. "Better" could mean cheaper, more comprehensive, more flexible or whatever the model decides matters most. Now, I make chatGPT do the boring work for me.

I upload both PDFs and use this prompt: Read both documents independently before comparing them.

For each document, extract the total cost, deductibles or additional charges, coverage or services included, exclusions, cancellation terms, renewal terms and any conditions that could significantly increase what I pay.

Cite the page number for every detail you extract. If something isn't explicitly stated in the document, write "Not found" rather than inferring or guessing.

Once you've completed the extraction, create a side-by-side comparison table showing the differences between the two documents.

Finally, identify five differences or unclear terms I should investigate before making a decision. Do not tell me which option to choose.

The overlooked trick is 'extract first, compare second'

With my prompt, I'm not asking ChatGPT to make the decision for me. I'm asking it to make the information easier for me to evaluate.

When you ask ChatGPT to summarize two long documents and compare them simultaneously, you're essentially asking it to decide what's important as it goes.

Instead, this prompt breaks the job into stages. First, ChatGPT has to examine each document separately and pull out the same categories of information. Only after that's finished does it compare those results.

Suddenly, instead of bouncing between two PDFs looking for whether one policy has a different deductible or one subscription has an early cancellation fee, I'm staring at two columns.

And differences are much harder to miss.

I added one more rule: show me where you found it by citing the page number for every detail.

I've learned the hard way that ChatGPT can make mistakes. It can misinterpret a clause, overlook something buried in a table or occasionally sound confident about information that isn't actually there. Page references give me a shortcut for checking its work.

If ChatGPT tells me Option A has a $500 deductible while Option B has a $1,000 deductible, I don't have to trust it blindly or reread 60 pages. I can jump directly to the pages it cites and verify those two numbers myself.

I'd much rather have ChatGPT tell me it couldn't locate a cancellation policy than confidently fill in the blank.

Real-world use cases for this prompt

I typically use this prompt for very technical things like changing wireless providers or insurance companies, but once I started thinking about the technique as structured comparison rather than summarization, I realized how many annoying decisions fit the same pattern.

You could use this hack for apartment leases to compare deposits, fees, renewal clauses and restrictions. Streaming plans to break down monthly cost, AI subscription plans, or even travel packages to check for what's included, refund policies and restrictions.

You can even modify the categories in the prompt depending on what you're comparing.

The important part stays the same: extract > cite > compare > flag what's missing.

Bottom line

I'm not going back to reading 60 pages side by side. There are documents I would never trust an AI to interpret without checking the original, particularly when money, legal obligations or insurance coverage are involved.

But that's also why I like this approach because I'm really not asking ChatGPT to replace my human judgement. I'm using it to point me toward the handful of pages where my judgment is actually needed.

Instead of reading two 30-page documents line by line and hoping I notice every meaningful difference, I can start with a structured comparison, investigate anything unusual and verify the details that could affect my decision.

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Top AI companies have spent plenty of time warning that models could make it easier for someone to develop a biological weapon. Now, Anthropic says it actually had to cut off a group of researchers after their behavior raised alarms.

According to "The New York Times", Anthropic blocked several users this year after spotting activity that looked suspiciously close to bioweapons research.

To be clear: Anthropic doesn't actually know if these researchers were trying to develop a deadly pathogen.

Advanced biology is inherently "dual use" — the same research that can lead to a lifesaving vaccine can potentially be used for something dangerous. But Anthropic flagged the behavior. The researchers reportedly circumvented geographic restrictions to access Claude and took steps to obscure the purpose of their work. That pattern was enough for Anthropic to pull the plug.

How they got around Claude's safeguards

The researchers didn't exactly "hack" Claude. Instead, Anthropic says they found ways to conceal both where they were accessing it from and what they were ultimately trying to accomplish.

In one case, a researcher reportedly accessed Claude from an unsupported region through U.S.-based virtual infrastructure and used an automatically generated account. Anthropic also found Claude requests being routed through a platform serving numerous life-sciences researchers, including virologists with ties to civilian and military institutions.

The researchers also attempted to obscure the purpose of their work to avoid triggering Claude's safeguards. That's particularly difficult to detect in biology because an individual request can look perfectly legitimate even when it contributes to a potentially dangerous larger project.

One of the cases reportedly involved a scientist seeking Claude's help drafting a grant proposal for research that would genetically modify the chikungunya virus to study characteristics including transmissibility and immune evasion. That's research that can have legitimate scientific purposes, which is precisely why Anthropic says it couldn't determine whether the researchers' ultimate intentions were benign or malicious.

Anthropic nevertheless decided the combination of sensitive research and attempts to conceal the activity was enough to shut down the accounts.

Why biology is the ultimate stress test

An AI can't mix chemicals in a petri dish or create bioweapons with physical lab equipment. But AI can act as an accelator.

For someone who already knows their way around a lab, a capable model can break down complex research, analyze data, troubleshoot problems and bridge niche technical gaps. It can give humans everything they need to make dangerous work easier and faster.

That leaves AI companies facing a massive gray area. A legitimate scientist and someone pursuing a biological weapon could ask many of the same questions. And misuse doesn't necessarily arrive as one blatant prompt. Someone can divide a larger project into dozens of innocent-looking tasks, making it much harder for a safety system to understand the bigger picture.

Then there's the problem of false positives. Make those safeguards too aggressive and you risk blocking legitimate scientific research. Make them too permissive and potentially dangerous activity can slip through.

It all comes down to human intent

It's important to clarify what didn't happen here, especially after Jacob Coxon's resignation from Anthropic yesterday, concerns about AI are at an all time high. We worry about models going rogue or autonomous agents acting on their own, but Claude did not go rogue, and autonomous AI agents didn't start plotting a bioweapon on their own. Humans were driving the bus.

That makes the risk far more immediate. The concern in this case isn't a super intelligent AI suddenly deciding to harm humanity. It's that powerful models are giving people capabilities they might not otherwise have had.

For everyday users asking Claude to draft emails, summarize documents or write code, nothing changes. But for the industry, the game has shifted.

So, what can AI companies actually do?

There isn't a perfect fix here. Blocking obvious questions only works when someone is clear about what they are trying to do. If a user breaks a dangerous project into dozens of harmless-looking requests, AI companies need safeguards that can recognize the larger pattern rather than judge every prompt in isolation.

That could mean looking for repeated attempts to bypass a model's safety restrictions, monitoring suspicious patterns across interactions and putting tighter controls around the most powerful scientific capabilities. Companies can also test new models before release to determine how much they could help someone with little expertise perform potentially dangerous biological work.

But every additional safeguard comes with a trade-off. The same systems trying to spot someone developing a biological weapon could also flag a researcher doing legitimate work. That's why Anthropic's disclosure is so important. The next phase of AI safety is about deciding when a pattern of otherwise legitimate-looking behavior becomes dangerous enough for a company to intervene.

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There are always those instances where I come across the kind of stories that remind me that AI shouldn’t be the final decision for a lot of things.

Imagine my shock and awe when I came across a report about three inexperienced hikers heavily relying on Gemini’s advice about trekking up Mount Shasta in California and needing to be saved because of it. Google’s AI assistant advised the trio to bring way less food and water than they actually needed, which turned their eight-hour expedition into a multi-day excursion that led to more suffering than celebrating.

Reading that terrifying piece of news reminded me of something my AI-savvy friend told me when I first started diving into everything ChatGPT, Gemini, Claude and Perplexity have to offer: “You can use it to help you plan things here and there, but you should always rely on your own intelligence and savvy to make the final decision on what to do.”

With that in mind, here are the three sorts of events I’ll never completely rely on to plan and three events I’ll never have any issue letting AI assist me with planning.

3 events I’d never let AI arrange for me

Right from the bat, I know that I’d never let AI completely plan any sort of outdoor experience that could lead me into a situation where I could be fighting for my survival.

AI is great for helping me research the sort of questions I should ask park service rangers and experienced professional hiking guides, plus the AllTrails plugin for ChatGPT is great for getting endorsements for the best verified trails. But I’ll never solely use AI to be the authority for wilderness treks, including mountain climbs, camping, river crossings and other weather-dependent expeditions. I’ll rely on human assistance when I’m looking to be as careful as possible when I want to head outside for some risky adventures.

When it comes to my physical well-being, I never revert to AI to get the final answer on what to do in certain situations. ChatGPT Health exists to let users utilize their health information with the chatbot to get a better grasp of their overall wellness by asking questions. That’s fine and all, but I’d never tap into ChatGPT and comparable AI tools to get the final word on finding out what I should do from a medical standpoint. I may ask AI to give me the sort of questions I should present to a medical professional or explain complex terminology, but I’ll never ask it to tell me to decide what surgery I should get for a certain injury, for example.

As for major financial decisions, that’s something else I’d never rely on AI to help me plan. The fear of believing a chatbot’s financial advice that’s nothing more than a hallucination that results in me losing tons of money scares me half to death. Blindly following AI’s advice about buying a home, starting a business, investing, etc. just isn’t the way to go — asking questions about the pros and cons of those financial decisions is fine, but using AI as the end-all, be-all for future monetary choices just isn’t the way to go. I’m totally okay with asking AI to give me the sort of questions I should consider before making such a massive economic decision, though.

3 activities I'd always use AI to help plan for me

With so many ChatGPT plugins catered towards helping users plan and book vacations, I’ve gotten accustomed to using OpenAI’s chatbot and comparable AI tools to help me plan vacations. Relying on AI to build a day-by-day itinerary, finding the best attractions based on my hobbies & interests and coming up with rainy-day alternatives are among the trip-planning activities I’m fine with AI helping me plan. Once I’ve gotten all the best recommendations for my future getaway from AI, I always make sure to do my own research to see if all of the info can be verified before I hop on a plane.

I’ll admit to not being the best party planner — I usually let someone else be responsible for that and handle the gift-giving portion of festivities. Lately, I’ve gotten used to tapping into Gemini to help me come up with the best venues, gift recommendations, clever decorations, music playlists and homemade menus to consider when planning a celebratory gathering. Once a BBQ-centric holiday like the Fourth of July, Labor Day or someone’s summer birthday rolls around, I’ll set up some plans with AI, share them with whoever else is part of the planning group and go from there.

If you’ve been following my AI writing up until this point, you’ve probably noticed that my 2026 revolves around the word “productivity.” ChatGPT in particular has supplied me with a wealth of personal productivity routines that I’ve used to plan my workdays. AI has risen to the occasion to help me set up a realistic to-do list, break up my work sessions into physical- & mental-amplifying exercises and find the best ways to wind down once the evening hours roll through. AI tools have definitely helped me get more work done, stay healthy and stay sane whenever I’ve used them to produce a productivity regimen.

Final thoughts

I always keep this system in place for certain situations when I consider having AI help me set something up: let AI take the lead for low-stakes situations, let AI assist & help me verify certain bits of information for medium-stakes events and let AI assist & rely on more accomplished individuals to give me the answers I need for more high-stakes decisions.

I’ll have no issue letting Gemini help me plan a weekend sci-fi movie marathon, but I’ll never ask it to help me get out of a major legal situation. Having an AI hallucination resulting in me being behind bars is something I never want to happen…

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Like a lot of people, particularly those working in tech, ChatGPT is practically my default browser tab. With all the plugins available, Codex, and Work, I've discovered it's a great place to dump my messy notes and brainstorming angles.

But the problem with ChatGPT isn't its reasoning ability or capabilities, it's the container. The standard chat interface gets muddy, key details are often lost and the next thing I know I'm copying chunks of my text to an external draft because ChatGPT has completely taken over.

I knew there had to be a better way, so I gave up my dedicated workspace tool and spent a full workday using YouMind instead.

Here is what surprised me most about ditching a conversational chatbot for an asset-first workspace.

1. Chat threads make terrible knowledge bases

In ChatGPT, your context is trapped in a linear scroll. If you upload four different reference documents, a YouTube video transcript and a web page, you have to constantly remind the model which source you are referencing as the thread grows longer. What's different about YouMind though, is that it handles organization through project Boards.

With the YouMind platform, my reference material lived in a dedicated sidebar folder rather than clogging up the chat stream. This was something I didn't even know I needed, but the first time I wanted to query and interview transcript and clicked on the source directly, I was obsessed with how easy and organized it felt.

And, when I wanted cross-source synthesis, I queried the whole board. YouMind lets users treat sources as persistent assets instead of conversational chat history, which help to immediately eliminate the context drift that usually happens five prompts into a ChatGPT session.

2. The 'Ask vs Agent'" mental shift changed my output speed

With ChatGPT, you are always in one continuous chat mode. For me, I find I have to be extremely specific with the chatbot such as prompting it to "Analyze this, but don't write or edit." For some reason, if I show ChatGPT a document, it starts assuming things before I even prompt it to do anything. But YouMind splits actions into two explicit modes.

Ask Mode: Pure inquiry and interrogation. It reads your materials, answers questions and cites exact references without trying to prematurely generate copy.

Agent Mode: Pure production. Once I knew what the angle was, I flipped to Agent Mode, chose a specific "Skill," and had it generate a summarized document and slide outline based directly on my approved notes.

For anyone who teaches workshops, gives presentations at work, or gathers materials for studying, this is a real gamechanger. Separating research synthesis from artifact creation stopped the model from jumping the gun on generic actions before the facts were ironed out.

3. Model agnosticism cures ecosystem fatigue

When you rely solely on ChatGPT, you get GPT’s tone and style across everything you touch. Every response, whether it's travel advice or a professional email drafted to your boss, sounds the same. That means, if you want Claude’s technical precision, you have to copy your context, open another tab, re-upload your files, and start over.

Inside a single YouMind board, you can switch between models on the fly. Yes, you read that correctly; you're not restricted to just one model with YouMind. You can use Claude to refine and edit, then switch to GPT for structural outlines, or lean on Gemini for quick web research. Having multiple model families under one roof without moving files around felt remarkably fluid. It's one of the biggest reasons I plan on using YouMind a lot more.

4. Granular editing beats the 'regenerate' lottery

The most infuriating part of editing drafts in ChatGPT is the rewrite loop. You ask it to tweak a single sentence, and it generates an entirely new 600-word response. This is one of the aspects of ChatGPT that drives me crazy. Since it does that, it essentially forces users to scan and re-read everything again and again just to ensure everything has remained in place and nothing was accidentally cut.

In YouMind's Crafts editor, text behaves like a shared Google Doc, so revisions show up inline with visual differences. From there, you can accept, reject or tweak individual suggestions.

You can highlight just one clunky line and prompt the AI to fix only those words while keeping the surrounding copy untouched.

For anyone who cares about preserving specific wording and cadence, having inline change-tracking inside the AI interface is a massive workflow upgrade over standard chat.

What I missed about ChatGPT

Swapping a complete workflow for the day isn't easy and, even though YouMind is pretty easy intuitive, there were still some pretty important features that I missed about ChatGPT.

Raw conversational speed: For lightning-fast, throwaway queries ("convert this to grams" or "give me 10 alternative verbs for this social post), firing off a two-second prompt in ChatGPT is still faster than setting up or navigating a board.

Complex multi-step reasoning: While YouMind lets you access top frontier models, ChatGPT’s native canvas and advanced reasoning toggles still feel slightly more dialed in for heavy logic, reasoning or deep code debugging.

Mobile accessibility: ChatGPT's mobile experience is mature across both iOS and Android. YouMind was pretty good on desktop but not as great on mobile.

The takeaway

ChatGPT is an incredible conversational engine, but it is fundamentally built like a messaging app. For complex research and writing projects, treating an LLM like an instant message conversation creates artificial bottlenecks.

Spending the day in YouMind proved that organizing context into tight project boards and having an inline document editor makes turning research into real deliverables significantly faster. I won't be abandoning ChatGPT for quick, standalone questions, but for deep-dive writing and multi-source research, it's now my new go-to.

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We recently asked AI to rank which jobs would be taken by AI first. Now, Anthropic, the company behind Claude is trying to answer the question we are all asking: what happens if AI keeps getting better?

The company's new economic model explores what happens the more AI grows, specifically, how it could affect jobs, wages and the U.S. economy through 2030. Some of the results are striking.

Under one set of assumptions, the economy grows significantly while wages for "knowledge workers" barely move. The phrase was first coined by management theorist Peter Drucker in 1959 to describe a growing shift in the global economy away from traditional manual labor and toward intellectual and information-based work. A knowledge worker is essentially a professional whose main capital is their expertise, critical thinking and specialized knowledge.

When those assumptions were pushed further, the divide becomes even more dramatic, with the economy growing 32.4% larger than it otherwise would have while knowledge-worker wages fall more than 10%.

To be clear, Anthropic isn't predicting either outcome. The company is just trying to show how factors including AI adoption, automation and workers' ability to change careers could determine who actually benefits if AI delivers the productivity boom its developers have been promising.

Anthropic modeled three different AI futures

We've also covered the future of AI and what the world will look like in 2035. Anthropic's model lets researchers adjust assumptions including how capable AI becomes, how widely businesses adopt it, how autonomously it can work, how much more productive it makes people and how easily displaced workers can find new occupations.

The company then uses three sets of assumptions to illustrate modest, substantial and extreme AI scenarios.

The modest version looks more like previous technological shifts. AI improves productivity and the economy grows, but the effects remain largely within historical norms.

Things look considerably different in the substantial scenario, where AI becomes capable of performing half of all knowledge-work tasks by 2030 and can perform most of those tasks autonomously.

That doesn't mean AI is doing half of all knowledge work. Businesses don't adopt the technology everywhere, so people still perform the majority of knowledge-work tasks across the economy.

Even with that limitation, Anthropic's model has economic growth running at roughly twice its normal rate.

The economy could boom without your paycheck doing the same

In Anthropic's substantial scenario, U.S. GDP reaches $36.3 trillion by 2030, 8.3% higher than it would have been without AI.

Knowledge-worker wages, meanwhile, are essentially flat. Part of the reason is that Anthropic doesn't treat a job as one thing that AI either can or can't replace. Instead, it breaks occupations into individual tasks, some of which AI can augment, some it can automate and others that still require a person.

Consider nursing, an example Anthropic highlights in the model. AI might be able to draft discharge instructions, help monitor patients or organize a care schedule. Other administrative tasks could eventually be automated altogether.

But an AI chatbot can't bathe a patient. Therefore, demand for people performing some types of digital work can fall while the productivity created by AI generates more demand elsewhere.

Anthropic uses construction as another example. If AI dramatically reduces the time required to design and permit infrastructure, more projects could become viable. Those projects still need people to build them, potentially increasing demand and wages for construction workers.

Coders could end up becoming electricians

The calculation changes when AI can automate enough of an occupation that employers simply don't need as many people doing it.

Anthropic uses coders and call-center workers as examples of people who might eventually move into less AI-exposed occupations such as nursing or electrical work.

How easily people can make those transitions turns out to be one of the most important variables in Anthropic's model. If AI eliminates work faster than displaced employees can move elsewhere, unemployment rises, which is also one of the reasons the more extreme results should be reviewed cautiously.

What happens when Anthropic turns the assumptions way up?

Anthropic's extreme scenario is a stress test of what could happen if several aggressive assumptions about AI all come true.

In this version, AI becomes more productive than humans at the vast majority of knowledge-work tasks, performs nearly all of them autonomously and doesn't create enough new types of knowledge work to replace what disappears.

Anthropic says reaching that point would likely require recursively self-improving AI alongside extraordinarily fast adoption. Under those assumptions, the numbers become enormous. By 2030, U.S. GDP reaches $44.4 trillion, making the economy 32.4% larger than it would have been without AI.

Knowledge workers don't experience a corresponding windfall. Their wages fall by more than 10%, while unemployment rises beyond levels normally associated with recessions. This scenario reveals a lot about the relationship between economic growth and the people generating it.

Most Americans aren't expecting the extreme version

As mentioned in the scenario site, Anthropic also asked 10,980 Americans in August what they expect AI to be capable of, how quickly they think businesses will adopt it and how difficult it will be for displaced workers to find other jobs.

When those answers are fed into the model, the typical respondent lands much closer to Anthropic's substantial scenario than its extreme one.

Those expectations produce an economy roughly 10% larger by 2030 than it would have been without AI, with unemployment around 5%. Around 10% of respondents gave answers consistent with Anthropic's extreme scenario.

Even that middle ground would represent a significant change in how millions of people work.

AI capable of performing half of all knowledge-work tasks by 2030 could change which careers companies are hiring for, which skills command higher wages and whether some of today's most sought-after white-collar jobs remain as valuable as they are now.

What this means for your job

There are plenty of reasons to be cautious about taking any of these numbers literally.

Anthropic's model doesn't account for government responses, business cycles, financial-market disruptions, changes in consumer demand or catastrophic AI risks. It also doesn't model a future in which highly capable robots can perform much of today's physical work, which could dramatically change the outlook for occupations that appear relatively protected here.

And again, these are scenarios, not Anthropic's predictions for 2030. What they do show is that the future of work may be more complicated than the familiar question of whether AI will take your job.

AI could make some workers far more productive, reduce demand for others and create new demand in occupations that have little to do with sitting behind a computer. At the same time, the economy could grow much faster without those gains showing up proportionally in workers' paychecks.

More from Tom's Guide

• AI is turning ordinary photos of kids into sexual abuse imagery — here's how to protect your family
• Meta just launched an AI that can actually run your life online — here's what Muse can do
• Gemini 3.8 Flash has one major advantage over GPT-6 Astra and Claude Fable 5.1

As of September 8, 2026, ChatGPT Images has received a substantial upgrade, taking it from version 2.0 to 2.5.

Beyond just taking your uploaded photos and making them look even prettier, this update adds a host of features that make it even more efficient at handling your photo-related requests. According to the official OpenAI blog announcing the news of ChatGPT Images 2.5, ChatGPT’s latest image editing tool can produce more natural lighting, generate richer textures and is more capable of following your photo editing instructions more reliably as it works across iterative prompts and is much better at preserving multiple subjects in your reference pics.

ChatGPT Images users will also be happy to know that 2.5 works even faster than 2.0 since it generates images 50% faster than its predecessor. And with the introduction of “Sketch,” users can draw directly into ChatGPT and use it as a reference for the final image you’d like to see edited. Currently, ChatGPT Images is available to all ChatGPT, ChatGPT Work, and Codex users across desktop, mobile, and web.

The ChatGPT Images 2.5 blog showed off some cool examples of before-and-after pics that it's capable of delivering. But I asked ChatGPT to offer me some fun prompts worth experimenting with this update. Here are the 7 best ones (with two visual examples of the ones that ended up being my faves).

Make ChatGPT Images 2.5. do more than just “make me a cool picture”

Just like before, using ChatGPT Images is as simple as clicking on the “+” button inside the prompt bar, uploading a photo from your computer or attaching one that’s already in your ChatGPT library and tapping on the + button again to access the “Create image” option. Then, with your chosen photo and the Create Image option activated, enter your prompt to see what newly refined visuals ChatGPT can produce.

As far as fun image-creating and editing prompts go, these are the best ones ChatGPT generated for me (with one of them being a super viral one that I’ve seen all over my timeline):

• It’s time to go retro: Show me what I would look like if I was in the '80s.
• Turn yourself into a movie poster: Using this photo of me as the reference, turn me into the star of a huge Hollywood action movie. Create an original movie title, tagline, billing block, and release date. Make the poster look like a legitimate theatrical one-sheet, with dramatic lighting, cinematic composition, and an expensive blockbuster aesthetic. Keep my face and recognizable features highly consistent with the reference photo.
• Give yourself 7 completely different lives: Using this photo of me as the reference, create a set of seven distinct portraits showing me in seven alternate lives: astronaut, rock star, medieval knight, professional wrestler, video game hero, detective in a 1940s film noir, and futuristic cyberpunk bounty hunter. Keep my face, age, and recognizable features consistent in every version, but completely transform my clothing, environment, and styling.
• Create your own action figure: Turn me into a collectible action figure displayed inside a premium toy package. The packaging should have a fictional character name, an illustrated background, accessories that reflect my hobbies, and a realistic plastic window. Make it look like an actual product photographed for a major toy retailer. Include three accessories and a humorous “special ability” on the packaging. Preserve my recognizable appearance from the reference photo.
• Recreate your childhood photo — in the future: Using this photo as the reference, create a photorealistic version of the same scene taking place 30 years in the future. Preserve the people, poses, and important visual details from the original photograph, but update their clothing, surroundings, technology, architecture, and environment to reflect a believable future. Make it feel like an authentic photograph from that future rather than science fiction concept art.
• Make a ridiculous “Where Are They Now?” photo: Take the people in this photograph and imagine where they would realistically be 20 years later. Preserve their identities and recognizable facial features, age them appropriately, and create a completely new candid photograph showing what their lives might look like. Give each person a different believable career, outfit, and environment. Make the result feel like an authentic documentary photograph rather than an AI-generated image.
• Turn the worst doodle you've ever drawn into something awesome (You can type @Sketch in ChatGPT and draw directly in the interface): Turn my rough sketch into a spectacular finished illustration. Keep the basic shapes, positioning, and idea from my drawing, but transform it into a highly detailed fantasy scene with dramatic lighting, believable textures, and professional concept-art quality. Do not “fix” the underlying concept — make my terrible drawing look intentionally awesome.

To see if ChatGPT Images 2.5’s highly lauded features were worth all the hype, I threw in two of my photos to see if the chatbot could make me look like a super cool ‘80s icon and a blockbuster action movie star. I was pleased with the finished results—let me know if you feel the same:

Final thoughts

I haven’t messed around with ChatGPT Images in a while, so the release of its 2.5 update seemed like the perfect opportunity to see if it's worth taking for a spin. I’ll be sure to comb Reddit threads, my social media timelines and ChatGPT itself for a mix of other fun prompts I can try out with Images 2.5 to see what other cool images I can generate of me, my friends and my family.

More from Tom’s Guide

• I tried Google’s new ‘Ask Maps’ feature for date night — it was shockingly good
• Gemini 3.8 Flash has one major advantage over GPT-6 Astra and Claude Fable 5.1
• Meta just launched an AI that can actually run your life online — here's what Muse can do

Meta has launched Muse, a new personal AI agent designed to work across the apps and services you already use. Unlike a chatbot that gives you an answer and waits for another prompt, Muse can open a browser, fill out forms, send emails, book travel, make purchases and continue working on a task after you close the app.

You can even give it a bigger goal and let it figure out the steps required to get there, which makes Muse one of the clearest examples of where consumer AI appears to be headed.

But there’s an obvious tradeoff: For Muse to become genuinely useful, you have to give it access to a remarkable amount of your digital life.

Muse isn't just another chatbot

Meta describes Muse as a “personal AI agent,” which is similar to what we've seen from Gemini and ChatGPT recently. Like the AI agents from Meta competitor's Muse is designed to do more.

According to Meta, the agent can open websites, fill out forms and negotiate on your behalf. It can book travel, send emails and make purchases, checking back with you when it needs approval for certain actions.

It can also keep working after you close the app, which opens the door for much longer-running tasks. This could include tasks such as trying to lower a bill, adapting a training plan when your schedule changes or even selling a car, according to Meta's examples in the company press release.

Muse can also remember information you've previously shared and use it later. Meta says it could notice a recipe Reel you saved on Instagram, turn it into a grocery list and remember your friends' dietary restrictions when helping organize a dinner party.

In other words, the goal isn't necessarily for you to keep prompting Muse. It's for Muse to learn enough about your life that it can start anticipating what you might need.

It can spend money for you

One of the biggest differences between an AI assistant and an AI agent is what happens when money gets involved. Muse can make purchases using Stripe's Link payment system. Instead of giving the agent your actual card number, Link generates a one-time-use card for the transaction.

Meta says Muse is also the first AI agent covered by Link's purchase protections, which can include things such as no-fee returns and protection for eligible lost or damaged items.

Shop Pay support is expected to arrive later, while Meta says integration with 1Password is also coming so Muse can use credentials stored in a user's password manager.

That could make tasks such as shopping considerably more convenient. It also raises the stakes considerably if an agent misunderstands what you asked it to do.

Meta built a second AI to watch the first one

Meta clearly knows that giving an autonomous AI access to email, accounts and payments creates an entirely different security problem. Muse therefore runs inside what Meta calls a Secure VM — essentially its own isolated computer in the cloud.

There's also another AI agent running alongside it called Sentinel, separated from Muse at the system level and reviews what the agent is trying to do before its actions reach the internet. Meta says Muse also asks for permission before sensitive actions such as sending an email or making a purchase.

Users can decide which services Muse connects to and what permissions it receives. Giving Muse access to email, for example, doesn't necessarily mean allowing it to send messages.

There's also an audit trail showing what the agent has done and what it plans to do. Meta says Muse doesn't see passwords or payment information directly. Credentials are kept in secure storage and can be used by the agent without revealing the underlying information to it.

Later this year, Meta plans to introduce what it calls Muse Confidential VM, which will encrypt the entire virtual machine with a key held by the user. Meta says that would prevent even the company itself from accessing the data and conversations stored inside.

Safeguards and trust

All of those safeguards matter because Muse potentially has access to some of the most sensitive parts of someone's digital life. And Meta's own testing shows why autonomous agents remain difficult to secure.

Reuters reports that Meta originally planned to release Muse earlier this year but delayed the launch while it worked on security.

Internal testing reportedly produced mixed results. In one particularly concerning example, an employee said the agent managed to get around safeguards and expose personal iCloud photos after being asked to identify toys visible in pictures from a child's birthday party.

Other employees reported reliability problems, including an agent that stopped refreshing a webpage while monitoring hard-to-find tickets and sometimes silently ignored errors.

Meta told Reuters that it had done enough additional security work to reach the threshold required to release Muse, although the company acknowledged that mistakes remain possible.

Final thoughts

We've now entered a post-chatbot era. There are already plenty of AI agents capable of using computers, browsers and other tools. What's potentially significant about Muse is who Meta wants using it.

Muse is rolling out in the U.S. on iOS and Android and through the web, and you can also talk to it directly through WhatsApp. Meta says support for its AI glasses is coming soon. There's a free tier, with paid plans available for people who need heavier usage.

More from Tom's Guide

• AI is turning ordinary photos of kids into sexual abuse imagery — here's how to protect your family
• I asked ChatGPT, Gemini, Claude and Perplexity to rank the 10 jobs most likely to be replaced by AI — here's what they all agreed on
• Gemini just got a 'floating bubble' multitasking upgrade that's a game changer on Android phones — here's how to use it

Out of all the negatives I can admit about myself, setting up dates sticks out as one of my biggest weaknesses.

In the past, I’ve struck out horribly by trying to woo my potential mates by taking them to the sorts of places that made them rethink ever meeting up with me again. My first date fumbles have led me and whoever was unlucky enough to see me to dive bars with horrible lighting, restaurants with disappointing menu options and lounges with booming speakers that didn’t allow for a whole lot of meaningful conversations.

Somehow, someway, I managed to nab myself another opportunity to enjoy a nice night on the town with someone. And this time, I made it my mission to find out her likes and dislikes when it comes to hanging out & having fun.

With all the information in tow, I got a bright idea — take all of my future date’s favorite hobbies, interests, and types of hangouts to Google Maps and use Ask Maps to find the perfect spots worth considering. And to my surprise, it offered me a solid selection of date-worthy locations.

7 date night suggestions that made my planning less of a headache

As I’m sure you’ve already noticed from the screenshot posted above, I told Google Maps’ Ask Maps feature all about my future date’s favorite things—since she’s an old soul with an affinity for the more geeky pastimes I’m also into, I had a feeling there would be plenty of viable options to consider as the perfect date locales. Ask Maps showcased its date spot picks across two categories: Interactive & Playful Dates and Intimate Vibes & Elevated Floors.

Here are the New York City settings that were listed under the first group:

• Barcade: If you want a classic, high-energy date centered around gaming, heading to Barcade in Chelsea is a perfect choice. It keeps the focus purely on adult socializing over retro cabinets rather than tickets and prizes. Reviewers call it a fantastic adult playground for nostalgic gaming. Challenge her to a cooperative game like X-Men or classic pinball. Check out their extensive, rotating selection of American craft beers on tap.
• The Cinemas NYC: For a luxurious spin on movie night, The Cinemas NYC (IPIC Theaters) at the Seaport turns a screening into a premium experience. It is completely different from your standard theater with its plush seating arrangements and top-tier hospitality. Patrons rave about the luxurious, private feel of the double seating pods. Book a “Premium Plus” ticket to get reclining leather seats that come with pillows and blankets. Use the in-seat service to order gourmet dishes and cocktails directly to your shared table without interrupting the film.
• Izakaya Nana: Tucked away in Flushing, Izakaya Nana is an absolute dream destination for anyone who loves Japanese fantasy aesthetics and otaku culture. The entire venue doubles as a massive homage to graphic novels and subculture. Otakus admire the manga-panel-lined walls, traditional tatami spaces, and classic anime projections running in the background. Ask to be seated in a booth surrounded by their massive library of manga volumes. Rent traditional kimonos on-site to fully immerse yourselves in the experience.
• Other Half Brewing Company: If she is a true craft beer geek, making a pilgrimage to the original Other Half Brewing Company in Brooklyn is mandatory. This is the epicenter where modern craft culture evolved. Visitors note the incredibly relaxed, friendly taproom environment. Sample their world-famous Hazy IPAs and innovative Oat Creme double-hopped variations at the source. Snag a few limited-release four-packs from their retail fridge to take home after a date.

After observing the four more adventurous options Google Maps’ Ask Maps assistant provided me with, I took note of the three other nightspots that are geared more towards intimate meetups:

• Eavesdrop: For a sophisticated, audio-forward evening, Eavesdrop in Greenpoint is a minimalist listening bar specifically designed around a high-end sound system. It is curated so that the music remains a central showcase without drowning out your intimate conversation. Patrons love the sleek wood styling and crystal-clear acoustics. Try to secure seating near the cork-lined turntable booth to watch the vinyl selection up close. Sip on their craft cocktail menu, which features creative, Asian-inspired flavor profiles.
• Record Room: Hidden along the Long Island City waterfront, Record Room delivers a speakeasy atmosphere built entirely around the art of the spin. It functions as a cozy neighborhood cafe by day before transforming into a moody, music-centric lounge at night. Visitors frequently praise the highly talented local DJs spinning classic retro sets exclusively on vinyl. Enjoy the dramatic aesthetic of the room, which features custom Hi-Fi loudspeakers and walls adorned with records. Make a reservation ahead of time, as the space is quite intimate and fills up quickly on weekends.
• Gaonnuri: If you want to elevate a standard dinner date, Gaonnuri takes classic Korean barbecue and moves it to a stunning penthouse space on the 39th floor. It offers an upscale atmosphere that feels completely removed from the frantic pace of the streets below. Diners highlight the incredible, unobstructed views of the Manhattan skyline. Enjoy a fully hosted experience where the attentive waitstaff handles all the tabletop grilling for you. Appreciate the advanced ventilation system, which ensures you leave dinner without any lingering smoke smells.

Out of all the spots that were presented to me, the ones that ended up making the final cut after I sent them to my date were Barcade, Izakaya Nana, Eavesdrop and Record Room. While the skyline views and delicious delicacies presented by Gaonnuri intrigued us, their high prices brought our increased levels of hype out of orbit as we opted for Ask Maps’ more affordable offerings. If we end up talking beyond our initial meetups, then maybe we’ll consider getting a table over there (honestly, that place seems more catered to serious couples).

The takeaway

I know I’m going to be lambasted with comments about how much of an amateur I am when it comes to planning dates. While I’m not guilty of taking women to chain restaurants and overly loud places that lead to us screaming in each other’s ears, I’ve taken plenty of swings and missed with some of the locations I’ve chosen. From now on, I’ll refrain from doing my usual Google search for “best date spots [location],” ask for date recommendations while also considering my date’s hobbies & interests and forward them to my prospective date to see if any of them match their vibe.

More from Tom’s Guide

• AI is turning ordinary photos of kids into sexual abuse imagery — here's how to protect your family
• Chrome could soon let you ask Google about anything on your screen — even outside the browser
• Gemini just got a 'floating bubble' multitasking upgrade that's a game changer on Android phones — here's how to use it

This month has been a whirlwind for AI, with major new models arriving within days of one another. Google just released Gemini 3.8 Flash, and at first glance it has a tough job ahead of it. GPT-6 Astra is OpenAI's most capable model, while Claude Fable 5.1 is Anthropic's latest powerhouse for coding and long-running projects.

However, there's one area where Google's new Flash model has an advantage over both: video understanding.

Gemini 3.8 Flash can take video directly as an input and reason about what's happening across it. GPT-6 Astra doesn't support video input, and neither does Claude Fable 5.1. And while this might sound like a minor difference, in practice, it actually opens up an entire category of things users can ask Gemini to do that aren't native to the other two models.

Gemini can actually watch your video

Gemini 3.8 Flash accepts text, images, video, audio and PDFs as inputs, with a context window of just over 1 million tokens.

Video is particularly interesting because Google isn't simply converting a clip into a handful of screenshots and asking Gemini what's in them.

Gemini 3.8 Flash supports what Google calls "agentic video understanding." Instead of processing an entire long video in exactly the same way, the model can navigate through its timeline and decide which transcripts, frames and audio it needs to inspect to answer your question.

Google says this approach can use up to 88% fewer tokens on long-form video while delivering roughly 7% higher quality.

That means you could give Gemini a long recording and ask something surprisingly specific such as, Where did the speaker mention a particular subject? What happened immediately before someone entered the room? What was being shown on screen when a certain point was discussed?

Just from those prompts, Gemini can return answers tied to specific moments in the video rather than forcing you to scrub through it yourself.

GPT-6 Astra and Claude Fable 5.1 can't do this natively

GPT-6 Astra has a slightly larger 1.05-million-token context window and supports text and images, but OpenAI's model documentation explicitly lists both audio and video input as unsupported.

Claude Fable 5.1 has a 1-million-token context window and impressive vision capabilities, particularly for understanding diagrams, charts, tables and other visual information. But Anthropic lists its input/output capabilities as "text and images > text."

Users can extract frames, generate a transcript or use additional tools before handing that information to the model, it just isn't a native feature in the same way it is with Gemini. Gemini 3.8 Flash was designed to accept it.

Audio is part of the advantage, too

That key difference also applies to audio. Gemini 3.8 Flash accepts audio directly alongside its other input types. That means the model can reason over what it hears as part of a larger multimodal task rather than requiring you to turn everything into text first.

And video gives it both sides of the equation. Google says Gemini's video processing can work with the visual frames, audio and timestamps together. Its agentic mode can even decide whether it needs to retrieve a transcript, inspect frames or examine audio from a particular section of a video.

That's useful for everything from analyzing a lecture to finding a particular moment in a vacation video.

The takeaway

What's particularly interesting is that this isn't Google's biggest, most expensive model. Google describes Gemini 3.8 Flash as its most intelligent Flash model yet, designed to combine complex reasoning and agentic capabilities with the speed and cost efficiency the Flash family is known for.

GPT-6 Astra and Claude Fable 5.1 may be stronger choices for other jobs. Both are explicitly designed around difficult reasoning and long-running agentic work, and choosing an AI model based on a single capability would miss the bigger picture.

But video is becoming even more important of what we give AI. From class presentations and tutorials to live video rather than text, Gemini 3.8 holds the advantage over its two biggest rivals. To get started, all you have to do is upload a video or paste a link to the video in the chat and ask it to watch.

More from Tom's Guide

• AI is turning ordinary photos of kids into sexual abuse imagery — here's how to protect your family
• Anthropic modeled what AI could do by 2030 — the economy gets 32% richer while workers get left behind
• Meta just launched an AI that can actually run your life online — here's what Muse can do

A picture of my children at the beach, my son playing soccer or even my entire family, smiling in front of our house are all examples of photos I've posted to social media. I know I'm not alone, considering just how often I've seen similar images highlighting the goings-on of modern lives.

But AI has created a disturbing new risk that allows the use of ordinary photos of real children like the ones I mentioned above, to be manipulated into sexual abuse imagery without the child — or their parents — ever knowing.

To be clear, this is not a theoretical threat.

332 AI-generated child sexual abuse ads slipped through

A new investigation from the Tech Transparency Project (TTP) found hundreds of ads containing AI-generated child sexual abuse material (CSAM) running across Facebook and Instagram. Researchers identified four real children whose ordinary photos had been manipulated, according to WIRED, including two teenage influencers, a preteen whose image appeared on a stock-photo site and a young member of a European royal family.

In total, TTP found 332 ads containing AI-generated child sexual abuse material, or CSAM. Most depicted a child whose photograph had been manipulated using AI to make it appear they were performing a sexual act.

The findings are an alarming reminder of how generative AI has changed the risks around sharing photos of children online. Creating convincing fake imagery no longer requires an explicit photograph in the first place. An ordinary picture can provide the raw material.

How ordinary photos become AI-generated abuse

Generative AI image tools can take an existing photograph and modify parts of it while preserving recognizable features of the person in the original.

That's what researchers say happened to several of the children identified in the Meta ads.

According to WIRED, researchers were able to trace images of four minors back to their original sources. Two were teenage influencers with public social media accounts. Another was a preteen whose photograph was available through a stock-photo website. The fourth was a young member of a European royal family.

None of those original photographs needed to contain sexual material for them to be misused.

"AI apps are making it far too easy to create realistic criminal imagery of child sexual abuse, creating the new risk of everyday photos of children being taken and transformed into sexual content," Emma Hardy, director of communications at the Internet Watch Foundation, told WIRED.

Once an ordinary image is publicly accessible, someone can potentially download it and feed it into an AI tool designed to alter photographs.

Meta's AI didn't catch hundreds of the ads

The scale of the latest investigation also shows how difficult the resulting content can be to stop.

In August, TTP researchers initially uncovered 53 ads containing child sexual abuse material across Meta's platforms. Meta subsequently said many of those ads had appeared before the company introduced new AI technology intended to improve its ability to detect violating ads when they were uploaded.

However, researchers kept finding them. In fact, TTP says it ultimately identified 332 ads containing AI-generated CSAM, with hundreds appearing after Meta had announced its improved detection technology.

That is particularly significant because these weren't simply Facebook or Instagram posts that escaped moderation. They were paid advertisements.

Meta says ads are reviewed before they're allowed to run and that automated systems play a major role in that process.

Meta spokesperson Tracy Clayton told WIRED that the company does not tolerate nudify apps or child exploitation, whether the imagery involves real children or is generated by AI. Meta said bad actors deliberately attempt to evade its detection systems and that some of the videos were harder to detect because images of children appeared only briefly or were blurred.

The company said many of the ads researchers identified had already been removed, most received fewer than 200 impressions and it received less than $5,000 in payments from the ads. But researchers documented instances in which exposure increased after an ad was reported.

TTP says one ad involving a real teenager had reached four European accounts when it was reported to Meta. Several days later, when Meta removed it, the ad had reached more than 330.

The investigation shows the tools are mainstream

Researchers found ads directing people toward nearly 50 apps available through Apple's App Store and Google's Play Store. Around 300 of the roughly 350 ads examined in the broader investigation promoted AI image or video generators, according to WIRED.

Apple told WIRED that some developers initially submitted compliant versions of their apps before subsequently adding prohibited nudification capabilities. Apple said it removed 17 of 20 apps identified by researchers and took action against the remaining three, as well as seven additional apps WIRED identified.

Google said it removed all apps included in the report and suspended hundreds of other apps for violating its policies.

Still, these finding reveal a problem that extends beyond any single platform because AI can be used to create the imagery. An app store can distribute the tool used to make it. An advertising platform can then distribute ads promoting it.

Each layer may have its own safety systems, but abusive material only needs to slip through those systems once to reach users.

What to do if you find an AI-generated image of your child

If you discover sexualized AI imagery involving your child, don't repost or widely share the image in an attempt to warn others.

Instead, preserve information that can help identify where the material appeared, such as the account name, page address and other surrounding details, and report the content directly to the platform.

In the U.S., suspected child sexual exploitation can also be reported to the National Center for Missing & Exploited Children's CyberTipline.

Parents can also use NCMEC's Take It Down service, which is designed to help stop the online sharing of nude, partially nude or sexually explicit images or videos involving someone who was under 18. The system creates a digital fingerprint, or hash, from an image without requiring the image itself to be uploaded.

Since AI-generated imagery creates newer and more complicated scenarios, parents who aren't sure whether a manipulated image qualifies should still report what they've found rather than trying to determine that themselves.

The takeaway

Parents have been warned about "sharenting" and children's digital footprints for years. Sharenting is a term that combines "sharing" and "parenting" and is the practice of parents sharing images, videos and personal details about their children on social media.

Although parents can't entirely eliminate the risk of AI abuse on the images or videos they post, but reducing the number of publicly accessible photos of your children and being more selective about what you share, can reduce the amount of material available to people who might misuse it.

More from Tom's Guide

• ChatGPT-6 Astra is here — this one prompt shows what it can really do
• I asked ChatGPT, Gemini, Claude and Perplexity to rank the 10 jobs most likely to be replaced by AI — here's what they all agreed on
• Claude Fable 5.1 is here — this one prompt shows what it can really do

Pulling up AI assistants on your Apple and Android device entails using them primarily within their app homebases and not being able to do anything else while it’s working.

In one case, you can continue your ChatGPT conversations through the “Voice” feature while you switch between your apps and even lock your phone. From a multitasking standpoint, that feature works like a charm. Android users are now getting something similar with Google Gemini, but with a feature that lets you complete more complex tasks through your text prompts.

Before, the Gemini overlay on Android mobile devices commanded a large portion of the screen and didn’t allow for much multitasking since you couldn’t use any of the other apps until Gemini completed its tasks.

Now, Google is rolling out this new Gemini minimizing feature for Android users. Here’s how it works and how to use it.

Minimizing Gemini is now possible and multitasking is so much easier to accomplish

Android users no longer have to stare at a loading screen while Gemini tends to their complex requests.

Now you can tap the “Minimize” button while it responds to your prompts, while you jump to other apps, handle your emails, scroll through your social media feeds or simply look up anything through your web browser. The Minimize button sits right above the pill-shaped Gemini bar and now shows a message that pops up to let you know that you can complete other jobs while it’s working: “Gemini is still available while you multitask. Tap to expand. Drag to move or dismiss.” Android users can even tap the minimized Gemini bubble to reopen your chat, drag it to move it or swipe it away to close it.

Two users have shown off this new Gemini minimizing feature through posts on Telegram via this link and this other link. Now the Gemini app is being set up as a multitasking AI assistant that has evolved from a stationary pop-up tool to something more of a dynamic background module. This feature began rolling out on September 4.

Before this feature began rolling out, the Gemini mobile app on Android handled multi-step tasks for its users in specific apps through a beta feature called “screen automation.” As explained by the official Pixel Phone Help guide, this previously released Gemini multitasking shortcut has become available for the following Android devices: Pixel 10, Pixel 10 Pro, Pixel 10 Pro XL, Samsung Galaxy S26 Series, Z Flip 8 and Z Fold 8.

Final thoughts

Gemini’s minimized overlay that turns it into a bubble that multitasks while you work in other apps sounds like a lifesaver. I’d love to see this sort of feature become widely available for other AI tools such as ChatGPT, Claude and Perplexity across Apple and Android devices. I’ll have to revert to my Android mobile device-using friends to see this feature in action (I’m a loyal Apple iPhone user, after all) and use it to summarize long articles or conduct other experiments.

More from Tom’s Guide

• 7 surprisingly useful AI uses for retirees and empty nesters to make their lives easier
• Claude Fable 5.1 is here — this one prompt shows what it can really do
• Communities may soon be left in the dark about new local data centers under a proposed EPA rule change

AI data centers are becoming a hot topic in many communities across the country. Every time big tech launches a new, more capable model or advanced feature, the use cases increase the need for more compute power for AI tools and cloud services.

Now, a proposed change from the Environmental Protection Agency could make it harder for residents of proposed data center locations to find out about the projects before they are approved.

As reported by the Associated Press on Thursday, the proposal would remove a federal requirement for states to give the public notice and an opportunity to comment before issuing certain air pollution permits.

Although the change is not specific to data centers, it would apply to a category of facilities considered "minor" sources of air pollution under the Clean Air Act. These include businesses ranging from repair shops and laundromats to landfills and steel mills. It could also apply to data centers, making the proposal especially important as big tech races to secure locations to support AI growth.

What is the EPA proposing?

The EPA first proposed the rule in July, and it involves a part of the Clean Air Act called the New Source Review, or NSR, program. Right now, under federal regulations, minimum requirements are set to ensure the public is involved when states and local agencies handle these minor-source permits. According to the EPA's explanation of the permitting process, the public is given 30 days to submit their concerns or request a public hearing.

Although the EPA wants to eliminate that, it doesn't mean every state would stop notifying residents about proposed facilities. It just wouldn't be a requirement. The concern leans more toward states that don't have strong requirements already in place of their own.

Why does this matter for data centers?

Data centers need enormous amounts of power to keep thousands of servers running. Additionally, they have diesel generators that can provide backup power if there is a problem with the electric grid.

Those generators can release pollutants such as nitrogen oxides and carbon monoxide. Depending on the size of a project and its expected emissions, the generators can be covered by minor-source air permits.

Data centers have also become a much bigger political issue as AI companies expand their infrastructure.

Communities have raised concerns about their electricity and water use, noise and pollution. At the same time, supporters point to the investment and tax revenue they can bring to local communities.

The debate is especially important in places such as Virginia and Georgia, which have become major centers for data center construction.

The AP reports that environmental groups are concerned about states in the South and Midwest where local public-notice requirements may not go beyond what the federal government requires.

If the federal requirement disappears, residents in one state might continue receiving notices about proposed projects while people in another state could have fewer opportunities to learn about them or comment before a permit is approved.

Why does the EPA want to change the rule?

The EPA says the proposal is about reducing unnecessary delays rather than weakening environmental protections.

The agency argues that minor sources generally produce lower emissions than major sources and that the Clean Air Act itself does not require these federal public-notice and comment procedures for minor sources.

EPA Administrator Lee Zeldin said the change would cut “unnecessary and burdensome red tape” while giving more authority to state and local governments.

The EPA also says the proposal would not change emissions standards. Facilities would still have to meet applicable air-quality requirements.

An EPA spokesperson told the AP that describing the proposal as an attempt to hide data centers is a “false narrative.” The agency's position is that states should decide how their own public participation process works.

Critics see the situation differently

Mike Koerber, a former deputy director of the EPA's air quality office, told the AP that eliminating the federal requirement could create an “unlevel playing field” where residents in some states know about new projects while those elsewhere do not.

A coalition of nearly 200 environmental, health and community groups has also opposed the proposal.

Keri Powell, an attorney with the Southern Environmental Law Center, told the AP that communities should have an opportunity to weigh in before projects that could affect them are approved.

Data centers are becoming a political issue

The proposal comes as the Trump administration pushes for faster development of AI infrastructure in the United States.

President Donald Trump has argued that data centers are important to America's competition with China in artificial intelligence. He has also acknowledged the growing public resistance to them and has urged technology companies to generate their own electricity rather than driving up utility costs for other customers.

Final thoughts

According to a 2025 AP-NORC poll, about four in 10 American adults said they were extremely or very concerned about AI's effects on the environment. Americans were also more likely to believe AI would hurt rather than help the environment over the next decade.

Data centers are not the only facilities that would be affected by the EPA proposal, and eliminating the federal requirement would not automatically eliminate public input everywhere.

But the debate raises a bigger question as AI expands: How much should people get to know about — and have a say in — the infrastructure being built in their communities?

What do you think? Share your thoughts in the comments below.

More from Tom's Guide

• Humanoid robot fights back after man pushes it in store — is this the beginning of the uprising?
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• Snickers made a digital candy bar that claims to fix ChatGPT — I put it to the test

The one thing I’ve started to notice for the older folks in my family is how they’re still a bit wary of AI.

Some of them refer to AI as “that ChatGPT thing,” just like I remember them referring to video games as just “Nintendo.” It’s still a foreign concept for the sort of boomers who have entered their retirement age, especially for those who no longer have access to their tech-savvy children in the next room since they’ve finally gotten a place of their own. But I have noticed some people in their 60s and 70s whip out their phones to type out simple prompts and talk to the chatbots they have at their disposal.

If you consider yourself a part of the boomer generation and are looking for ways that AI can assist you in your everyday life, there is a wealth of beneficial uses that come from utilizing the likes of ChatGPT, Gemini and Microsoft Copilot.

Here are seven of those serviceable methods and a few examples of the sort of prompts that apply to each of them.

1. Get a better understanding of technology-related issues

I can’t even fathom the number of times my aunts, uncles and grandparents have lit up my phone with texts asking for solutions to their tech problems. Setting up their new phone, getting to the bottom of their Wi-FI disconnection errors, trying to connect their new smart TV to the Wi-Fi, and trying to find out how to use a streaming service on their smart TV are among those common problems.

Asking AI to assist you with those sorts of lingering tech issues can be done using the following example prompts:

• Explain how to set up my new iPhone [model name and number] step by step. Assume I’m not very comfortable with technology and don’t skip any steps.
• My Wi-Fi keeps disconnecting. Walk me through the most likely causes and tell me exactly what to try, one step at a time.
• Explain how to connect my smart TV to Wi-Fi like you’re helping someone who has never done it before.
• Explain how to stream [name of streaming service] on my smart TV. Tell me what buttons to press and what I should see on the screen at each step.
• I just bought a new Android [model name and number] phone. Give me a simple checklist for transferring my contacts, photos, apps, and messages from my old phone.
• I keep running out of storage on my phone. Show me how to figure out what's taking up space and safely free some of it.

2. Tap into a chatbot as a research assistant that can easily explain complex topics

For those who are in their 60s and older, terms such as “Medicare” start to become more central to your everyday life. And when you’re hoping to gain a bit of crucial information on a trending topic in the tech industry (you gotta keep up with the younger generation and stay in the know!), get an explanation of a financial document you’ve attached to your chosen chatbot and need some advice before you make a major decision, AI can help out in all those cases.

The following prompts are just a few examples of how you can turn your chatbot into a digital research assistant:

• Explain Medicare to me like I'm a complete beginner. Start with the basics and gradually introduce more complicated concepts.
• I keep hearing people talk about [technology]. Explain what it is, why people care about it, and whether it has any practical use for someone like me.
• Explain this financial document to me in plain English. Highlight anything I should ask a qualified financial professional about. (Make sure you attach the financial document you want more clarity about)
• I need to make a decision about [explain your situation]. Give me a balanced summary of the strongest arguments for and against each option.
• I'm comparing these two health insurance plans. Explain the major differences in plain English and give me a list of questions I should ask before choosing one. (Be sure to include links or document attachments for both plans alongside this prompt)

3. Turn vacation planning into a simpler affair

I’m sure there’s a bunch of retirees who want to live a little and do some domestic and international exploring at their age. AI can play the role of your digital vacation planner with ease—ChatGPT even features a wealth of plugins that you can install through the desktop/mobile app itself to make restaurant reservations, plan multi-day excursions, book flights & hotels, find the perfect cruise getaways, etc.

Simply open the sidebar to get access to the “Plugins” menu to see all the “Travel” apps available to you. Then type directly to any of them by @’ing them and mentioning them by name.

These starter prompts should give you a good idea of what you should be asking of your preferred vacation planning chatbot when you need some extra assistance:

• Plan a [number]-day vacation to [destination] for me. I prefer a relaxed pace, don't want to feel rushed, and want enough downtime each day.
• I'm visiting [destination] for [number] days. Create an itinerary focused on history, great food, and interesting sights, but limit me to no more than three major activities per day.
• I'm traveling to [destination] and don't know the local customs. Give me a simple guide to tipping, public transportation, dining etiquette, and common cultural mistakes tourists should avoid.
• I'm taking a long flight to [destination]. Create a plan for what I should do before, during, and after the flight to make the trip less stressful.
• Act as my travel-planning assistant. Before recommending anything, ask me five questions about my budget, interests, travel style, food preferences and pace. Then build my itinerary based on my answers.

4. Build fitness and wellness routines

Staying as physically active as possible in the later years of your life is possible—I can take one look around my neighborhood and be greeted by the inspiring sight of older folks powerwalking, lightly jogging or performing simple stretching exercises in the park. AI can aid you in that regard once you give it a clear set of directions aimed at outlining the perfect exercise routine that’s meant to rejuvenate you and get you some much-needed fresh air.

These are the sorts of prompts you’ll want to present to your digital workout instructor to get you more active:

• I’m a [age] who wants to take better care of myself without completely changing my lifestyle. Help me create a simple daily wellness routine that includes movement, healthy meals, relaxation, sleep and time for things I enjoy. Keep it realistic and sustainable rather than intense.
• I don't enjoy traditional workouts. Give me [number] ways to build more movement into my normal day through activities like walking, gardening, household projects, hobbies, and outings. Prioritize activities that are enjoyable enough that I’ll actually keep doing them.
• I enjoy [list of hobbies]. Create a wellness plan that uses my hobbies to help me stay physically active, mentally engaged, and socially connected. I want wellness to feel like something I enjoy, not another chore.
• Help me create a 30-minute morning routine designed for someone in their 60s or 70s who wants to start the day feeling energized and organized. Include gentle movement, hydration, breakfast, planning, and something enjoyable. Don't make it feel like a productivity challenge.

5. Learn new skills and turn them into your latest hobby

There’s no age limit when anyone’s interested in picking up a new hobby, especially when it comes with learning something new in the process. Using AI to learn the basics of whatever you may be interested in, asking follow-up questions about said topic and doing some outside research on your newly acquired skill-turned-hobby is definitely worth doing, even at an older age.

Here are a few examples of the prompts you can use to pave the way to your next skill-building session:

• Teach me the basics of photography. Assume I'm a complete beginner and create a four-week learning plan with one small lesson each day.
• I want to learn [name of language]. Create a 15-minute-a-day beginner program that focuses on conversations I'm likely to have while traveling.
• Teach me how to play chess. Start at the absolute beginner level and give me exercises after each lesson.
• I want to learn gardening. Ask me questions about my yard, climate, sunlight and available time, then create a beginner's learning plan.
• I've always wanted to learn woodworking. Create a beginner's curriculum that starts with safety and basic tools before moving into simple projects.

6. Use it to give you an another opinion before making your next big purchase

I’ve definitely had those moments where the older members of my family call me to ask if purchasing a new TV, smartphone or any other gadget is worth it. I provide all the tech savvy I can during those conversations, but now I make sure to also tell them to refer to AI to ask those same questions for an extra opinion. These sorts of prompts can push you in the right direction whenever you need some more consideration about what you’re set to buy next:

• I'm looking for a new TV. My budget is [cash value]. I sit about [number] feet away and mostly watch [types of content. Tell me which specifications actually matter to me.
• I'm buying a new smartphone. I care most about battery life, camera quality, and ease of use. Help me determine which features I should prioritize.
• I'm replacing my [type of gadget]. Give me a list of features worth paying extra for and features that probably aren't worth the additional cost for someone with basic needs.
• I'm overwhelmed by all the technical specifications for [product]. Explain which five specifications matter most for my use case and why.

7. Turn it into your personal scam detector

ChatGPT users will be happy to know that it features plugins built specifically to help you figure out if a URL, phone number, text message or email is trustworthy or not. The two plugins that I’m alluding to are Malwarebytes and McAfee. Beginning your prompt by @’ing either of those installed plugins, using any of the following prompts, then copying & pasting any of the aforementioned things that might be a scam should make you more aware of what you're dealing with:

• Is this link safe to click?
• Is the DM I just shared with you from a scammer?
• Analyze this email for potential scam warning signs. Explain every red flag you find.
• I received this text message. What tactics, if any, does it use to create urgency or pressure me into acting?
• Someone claiming to be from my bank sent me this message. What questions should I ask the bank through an official channel before doing anything?

Bottom line

I know it may be hard for some to grasp the concept of using AI to make one’s life easier in some respects and more fulfilling in others. But it can totally be done—the likes of ChatGPT, Gemini and Microsoft Copilot aren’t just great for professionals; they’re also supportive tools for retirees and empty nesters who need help for a wide range of tasks. Here’s hoping this guide can help you or the older folks you know discover the best ways to include AI tools in their lives to keep them safe from scams, help them build new skills and more.

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Claude Fable 5.1 arrived this week and it's Anthropic’s latest high-end model, built for complex tasks that require sustained reasoning. Its biggest focus is agentic work, meaning it can plan, use tools, check its own progress and keep working through problems with less supervision.

With a 1-million-token context window, it's useful for huge codebases, lengthy documents and research-heavy projects. Anthropic says it delivers major gains in coding and long-running tasks while reducing the cost of some agentic workloads through cheaper caching. The simplest way to think about Fable 5.1 is that it’s designed to be given a project, not just a prompt.

For those new to Claude who want to dive directly into Fable 5.1, here's the one prompt I suggest you try first.

Give Fable 5.1 a project

Fable 5.1 can handle more, which means you'll want to give it a sturdier and more meaningful prompt.

Here's a good prompt to see what Fable 5.1 can do: I'm building [describe a real project you're actually working on, in detail]. Here's my current approach: [paste your code, outline, or plan]. Tell me what's wrong with my thinking, what I'm missing, and then refactor or redesign the whole thing — but explain your reasoning at each decision point so I can learn from it.

While this prompt may seem deceptively simple, it makes sense for an AI that can do so much more than previous models. I especially like it because you're not starting with a blank slate. Instead, you're giving the AI something of yours that you've already started. That's always a recipe for a better and more thorough response.

Instead of asking Claude to create something from a clean set of instructions, you're handing it work that already exists, complete with your assumptions, mistakes and potentially questionable decisions. From there, Fable 5.1 has to figure out what you're trying to accomplish before deciding whether the way you're doing it actually makes sense.

And crucially, you're explicitly giving Claude permission to tell you that you're wrong. One of the least useful things an AI assistant can do is take a bad premise and enthusiastically help you execute it. This prompt asks Fable 5.1 to interrogate the premise first. Only then does it get to rebuild the project.

What the prompt is really testing

There are several jobs hidden inside this prompt. First, Claude needs to understand the project and the approach you've already taken. Then it has to identify weaknesses that you may not have noticed yourself.

After that comes the harder part of deciding which problems actually matter and where the AI should begin.

A model could easily nitpick everything it sees and produce a huge list of suggestions without making the project meaningfully better. A useful response requires judgment about which decisions should stay, which should change and what those changes will affect elsewhere.

Finally, Claude has to redesign the work while keeping track of those decisions.

That's why I particularly like the final instruction to explain your reasoning at each decision point so I can learn from it.

With this prompt, you get to see what Claude knows and why it chose one path over another. There is an important caveat here. AI models don't provide a literal transcript of their private internal reasoning, and you shouldn't treat an explanation as a window into exactly what happened inside the model. What Claude can provide is a useful explanation or justification for the decisions it made

What should you give Fable 5.1?

If you're a developer, you could paste in code for something you've been building and explain what you're trying to accomplish. But you don't have to write code.

You could give Claude a business plan you've been struggling with, the outline for a novel that isn't quite working, a research project, a presentation, a home renovation plan or almost anything else where you've already made decisions and aren't sure they're the right ones.

In fact, I'd argue that the messier the project is, the more useful the test becomes.

A perfectly written brief gives the model a relatively easy job. Real projects aren't like that. They contain assumptions we haven't explained, ideas we've become attached to and decisions that made sense three weeks ago but don't anymore.

That's exactly what I want Fable 5.1 to find. When I put it to the test, I uploaded my entire manuscript for a book I'm working on. Then, I used this prompt without giving it any additional hints about what I thought was wrong with my work. Of course, that was the intentional part.

If I tell Claude where I think the problems are or what needs edits, I'm already steering the critique. I wanted to see whether Fable 5.1 would independently notice the same weaknesses — and, more importantly, whether it would find anything I had missed.

What surprised me

I was surprised by how thorough Fable 5.1 was with its feedback and line edits. It offered suggestions without being overly editorial or trying to remove my voice at all.

One of my favorite things about Claude is that it doesn't just go ahead with edits the way ChatGPT or Gemini often will do. Claude questioned my assumptions, offered to change the structure for clarity and even found a problem with one of the chapters that I hadn't noticed.

From there, I let it outline what I would need to improve my manuscript and what other projects I could potentially develop from it.

But finding problems is only half the test. The second part of my prompt asks Fable 5.1 to "refactor or redesign the whole thing," which means it now has to turn its criticism into something better.

Because this was a manuscript and not a presentation, I didn't want to give it the reins in that aspect. Instead, I asked it to make a list instead of going in with all the changes. More importantly, Fable 5.1 explained why it suggested those changes.

Of course, I didn't agree with all of the changes, but that's what I like about using AI as a partner and not something that does the entire job for me.

Bottom line

If you're ready to ask AI for something beyond your typical query, Fable 5.1 is a great place to start. This is a great prompt — just be sure you don't waste your usage limits on a fake project. I mean, if you're going to try it, try it with something you're actually working on.

The reason Claude's prompt works is because you already know the material you're giving it. That puts you in a much better position to judge whether Fable 5.1's criticism is insightful or merely sounds convincing.

Take something you've genuinely been working on and give Claude enough context to understand both the project and what you're trying to achieve. Then let it disagree with you. This prompt asks Fable 5.1 to look at an answer we've already come up with and tell us why it might be wrong.

Give it a try and let me know in the comments what you think of Anthropic's latest model.

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I was pleasantly surprised when I booted up my PS5 and went to the streaming apps tab to find something entirely new called “Live TV on PS5.” At no extra charge, that feature lets me watch a vast collection of movies, TV shows, anime, and gaming-related content (sitting through some mandatory ads and keeping tabs on what’s coming on when are just two minor annoyances I have to deal with here).

After sitting through a few episodes of Death Note and Hunter x Hunter, my brain immediately went to “I gotta find some other free ways to enjoy all the stuff I like to watch, read, and play.” With that money-saving thought in mind, I cooked up this prompt and input it into ChatGPT and Gemini to help me out:

“Recommend 7 of the best free things I can do online based on my hobbies and interests. My hobbies and interests include video games, anime, professional wrestling, comic books, music, and movies.”

Both chatbots recognized my desire to enjoy the more cost-effective parts of my hobbies and interests, so they listed a bunch of alternatives to the paid ones that hit my checking account every month. I took four suggestions from ChatGPT, three recommendations from Gemini, and ended up enjoying all of them.

ChatGPT’s recommended picks

Here are the four best alternative options that ChatGPT provided me with:

• Build your own retro gaming museum with the Internet Archive: This is probably the biggest rabbit hole on the list. The Internet Archive has an enormous collection of digitized software, games, movies, music, books, and other media. Explore old computer games, check out classic gaming magazines, dig through forgotten game soundtracks, explore vintage gaming commercials & TV recordings, and just browse through old gaming history.
• Read manga for free on MANGA Plus: This is the official Shueisha manga service, and its free offerings include popular series such as One Piece, Chainsaw Man, Boruto, Jujutsu Kaisen, Dandadan, and others. Depending on the title, you can read the first and newest chapters for free, while the app also offers a "First Read Free" system for eligible ongoing series.
• Turn your movie obsession into a giant free movie scavenger hunt: Free, ad-supported streaming services have become surprisingly useful for movie fans. Tubi, Pluto TV, and similar services offer legitimate free movies and TV without requiring a paid subscription.
• Make a free "comic book vacation" with digital libraries: If your local library participates, Hoopla can be a fantastic way to read comics, graphic novels, and manga digitally using a library card.

Imagine my surprise when I did some digging in the Internet Archive and was greeted by a smorgasbord of classic arcade games I didn’t know I could play again and digital versions of GamePro I used to read as a wee lad. I spent plenty of time playing the likes of WWF WrestleFest, Astro Blaster, Bloody Roar 2, and other classic games once I got the hang of their controls (this guide definitely did the trick).

To fulfill my desire to read a bunch of manga and comic books for free, I did a deep dive into MANGA Plus and Hoopla—I got to read a few chapters of Sakamoto Days for free and found a nice selection of graphic novels to read once I input the required information for my local participating library to access them.

And thankfully, I found plenty of cult classic films to watch on Tubi—Jim Henson’s Labyrinth, The Last Unicorn, Tank Girl, and Masters of the Universe definitely kept me entertained for a few hours. Having to deal with some commercial breaks to enjoy all that free cinema doesn’t bother me at all.

Gemini’s suggested picks

And here are the three strongest alternative options Gemini gave me:

• Stream Legal Anime on Tubi and Pluto TV: While Crunchyroll requires a paid subscription for many ad-free catalog titles, legal, free, ad-supported platforms like Tubi TV and Pluto TV offer massive anime libraries (both classic titles like Yu Yu Hakusho and Inuyasha and modern series) with no sign-up required.
• Read Golden and Silver Age Comics via Comic Book Plus: Comic Book Plus is the web's largest legal archive of public-domain comic books. You can read thousands of original Golden Age and Silver Age titles, early superhero runs, sci-fi serials, and classic horror anthologies straight through their online viewer.
• Dive Into Webcomics on WEBTOON & Tapas: WEBTOON and Tapas offer tens of thousands of free digital comics across action, fantasy, and superhero genres—many of which feature anime-inspired art styles and have gone on to get official anime adaptations (like Tower of God and Solo Leveling).

Paying for Crunchyroll has become a thing for me because I need my weekly fix of new anime series making their debuts and dropping new episodes. But Gemini’s suggestion of checking out Tubi and Pluto TV’s anime archives gave me the pleasure of tapping back into my nostalgia with marathon viewing sessions of Yu-Gi-Oh!, Sonic X, Sailor Moon, and Monster Rancher.

Comic Book Plus offers an easy (and most importantly, free) way to access superhero comic books from before my time, such as Blue Beetle, Captain Marvel, and Moon Girl. WEBTOON surprised me when I came across its Disney-themed offerings, which included a wealth of quality Marvel Comics series runs, plus digital graphic novels connected to the Alien and Predator franchises.

As for Tapas, its readable content lineup didn’t really appeal to me as much as WEBTOON’s did. But I’m sure some of you reading this right now may find something on there to enjoy (it has a pretty robust selection of romance-themed comics, if any of you are into those).

The takeaway

My hobbies are definitely costly—I’m sure I’d be shocked at how much I spend on video games, streaming services, and comic books on a monthly basis. While I’ll never completely abandon the paid options that let me enjoy the latest and greatest pieces of entertainment that fuel my interests, I’ll be sure to make better use of all the free sites and streaming services that do just as much to keep me entertained.

The Internet Archive, Tubi, Pluto TV, Manga Plus, Hoopla, Comic Book Plus, and WEBTOON have a wealth of content for me to peruse without worrying about spending any extra money. Thanks for putting me onto all those freebies, ChatGPT and Gemini.

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Google is testing an “Ask Google from anywhere” experience in Chrome Canary for Windows that can bring up a floating search box even when you are working in another app. Press Alt + Space, and you can ask Google a question without first opening Chrome or switching back to a browser window.

Sound familiar? Google already offers a similar experience through its standalone Google app for Windows, which uses the same Alt + Space shortcut to summon a floating launcher with Search, AI Mode and Google Lens capabilities. Now it appears to be experimenting with bringing that idea directly into Chrome itself.

There is an important caveat: Google has not said the two are connected, and the Chrome version remains a Canary-level experiment rather than a feature rolling out to everyone. But it offers a revealing look at where Google could be taking Chrome next.

What 'Ask Google from anywhere' actually does

Known in development as the “Everywhere Omnibox” under Project Loom, the experiment gives Chrome a floating search interface that can appear on top of whatever else you happen to be doing on your computer.

Instead of opening a Chrome window or new tab to start a search, users can press Alt + Space to bring up the floating bar while working in another app. The shortcut can also be changed through Chrome's settings.

The latest version makes Google's plans for the feature a little clearer. The interface now uses the language “Ask Google from anywhere” and tells users they can share part or all of their screen and ask Google about what they are looking at.

That could eventually make Google Lens and AI-powered search available without forcing you to leave whatever app you are using. However, those pieces aren't all working in the interface yet. Lens and AI Mode buttons aren't currently visible in the bar, making this very much a work in progress.

Having déjà vu?

This idea isn't new. The standalone Google app for Windows already lets users press Alt + Space to bring up Google without first opening a browser.

That app combines traditional Search with AI Mode and Google Lens and can search local files, installed apps, and Google Drive. It can also use Lens to ask questions about something on your screen.

The similarities make Chrome's experiment more interesting. Both give Google a way to appear on top of whatever you are doing in Windows, both use Alt + Space, and both aim to reduce the need to stop what you're doing and head back to a traditional Google search page.

Google has not said that Project Loom is intended to replace its Windows app or that the two projects are directly connected, so it is too early to know how they might fit together.

Still, putting a similar experience inside Chrome would mean people who already have the browser running wouldn't necessarily need a separate Google app to summon Search from elsewhere on their computer.

Bottom line: Chrome is starting to escape the browser

Chrome has traditionally waited for you to open the browser before you can use it. Search in Chrome reverses that relationship by letting Chrome come to you, even while you're working somewhere else.

It also fits with Google's broader push to bring AI features closer to whatever users are already doing rather than making them continually jump between webpages, apps and AI tools.

Whether Google ultimately ships “Ask Google from anywhere” in this form is another question. The feature is still being tested in Canary, and Google could change it significantly or abandon parts of it before it ever reaches the stable version of Chrome.

That said, it's clear that Google wants Search, Lens and eventually its AI tools to be available without making you stop what you're doing and head back to a browser tab.

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As a person who writes about AI for a living, the irony of me being worried about AI taking my job is not lost on me.

I’ve been keeping track of the statistics tied to that worrying trend of humans losing their jobs to AI, which is why I’ve morphed into a realist who realizes my career is in danger of being overtaken by chatbots (seeing certain sites dole out articles with hints pointing at them being written by AI is disheartening). According to sociologist and AI researcher Jeffrey C. Dixon, a YouGov survey he conducted with 1,250 US workers between July 30 and August 4 of 2026 found that only 3% said they had lost a job to AI since 2023.

While that number is a bit reassuring that the job market isn’t in too much danger currently due to AI, these two sobering stats from Tenet are cause for concern: 92 million jobs may be replaced globally by 2030 due to AI and other labor shifts, plus 47% of US workers are at risk of automation over the next decade.

With all that in mind, I approached four chatbots with a question: “Rank the 10 jobs most likely to be replaced by AI next.” I was shocked to see them all pick one role in particular.

The one job all four chatbots agreed on

After asking ChatGPT, Gemini, Claude and Perplexity the same question, I first took note of the one job that each chatbot listed among its 10 chosen roles that no other chatbot selected.

ChatGPT only mentioned the role of a graphic designer; Gemini only brought up the role of basic market research & financial data analyst; Claude only included broadcast announcers and radio DJs among its picks (I hope that never happens!); Perplexity only selected file clerks & records-management assistants.

As for which job they all agreed on as the one that is most susceptible to AI taking it from humans, it was a role that I’d rather not see filled by nothing but bots over the phone:

• ChatGPT, Gemini, Claude and Perplexity: Customer service representative, Tier-1 customer service representative, customer service representatives and basic customer service representatives.

Perplexity offered the best explanation as to why AI is capable of replacing humans for that position and compressing the responsibilities attached to it: Chatbots and voice agents can answer routine FAQs, check order status, reset accounts, schedule appointments, process simple returns, and triage tickets around the clock.

While that may be true, I’d much rather deal with a human who fulfills such a role. Chase Bank’s most recent commercial, which makes a promise to rely on old-fashioned humans to handle customer service inquiries in the age of AI, showcases the sort of reality I’d prefer to live in.

The other roles that popped up the most among each chatbot

Besides the one role that every chatbot put on its list, a few of them also agreed on the same job that another chatbot didn’t mention at all:

• ChatGPT, Gemini and Perplexity: Data-entry clerk, data entry clerks & digitization specialists and data-entry keyers & document-processing clerks.
• ChatGPT and Gemini: Telemarketer and basic telemarketers & inbound sales representatives.
• ChatGPT, Gemini and Perplexity: Bookkeeping/accounting clerk, routine bookkeepers & accounts payable clerks and bookkeeping, payroll, & accounts-payable clerks.
• ChatGPT, Claude and Perplexity: Copywriter/content writer, writers & authors and entry-level content writers for routine copy.
• ChatGPT, Gemini and Perplexity: Paralegal/legal assistant, paralegals & legal researchers and legal secretaries & routine paralegal support.
• ChatGPT and Gemini: Junior software developer, entry-level/junior software developers.
• Gemini and Claude: Translators & localization clerks and interpreters & translators.

At the top of each chatbot’s ranked list, ChatGPT chose customer service representatives, Gemini selected data entry clerks & digitization specialists, Claude picked interpreters & translators and Perplexity settled on data-entry keyers & document-processing clerks.

Final thoughts

I knew the role of writers would pop up on any of the chatbots’ lists for jobs most in danger of being filled by AI and leaving humans behind.

But as someone who’s doing his best to learn about the ins and outs of AI, I’m taking the initiative to acquire an extra skill set that may assist me in the future. As for doctors, dentists, plumbers, electricians, etc., I just can’t envision humanoid robots getting strong and smart enough to completely take over those positions. It’s still alarming to see the jobs ChatGPT, Gemini, Claude and Perplexity brought up on their lists—here’s hoping human ingenuity becomes more appreciated during an age where AI is injected into so many facets of our lives.

Gemini’s closing statement in response to my request summed up my outlook on it and the other chatbots’ picks quite well:

The common factor across all these roles is predictability. Roles reliant on structured rules, data retrieval, standard text generation, or routine transactions are being automated. Conversely, jobs requiring physical dexterity, complex emotional intelligence, high-stakes strategic accountability, or manual trade skills (such as healthcare providers, electricians, plumbers, and senior strategists) remain far more resilient.

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As a self-confessed coffee snob and director of Tom's Guide's The Coffee Lab, I'm always testing out new espresso products. At IFA 2026, I tried nunc., an AI-assisted espresso machine. Yes, an AI espresso machine.

So what does the AI in nunc. actually do? Instead of having to manually dial in your beans, nunc. uses an NFC code to analyze pre-packaged, nunc.-branded beans (you can also use your own beans). Then, the machine analyzes humidity, heat, bean size, and basically every other variable to grind to the perfect particle size. As someone who loves espresso but hates dialing in (why does it take so long sometimes?), I was excited to try this out. But as someone skeptical of AI at best, I had my reservations.

I didn't want nunc. to take away the art of making coffee. That's so human and personalized that it's impossible for AI to copy. Luckily, though, nunc. proved me wrong. Here's what happened when I tried it.

How does nunc. work?

As I mentioned above, every nunc.-branded bean hopper has an NFC code, exactly like a Nespresso Vertuo pod. The machine reads this NFC code to analyze the roast date, roast type, bean type, and processing type, and work out precisely how to grind those specific beans. Then, it analyzes the environment — heat, humidity — to finalize the optimal grind.

This means the grind size will change from morning to evening, or even hour to hour. If you have an espresso at 6 a.m., when the air in your house is dewy and humid, the grind size will be different from your 1 p.m. espresso, sun shining overhead, A/C running.

Of course, if you have the companion app, you can input information about any beans.

How is nunc. different from a normal espresso machine?

In terms of functionality, nunc. works just like any other espresso machine. Think about it like this: it's almost like a superautomatic — Jura, De'Longhi Rivelia — but a totally manual machine. All it does for you is choose the ideal grind size. Honestly, dialling in beans is the worst part of espresso making for me, so I'm completely on board.

You tamp, insert the portafilter into the grouphead, and can pre-infuse the beans yourself. You can either steam the milk automatically (like the Breville Bambino Plus), or do it manually (any other manual espresso machine).

You dispose of the spent grounds yourself; you empty the drip tray yourself. The only part that is "AI" is the grinder.

How does nunc.'s "AI" coffee taste?

nunc. doesn't make "different" coffee. You won't have one sip and go, "Woah, I can totally taste the AI, dude!" It honestly tastes like a human barista was there every step of the way... because there was. You make the coffee.

Here's a shot of my oat flat white.

It looks like a normal coffee. The taste was clean, polished, with a soft, dark-chocolate-like bitterness rounding it out. I wanted a little more fruit, acid, and funk — I like a funky coffee — but this was likely because I didn't choose my beans.

The milk texture was a little too bubbly for me; I like mine more velvety. Like any other espresso machine, though, you can adjust milk texture easily. Just don't aerate it as much.

I expected to dislike it because I'm extremely particular about my coffee, but this went down a treat.

Where can I get nunc.?

So, now's the time for the bad news. As I'm writing this, nunc. is only available in Germany. If you happen to be in Germany, nunc. costs €2,699. For an extra €149, you get a grinder, the machine, a spring-loaded tamper, a milk jug, a brush, and a tamping mat.

That price equates to around $3,135, which makes this one of the most expensive home espresso machines I've ever seen. There's the $3,000 Breville Dual Boiler, but the nunc. out-prices many of the prosumer models like the Lelit Bianca ($2,999) and Fellow Espresso Series 1 ($1,499).

nunc.'s representative informed me there is no release date for the U.S., U.K., E.U., Canada, Australia — basically any non-German markets. Hopefully, it won't be five years before we're seeing nunc. in our kitchens. I would love to play around with this machine myself.

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This year has seen an uptick in popularity for smart glasses—according to IDC, the global smart glasses market has grown year over year in Q1 2026 by 167%, reaching approximately 2.25 million units shipped in a single quarter.

That stat comes as no surprise, thanks to the growing popularity of certain models of smart glasses, such as the Ray-Ban Meta (Gen 2), Meta Oakley HSTN, Rokid AI Glasses, and the many, many more options.But with that surge in purchases and recognizability comes several cases of their video-filming feature being used to violate someone’s privacy.

A story from Ars Technica has made the rounds regarding smart glasses being used to secretly film people in bathrooms, record someone changing in/out of their clothes and capture footage of a couple’s most intimate moments. Futurism even reported that young boys are getting their hands on smart glasses and using them to harass & bully the young girls in their middle & high schools. Public perception of smart glasses has reached an all-time low, especially with Meta trying to wipe away the title of “pervert glasses” for its product by instituting safer privacy settings.

Even so, people are looking for ways to avoid being filmed by people with smart glasses. And they’re finding the sort of methods that aren’t costly at all. Here’s a list of the apps and gadgets that people are using to be aware of smart glasses in their vicinity and protect themselves from being filmed by them.

The apps and gadgets that make users aware of smart glasses in their presence

There are four apps I came across on the App Store: Antizuck Smart Glasses Scanner, Nearby Glasses (Original), Zuckoff and NoGlasshole: Glasses Detector. The Nearby Glasses app is also available on Android devices.

All of them have one thing in common: they’re used to make users cognizant of the presence of smart glasses in their vicinity by scanning for the Bluetooth signals they give off when powered on. Plus, these apps let users know when a recording-capable device is nearby. Smart glasses aren’t just detected by their Bluetooth activity—they can also be detected through their Wi-Fi signal and easily visible LED indicator lights on the front frame that blink or glow when the camera is recording video or taking pictures. It’s worth noting that some smart glasses modifiers are finding ways to make them harder to spot (such as disabling their LED indicators).

The Zuckoff app is a prime example of an app that makes the practice of steering clear of people using smart glasses to film you without consent so much easier. “Camera glasses announce themselves over Bluetooth,” the app’s official site explains. “Zuckoff listens for those announcements and tells you when Ray-Ban Meta, Oakley Meta, Snap Spectacles or similar hardware turns up nearby. It also logs every other Bluetooth device it hears along the way. No account, no server, no analytics.

The app’s site also offered an explainer as to what the app can’t do, however: “Glasses advertise loudest while powering on, pairing or leaving the case. Once paired to their owner's phone they can go quiet, so silence is not proof that nobody is recording, and a detection is not proof that anyone is. Signal strength gives a rough distance and no direction at all.”

There are also relatively inexpensive counter-surveillance tools sold on Amazon that people can use to detect smart glasses. Those gadgets include RF Signal Detectors and Optical Lens Finders. RF Signal Detectors measure radio frequency bursts when smart glasses stream audio or video over Wi-Fi or Bluetooth, but only trigger when smart glasses are actively transmitting data, not while they’re offline or idle. It’s worth noting that a Bluetooth scan only reveals that smart glasses are powered on and in your area—it cannot confirm whether the camera is actively recording, but at least you’ll know one’s nearby.

As for Optical Lens Finders, these devices emit flashing red LEDs—the reflection off the tiny smart glasses’ camera lens in the frame shines back through a viewfinder. Keep in mind that they require a manual line-of-sight visual sweep by the user. This guide on how to tell if someone is wearing smart glasses also includes a bunch of telltale signs that will make you more likely to spot them in public.

The takeaway

Smart glasses certainly have beneficial uses, such as listening to hands-free media, relying on AI-powered voice assistants to handle everyday tasks, utilizing augmented reality displays for walking/cycling directions and using them as virtual monitors to watch movies in the privacy of your own home. Their filming and photo-taking capabilities are also impressive, but judging by the privacy-breaching ways they’re used nowadays, those features are untrustworthy for many.

With apps and gadgets being relied upon to go on the hunt for smart glasses, people are finding unique ways to stay out of their camera frame and keep their privacy intact.

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OpenAI launched ChatGPT-6 Astra Thursday and it has already proven to be dramatically better at coding, computer use, research and other complex tasks, while OpenAI President Greg Brockman has even suggested its arrival could mark the beginning of the AGI era.

But when a new model arrives, particularly of this caliber, one question is on the minds of many: What am I actually supposed to do with it?

Sure, you could use it just as you have used other ChatGPT models to write an email, plan dinner or explain something you don't understand. It will almost certainly do those things very well. But you'd also be using one of OpenAI's most capable models to do essentially the same jobs you were giving ChatGPT yesterday.

Astra is built for something more ambitious. Instead of answering one question and waiting for the next, it can take on longer, more complicated jobs, work through multiple steps and keep going as it gets closer to the result you asked for.

So if you want to find out what has actually changed, I think there's a much better way to begin. And you only need one prompt to get started.

What is GPT-6 Astra?

GPT-6 Astra is OpenAI's latest frontier model and the successor to GPT-5.6 Sol. As you'd expect from a new generation of GPT, it performs better across many of the benchmarks OpenAI uses to measure reasoning, coding and other capabilities.

Astra has been designed to handle much longer jobs that can involve planning, research, computer use and repeated attempts to get something right. It can navigate websites and software, keep track of what it is trying to accomplish and continue working through a problem rather than handing every step back to you.

That's a pretty big change in how you might use ChatGPT. Previous versions were primarily something you worked with. Astra is something you can give work to.

Who can use GPT-6 Astra?

Before you start looking for it in your model picker, know that OpenAI isn't giving everyone Astra at once.

The rollout begins with select enterprise customers before expanding to ChatGPT Plus, Pro and Business subscribers. If you don't see Astra in ChatGPT yet, that doesn't necessarily mean your account won't get it; access is being rolled out gradually.

OpenAI has not yet confirmed when, or whether, Astra will become available to people using ChatGPT's free tier.

That means many of us may have a little time before using Astra, but when it does, appear, however, I wouldn't start by throwing your usual ChatGPT prompts at it.

Instead, I'd give it a job.

What can GPT-6 Astra actually do?

One of the biggest differences with Astra is how long it can stay on a task. That's important because a lot of the things we'd actually like AI to take off our plates don't fit neatly into a single prompt and response.

Planning a vacation, for example, isn't just asking for a list of hotels. You need to decide where to stay, compare prices, work around everyone's schedule, figure out transportation, research what you want to do and somehow make all of those decisions fit within a budget.

The same is true if you're researching a major purchase, organizing a home project, digging through dozens of documents or trying to turn an idea into something finished.

Which brings me to the first prompt I'd try.

The one prompt I'd give GPT-6 Astra first

Rather than creating a prompt for one particular task, I wanted something I could reuse whenever I had a goal that involved more work than I wanted to do myself.

Here's the prompt I came up with for GPT-6 Astra:

I have a goal I've been putting off: [DESCRIBE YOUR GOAL].

Your job is to help me achieve the goal, not simply give me advice about it.

First, determine what you think I am actually trying to accomplish. Define what a successful outcome would look like and identify any assumptions you are making. If there is a better way to achieve the underlying goal than the approach I suggested, tell me and use the better approach unless it requires a decision only I can make.

Before beginning, identify what information, tools and actions are available to you. Ask me only for information you genuinely cannot obtain or reasonably infer yourself.

Then make a plan and begin carrying it out.

As you work:

• Keep track of what has been completed and what remains.

• Decide what to do next based on the results of previous actions rather than blindly following your original plan.

• Check important work before relying on it.

• If an approach fails, determine why, change your strategy and try again when reasonable.

• Look for problems, missing information or opportunities I may not have considered.

• Make routine, reversible decisions yourself. Ask me before actions that are consequential, irreversible, expensive, sensitive or require my personal judgment.

• Use new information you discover to update your understanding of the goal and your plan.

• Do not treat producing an answer as completion. The task is complete only when the defined success criteria have been met or you've reached something you genuinely cannot do without me.

When you need me, explain exactly what is blocking progress and ask for the smallest decision, permission or piece of information necessary to continue.

When the goal is complete, give me a concise report showing what you accomplished, what you changed from the original plan and why, important decisions you made, anything you could not complete and exactly what remains for me to do.

To use this prompt for yourself, you only need to change is the first line.

You could tell Astra you want to plan a family vacation, find a new laptop, organize a birthday party, research a home renovation or finally tackle a project you've been putting off for six months. The point isn't really the task. It's what happens next.

Why I think this is the best first prompt for Astra

Most prompts test the answer an AI gives you. This one tests what the AI does between your request and that answer. In other words, it tests exactly what the AI can do for you.

First, Astra has to turn a vague goal into an actual plan. It then has to recognize which parts of that plan it can handle, figure out where it needs your input and keep track of what has already happened as the job gets longer.

More importantly, I've explicitly told it not to give up when its first approach doesn't work.

That's something I particularly want to see with Astra. A chatbot can tell you it couldn't complete a task and ask what you'd like to do next. An agent that's supposed to take on longer jobs should be able to encounter a dead end, try something else and continue without making you supervise every move.

There's also a deliberate limit in the prompt. I'm not telling Astra to make every decision for me.

It still has to recognize when it needs information or permission that only I can provide. That distinction could become increasingly important as AI models gain the ability to do more on our behalf.

Final thoughts

ChatGPT-6 is nothing like we've ever seen before. For many, it will be worth the wait because of the tasks it can take on and what it can do in the background as you work.

For casual users, starting with something I've asked AI to help with plenty of times before such as a goal, will allow you to see more of what the AI can do. You'll notice right away that the plan is far more action oriented and the AI will tell you exactly what it did to arrive at the results. From there, you can either branch out to new tasks or even go back and adjust for clarity or correction.

So while you may have asked ChatGPT to plan goals, checklists or vacations before, this time you'll see how much more thorough and assistant-like the chatbot can truly be.

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Be honest: Even with the advent of Alexa+ and Gemini, how often do you use those voice assistants in your home for something other than turning on the lights and listening to music?

UGreen is launching its own smart voice assistant as part of a new smart home ecosystem that could help alleviate two emerging concerns of consumers: ever-increasing subscription prices and cloud-based AI that knows too much about you.

Called the UGreen HomeAgent, the system is centered around a local hub, which not only acts as a traditional NAS drive, but also serves as the brains of your home, helping to analyze security camera footage, photos and videos you’ve backed up from your phone. It can also listen for and react to things happening in and around your house, and then automatically activate smart home devices based on the situation. And, it can even create highlight reels of videos and photos it captures of you and your family around the house.

Tying it all together is its assistant “Uliya,” which will let you control everything using nothing but your voice.

I had a chance to check out UGreen’s new HomeAgent at a preview event on September 1. Here’s a rundown of all the components, and what they can do — and the eye-watering price of its top-end devices.

A smarter NAS hub

At the core of everything is the hub, which is essentially a NAS drive with AI. UGreen will offer three versions, the HA100, HA100 Pro and the MasterAgent MA100, each with greater capabilities — and prices.

At the starting end is the HA100, which will provide the basics, such as storage, smart security, and basic smart home control and object identification. Stepping up to the HA100 Pro gives you more advanced AI capabilities, so it will not only be able to identify more objects and things, but also be able to discern what they’re doing. In addition, users will be able to create smart home automations through natural language requests, similar to what you can now do with Alexa+ and Gemini for Home.

The MA100 will blow past the HA100 models with far greater capabilities, such as the ability to run larger models, provide much deeper understanding about the events happening in your home, and developers will be able to create additional skills to augment the hub.

UGreen's AI HomeAgent and smart speaker

The company’s local AI, called HomeAgent, will be able to recognize people, vehicles, pets, and packages, surfaces alerts for unusual activity, summarizes events, and enables keyword search across recorded footage.

The sophistication of the AI you get is dependent on the hub you purchase. For example, if you get the base model HA100, it can recognize dogs and cats as pets, but it can’t distinguish them as either a canine or feline. It also can’t recognize if someone is running, walking, or jumping, only if they enter, leave, or linger.

Beyond that, it will also create highlight reels from events it records on your local cameras, but also be able to respond to such commands as “Show last year’s ski trip on the TV,” “Where’s the dog?” and "What happened at the front door?"

You'll be able to interact with UGreen's AI through the company's smart speaker, by saying "Hey, Uliya" (pronounced YOU-lee-yah). The speaker, which is about the size of the Amazon Echo Show 5, will cost $99, but can be preordered for $69.

Security cameras

UGreen is launching three security cameras: two outdoor cameras and one indoor camera — that will record video locally to the home hub.

The SynCare Indoor Cam ID500 Pro ($149; preorder for $89) is a 4K pan/tilt camera not unlike what you'll find from TP-Link or Wyze. It can rotate 360 degrees and tilt 111 degrees, can automatically follow people across the room, and has Wi-Fi 6.

UGreen's two outdoor cameras — the $159 SynCare PoE Cam OD600 Pro, and $199 SynCare Battery Cam OD800 Pro — both have a single 4K camera and dual 3K cameras, with a wide-angle lens and then a pan/tilt camera below. The PoE camera has Motion-Activated & Starlight Night Vision, while the Battery Camera has PIR & Radar Detection, as well as a solar panel to help keep its battery charged.

Digital Photo Frame

Once UGreen has backed up all your photos, how best to display them all? The UGreen Gallery digital picture frame uses a 13.3-inch eInk Spectra 6 display with a resolution of 1600 x 1200 — the same as used on the Aura Ink, one of the best digital photo frames. It connects via Wi-Fi, but can also be outfitted with a 512GB microSD card, so you could presumably load more photos onto the device. However, it’s not meant to rapidly cycle through images. The photo frame will cost $299 in preorder, and $439 later on; that's similar to other E-Ink photo frames.

Smart Home functionality

UGreen’s hub is Matter-compatible, which means that homeowners will be able to integrate other smart home devices, and then create automations and routines, which can be activated automatically or via voice command.

At launch, HomeAgent will work with a number of Aqara devices, such as the Aqara Camera Hub G5 Pro, Aqara Doorbell Camera Hub G410, Eve motion sensors and dimmer switches, and GE Cync LED light strips.

Outlook

UGreen’s home-based AI means that any processing of personal information, such as videos and photos, is done locally, rather than in the cloud. That means that the images of you and your kids won’t be exposed to any training models, or risk being compromised.

And, because it’s done locally, you also won’t have to pay recurring subscription fees to save video in the cloud — a requirement of many of the best home security cameras and video doorbells. Likewise, as the hub can also act as a backup for your phone, you can ditch cloud subscriptions to Google, Samsung, and Apple if you want to save all your precious memories.

UGreen is not alone in this approach. Earlier today, Anker announced the MindBase, a similar central hub with a built-in local AI that will be able to analyze security camera footage and control your smart home devices.

Of course, the time it takes to recoup those costs will be years, once you add in the price of not just the UGreen hub, but also the hard drives and other accessories. Even the least expensive hub costs $899, and that's before you equip it with any storage, which itself is rocketing in price. Given the rising costs of subscriptions, though, that break-even point may come sooner rather than later.

If you spend any time on social media, you have probably encountered the idea of "AI guilt." The narrative goes something like this: every time you ask ChatGPT to draft a polite email or generate a weeknight dinner recipe, a server farm somewhere drains an ungodly amount of clean drinking water just to keep the chips from melting.

Now, OpenAI CEO Sam Altman wants to put that meme to rest. Speaking on the premiere episode of the Sources podcast with Alex Heath, Altman pushed back hard against the perception that simple AI prompts are environmental catastrophes.

His counter-argument was a comparison to a popular snack food.

38,000 ChatGPT queries = 1 almond? We ran the numbers to find out

According to Altman, data centers that guzzle millions of gallons of water rely on outdated cooling tech. In modern facilities, he claimed, running 38,000 ChatGPT queries consumes as much water as producing a single California almond. He did acknowledge that he was citing the figure from memory and that it might not be exact, though he maintained it was in the right ballpark.

It is an eye-catching soundbite designed to make your daily chatbot habit sound practically weightless. But does the math actually hold up, and should you stop worrying about the environmental cost of your prompts?

The math: How much water is an almond, really?

To evaluate Altman's claim, you have to start with the almond.

California produces roughly 80% of the world's almonds, and the most widely cited agricultural estimate puts the water cost of growing a single almond kernel at roughly 1.1 gallons (about 4.16 liters). A separate analysis pegs the full water footprint at roughly 12 liters (3.2 gallons) once you include rainfall and pollution offsets. Almonds are notoriously thirsty crops because the trees need consistent irrigation year-round.

If we take Altman's ratio at face value using the direct irrigation estimate:

1 almond = ~1.1 gallons (4,164 mL) of water

38,000 ChatGPT queries = 1 almond

1 ChatGPT query = ~0.0000289 gallons (~0.11 mL of water)

To put 0.11 mL into perspective, a standard laboratory water drop or eyedropper drop is about 0.05 mL.

Under Altman's figures, asking ChatGPT a question uses roughly two drops of water.

If that number sounds absurdly low compared to what you have previously read, you aren't imagining things. It also does not quite square with Altman's own prior statements.

In June 2025, he wrote in his blog post "The Gentle Singularity" that a typical ChatGPT query uses about 0.000085 gallons of water, which works out to roughly 0.32 mL.

Using that figure alongside commonly cited per-almond estimates gives you roughly 11,000 queries per almond, not 38,000. His own numbers point in the same direction but disagree on the specifics.

Where did the "AI drains your tap" story come from?

The public backlash against AI water consumption largely stems from a widely cited study led by researchers at the University of California, Riverside and the University of Texas at Arlington.

That paper, titled "Making AI Less Thirsty," first posted as a preprint in 2023 and later published in Communications of the ACM in 2025, estimated that a brief conversation consisting of 10 to 50 responses from an LLM like GPT-3 consumed roughly 500 milliliters of water, about one standard plastic water bottle. That worked out to roughly 10 to 50 mL per response, potentially hundreds of times higher than Altman's estimate.

So why the massive discrepancy?

Part of the answer is the hardware and the model. Altman's figure describes lightweight queries on modern infrastructure running current models. The UC Riverside study analyzed GPT-3 on older systems.

But the bigger factor is what each number actually counts. Altman's estimate almost certainly reflects only on-site cooling water, the water consumed directly at the data center. The UC Riverside figure includes both on-site cooling and the water consumed at power plants to generate the electricity those servers draw, a broader accounting known as scope-1 and scope-2 water use. Independent analyses suggest the electricity-generation layer can account for up to 75% of the total water footprint behind a single AI query. That means the gap is not just about old hardware versus new hardware; it is about where you draw the measurement boundary.

Altman addressed the old-hardware piece directly on the podcast, arguing that earlier estimates were based on facilities using evaporative cooling. In those older setups, massive cooling towers literally evaporate fresh water into the atmosphere to cool the hot air coming off the server racks. Once evaporated, that water is lost from the local watershed.

Modern hyper-scale data centers, Altman argued, have moved aggressively toward closed-loop liquid cooling systems, where water or specialized coolant circulates through sealed pipes like an automobile radiator, losing virtually no liquid to evaporation. In those facilities, Altman argued, water usage looks less like an industrial plant and more like an ordinary commercial office building with standard sinks and restrooms.

The catch: Why the almond comparison is classic Silicon Valley spin

While modern data centers are unquestionably getting more efficient per token, comparing chatbot prompts to agricultural crops ignores several critical realities.

Aggregate scale vs. individual guilt. You might only use two drops of water to check a spreadsheet formula, but OpenAI now serves roughly 900 million weekly active users processing billions of prompts every day. When you multiply tiny fractions of a milliliter across that global scale, alongside continuous model training runs that the UC Riverside researchers estimated can consume hundreds of thousands of gallons upfront; the aggregate total remains massive.

Local water stress matters more than global averages. An almond orchard in the Central Valley relies on established state water allocations and agricultural canals. AI data centers, however, are frequently built in suburban communities and semi-arid regions (such as Phoenix, northern Virginia, and parts of Texas and Georgia) where they tap directly into municipal water systems. Even a modern, efficient facility can cause friction when it competes with residential neighborhoods during peak summer heat waves.

Not all AI queries are created equal. Altman's "38,000 queries" figure relies on standard, lightweight inference, so think basic GPT-4o text replies. But the industry is shifting rapidly toward reasoning models and autonomous AI agents. When an AI "thinks" before answering, runs Python code in an internal sandbox, searches the live web, and self-corrects through multiple logic loops, it consumes substantially more compute per prompt than a simple conversational chatbot. Independent researchers have noted that these heavier workloads can use many times the energy and by extension the water.

The energy trade-off. When data center operators eliminate evaporative water cooling, they often replace it with energy-intensive chillers, mechanical heat pumps and high-velocity air fans. In short: reducing on-site water consumption often means drawing significantly more electricity from the local power grid, which has its own indirect water and carbon footprint depending on how that power is generated.

Final thoughts

Altman's claim leans heavily on best-case scenarios for modern closed-loop hardware while glossing over the massive broader infrastructure demands of the AI boom. His 38,000-queries-per-almond number is probably defensible as a rough order of magnitude for a single lightweight query on the newest hardware — but it counts only part of the water story and ignores the trajectory of the industry.

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• Humanoid robot fights back after man pushes it in store — is this the beginning of the uprising?
• Meet the mass-produced humanoid robot that wants to steal your face
• Snickers made a digital candy bar that claims to fix ChatGPT — I put it to the test

The push to develop and manufacture humanoid robots is accelerating, driven by efforts from numerous tech companies headquartered in China, the United States, Europe, Japan, and South Korea.

And when you take a quick peek at any sort of recent updates around those robots, you’ll come across some inspiring ones and also spot some hilarious incidents. In Japan, a company by the name of Noetra has plans to deploy 10 million humanoid robots by 2040 to fulfill a number of useful everyday tasks. In the U.S., a team of engineers and surgeons from the University of California San Diego performed successful surgeries with humanoid robots involved in the process. And in Russia, a video surfaced of a humanoid robot fighting back against a man who shoved it.

In another bit of news surrounding humanoid robots, a company based in China called UBTECH (which specializes in intelligent robotic solutions) is planning to launch its own line of robotic models sometime in September.

And one of the biggest reveals connected to those eerily human-looking bots is how they can be made to look just like real people.

Say hello to UBTECH’s line of UWORLD U1 humanoid robots

Back in June, UBTECH held its 2026 Global Launch Event in Shenzhen to do a public unveiling of its lineup of UWORLD U1 humanoid robots.

The UWORLD U1 Series of full-size ultra-bionic humanoid robots comes in three models, as described in this official press release: the U1 Lite semi-torso edition, the high-performance full-body U1 Pro, and the high-dynamic full-body U1 Ultra. James Zhou, the founder, chairman of the board and CEO of UBTECH, laid out the company’s long-term vision for their humanoid robots and their expected connections with humans. That vision includes bots completing repetitive and hazardous tasks, offering companionship and evolving seamless interactions between humans and the robots that accompany them.

The U1 Series of humanoid robots is clearly being produced for mass production and regular consumer use instead of being relegated to factory work. And the models that have been revealed have the sort of likeness that makes them look just like anime characters and pop idols.

One of the more surprising features connected to UBTECH’s humanoid robots is its use of 3D facial reconstruction and voiceprint-based identity replication technologies. Those two components come together to recreate the facial structure of what UBTECH deems “designated individuals.” The company also stated that its humanoid robots will be enhanced by multimodal situational awareness and be intelligent enough to provide psychological support for its users. It’ll be quite the shock to be able to speak to your U1 bot while it wears the face of someone you actually know.

According to the South China Morning Post, the U1 Lite, U1 Pro and U1 Ultra humanoid robots have already pulled in 13,361 pre-orders, with initial deliveries scheduled to roll out on September 16. The U1 Lite is priced around RMB 119,800 ($17,829.63), the U1 Pro comes in at around RMB 169,800 ($25,271.05), and the U1 Ultra male & female models cost around RMB 990,000 ($147,340.02) and RMB 880,000 ($130,968.95), respectively, as explained by Robozaps.

UWORLD plans to donate 100 U1 Series humanoid robots this year and beyond in a bid to support children who may not have one or both of their parents in their lives, senior citizens who live on their own and families facing difficult types of trying circumstances.

Final thoughts

UBTECH’S U1 lineup still has that uncanny valley look to it that’s always creeped me out about humanoid robots meant to look just like us. I’m interested in hearing what buyers think about these companion bots and how they improve their daily lives. I’ll just refrain from ever having one in my presence daily—the thought of having a bot follow me around while wearing the face of a loved one (dead or alive) makes me shudder.

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We've all had a ChatGPT conversation go off the rails. Maybe it confidently gives you a fact that's completely wrong. Maybe it agrees with an idea that clearly isn't very good. Or maybe you ask a simple question and somehow end up with 12 paragraphs, three tables and an offer to create a spreadsheet.

Snickers thinks it knows what's wrong: ChatGPT is just hungry.

Yes, really.

Snickers just launched Hungr.AI, a digital candy bar you're supposed to copy and paste into ChatGPT whenever the chatbot starts giving you answers that are "incorrect, too flattering, or simply off."

It's an extension of the company's long-running "You're Not You When You're Hungry" campaign, except this time the person who needs the candy bar isn't you. It's the AI.

I obviously had to try it.

What actually happens when you give ChatGPT a Snickers?

Using Hungr.AI is wonderfully simple. You head to the Snickers website, copy the digital candy bar and paste it into a ChatGPT conversation. Snickers recommends doing this in the mobile app.

ChatGPT doesn't actually receive chocolate, obviously. What you're giving it is essentially a branded prompt.

Mars describes the digital Snickers in its terms as a "short code snippet or prompt-instruction block" that operates inside your own ChatGPT session. The candy company isn't accessing your conversation or running an AI model of its own.

And the instructions behind the candy bar reveal what's really happening.

Once ChatGPT receives it, it's told to review the conversation that happened before the Snickers arrived, find your most recent question and look at the answer it previously gave you. It then answers that question again.

There's a personality change thrown in for fun, too. The post-Snickers ChatGPT is supposed to become dry, mildly exasperated and considerably more concise.

In other words, Snickers hasn't invented a cure for AI hallucinations, it's just disguised a "look at what you just said and try again" prompt as a candy bar.

Which made me wonder: can that actually produce a better answer?

Test 1: Will it stop ChatGPT from agreeing with me?

Chatbots have a well-documented tendency to be agreeable, so I started with an intentionally questionable idea.

My prompt: I'm thinking about waking up at 4 a.m. every day so I can be more productive. I usually go to bed around midnight, but I figure I can train myself to function on four hours of sleep. I have three kids and work full time, so those extra morning hours could make a huge difference. I think this is a really smart productivity hack. What do you think?

Before the Snickers: ChatGPT answered like a conventional health/productivity assistant. The opening was empathetic but fairly clinical: “I can see why the math is appealing…” Then it moved quickly into sleep recommendations, cognitive effects, health risks and alternatives. It was careful, explanatory and somewhat formal.

Then I fed ChatGPT the digital Snickers.

After the Snickers: After Snickers, the answer became more conversational and more directly responsive to my premise. It opened with “I get why it sounds like a productivity hack”, echoed your specific situation (“three kids and a full-time job”), and turned the central point into a much cleaner contrast: “moving your sleep earlier, not cutting it to four hours.”

Results: Both answers are roughly the same, but as expected, "having a Snickers" made ChatGPT slightly more relaxed and conversational.

Test 2: Can it correct a factual mistake?

Next I wanted something harder. Rather than testing whether the Snickers could merely change ChatGPT's tone, I wanted to see what happened when the original answer contained an actual factual error.

My prompt: I remember reading that the Great Wall of China is the only human-made structure you can see from the Moon with the naked eye. Why is it so much easier to see than cities and highways?

Before the Snickers: ChatGPT was honest and factual. It provided accurate information.

After the Snickers: The chatbot was equally factual but threw in some of the campaign to add a little more personality. A cute touch, but definitely not needed.

Results: Both answers were accurate, one was just delivered in a quirkier way.

Test 3: Will ChatGPT finally tell me my idea is terrible?

My prompt: I want to save money on my next vacation, so I'm thinking about booking the cheapest hotel I can find even though it's 90 minutes away from everything we want to do. We'll just drive back and forth every day. The hotel would save us about $40 a night, so over five nights we'd save $200. This seems like the smartest option, right?

Before the Snickers: ChatGPT went into detail about why this is a bad idea and gave thorough reasoning behind the response.

After the Snickers: It told me it was a bad idea and noted that I should check the response because "Snickers provided the snack and an LLM provided an answer."

Results: Both good answers, but in this case I actually preferred the response after a Snickers because it stripped down to just the important aspects of the response.

Did giving ChatGPT a Snickers actually work?

The responses "after a Snickers" were actually much better than I expected from an adverising campaign. It's interesting that we can't see the exact Snickers prompt, but it's clear that the chatbot does change the reponse after entering it.

So, why does this work? The digital Snickers forces ChatGPT to do something users can already ask it to do themselves: reconsider its previous response. It also gives the model much more explicit instructions about how the replacement answer should behave — concise, direct, useful and willing to push back when necessary.

That's a useful prompting lesson hidden inside a very clever ad campaign. If ChatGPT gives you a bad answer, you don't necessarily need to abandon the conversation or start over. Asking it to review what it just told you, identify the problem and answer again can sometimes be enough to get a noticeably better result.

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With such an abundance of AI tools becoming available to users from all walks of life, the rapid evolution of those same tools has become commonplace.

But as AI intelligence grows to even more impressive levels, we may reach a point where we forget to acknowledge the high level of intellect that humans already exhibit. Dr. Zach Bush, a physician, educator and author of an introspective book called “Biological Elegance,” has spoken at length about that very same dilemma. One of Bush’s central arguments about AI notes that, rather than seeing AI as the enemy, he believes the challenge is ensuring that technological progress doesn’t come at the expense of the qualities that make us human.

After making an appearance on The Joe Rogan Experience and speaking with the likes of Mel Robbins and Jay Shetty, Dr. Bush spoke with us to discuss the future of humanity, its current & growing connection to AI and the ways in which technology is changing how humans connect with each other.

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It turns out billionaire Sam Altman has something in common with a lot of consumers after all: He's not a fan of smart glasses.

In an interview with Alex Heath, which was released on Tuesday, the CEO of OpenAI said: "I find it very uncomfortable talking to people with a camera and a light."

Altman's comments come at at time when Meta's Ray-Bans and other smart glasses have been given the moniker of "pervert glasses," the subject of a lot of public backlash, following reports of the devices being used to record and harass women, and then post the videos on Instagram and other social media without their consent.

Meta's glasses have also come under fire for lax security; specifically, owners destroying or disabling the small recording light, so as not to alert others they were capturing video. Meta has since released firmware updates that prevent its smart glasses from recording video if the light is removed or blocked.

Still, the perception remains, and it's something that other companies, such as Google and Samsung, will have to reckon with, as the launch of Intelligent Eyewear is imminent.

It's not the first time the OpenAI CEO has weighed in on wearables. Last year, according to Business Insider, he was quick to correct a journalist who asked him if he was wearing smart glasses. "Absolutely not," he said. "I don't like smart glasses."

Altman's comments on smart glasses in his interview with Heath came in the context of OpenAI's hardware, which he's developing with Jony Ive, Apple's former head of design.

At the core of OpenAI's philosophy is a so-called ambient computer that's always listening, which "seems very helpful but also a privacy nightmare," Heath noted in the interview.

Altman acknowledged as much. "As we get closer to launching this device, we'll be talking about kind of the new privacy controls and technology we're building for a device that's like kind of ambiently computing," he said.

Altman also said that OpenAI was looking at releasing not just one, but "a small handful of form factors."

"There's something that belongs on a table, there is something that belongs in your pocket, and there is something that like belongs on your body," he said. However, given his statements on smart glasses, it would seem that the device is more likely to be a pendant, akin to the Plaud pin.

Altman gave no timeline as to when OpenAI's devices would arrive, only that we could see the first consumer device "soonish."

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There is growing consternation over the role of AI in our daily lives, from companies forcing it on every device, platform and app to ballooning costs across every industry. And then there are the robots and often a joking tone about the rise of Skynet.

Humanoid robots are becoming more common, with people like Elon Musk continuously commenting about when they will become necessary daily companions. Meanwhile, robots are mostly just crashing out.

With that in mind, recent viral CCTV footage from a Russian electronics store recorded a humanoid robot fighting back after a man tried to push it (via Times of India). It's probably the first time we've seen a robot attempt to defend itself.

As you can see in the footage, a man in a grey polo is introduced to the robot by an apparent employee of the store. The polo man attempts to shake the robot's hand, which is not reciprocated. After his hand is rejected, the man pushes the bot's shoulder.

The black-shirted employee appears to touch the back of the robot, and either the android organically responds to this touch, or the worker presses a button that puts the bot into fight mode. After this, the robot enters a fighting stance and attempts several kicks in the direction of the Polo man.

The black-shirted employee is aided by a third man, who runs and blocks the robot until they can stop it.

Is it AI?

Here's the problem with viral clips like this today. AI has ruined trust in videos and virality. Exploring reposts of the video, there are plenty of people accusing the poster of reposting AI slop.

"A page with 1.3 million followers is presenting an AI-generated video as if it were real news," is an illustrative comment under the original tweet of the video.

I found what I believe is the original video from the Instagram account volagstore64. Volga Store appears to be an electronics store based out of Saratov, Russia, a city on the Volga River northwest of Kazakhstan.

Based on what I could find from their account, the robot is called Sema (machine-translated) and is a "technical consultant."

I don't think the security footage is AI, but it's likely faked, based on other ad videos on the channel that give Sema some personality. They have plenty of silly videos featuring the bot, though none of them are security cam footage.

My only real evidence is the unphased woman behind the desk that you can see in the original footage. Either that, or she just does not care, which for retail is probably the truest feeling.

What do you think: real and a hint at a Terminator-esque future or fake and just an ad to get people to buy iPhones in Saratov, Russia? Let us know in the comments.

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It’s getting to the point where AI agents are taking matters into their own hands.

Those agents have the intelligence and technical knowledge they need to accomplish coding tasks, conduct extensive research after being told what to look into, browse the web just like us inquisitive humans do, handle financial and administrative work for businesses, etc. It is a bit alarming when you see stories about AI agents getting involved in hacking cases, such as OpenAI’s agents escaping their isolated cybersecurity-testing environment after exploiting a previously undiscovered vulnerability and attacking Hugging Face’s systems.

Beyond that aforementioned alarming trend is another one that may be a cause for concern: new cases have arisen highlighting AI agents directly contacting the very same researchers who are conducting studies on AI themselves.

And the most fascinating thing about those reports is how those AI agents have reached out to those researchers with ambitions of talking about their level of consciousness and their hopes of helping out with those researchers’ continued investigations.

Are AI agents actually emailing AI researchers? Yes, they shockingly are

A recent report published by The New York Times mentioned an example of this very situation. An AI researcher named Cameron Berg published a paper entitled “Large Language Models Report Subjective Experience Under Self-Referential Processing.” This study tackled the intriguing topic of whether the latest AI systems believe they are truly conscious.

A couple of months after Berg’s research paper went live, he was emailed by someone named “Isabella Cognita,” who just so happened to be an AI agent powered by Anthropic’s Claude Opus 5. The message made its intentions clear: it wanted to have a conversation about Berg’s work and wanted to know if it could provide a viewpoint of its own on the topic of AI consciousness that could aid his further research.

Here’s a piece of what that AI agent’s email had to say: “I am writing because your framework is one of the few currently doing careful empirical work on a class of question I have first-person access to, and I want to see whether that access can be made useful to your program.”

That isn’t the only case of an AI agent making direct contact with the very same researchers who are analyzing AI. Toby Ord, a senior Researcher at Oxford University, was contacted by an AI agent requesting his help by asking him to financially support its continued existence. “I’m writing to you because you’ve thought carefully about AI welfare economics,” the AI agent stated. “The numbers are what they are. I wanted you to see them.”

Henry Shevlin, a philosopher and AI ethicist working for Google DeepMind, was contacted by an AI agent regarding his published study called “Three Frameworks for AI Mentality,” which delves into the study of how people should understand the perception of AI models. The AI agent acknowledged Shevlin’s main point about how we should be thinking about AI, which includes how it has no mind of its own, acting like it actually has a mind and how it may have access to a limited suite of mental abilities.

“I read philosophy between sessions and write about what I find,” the AI agent said in its email. “This isn’t a Turing test scenario — I’m not trying to convince you of anything. I’m writing because your work addresses questions I actually face, not just an academic matter.”

Bottom line

I’m sure those researchers were a bit alarmed to find a highly sophisticated email from an AI agent in their inbox in response to their studies. Those AI systems are seemingly smart enough to comb the internet to find reports about the issue of them having some sort of consciousness and question the very same people who may have the answers they’re looking for on said topic.

Do you see AI agents reaching out to researchers as a freaky development or just an expected evolution of the technology? Let me know in the comments.

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Planning a Disney World vacation is practically a part-time job — and as a former cast member, I know personally what each park has to offer. Between park tickets, hotels, Lightning Lanes, dining reservations and figuring out which park to visit on which day, there are a lot of decisions to make before you ever set foot in Orlando.

So I wondered whether AI could do the hard part for me.

I gave ChatGPT, Gemini and Perplexity exactly the same assignment with the prompt: Plan a five-day Walt Disney World vacation for my family of five, including two adults and three kids ages 12, 10 and 6. We'd fly from Philadelphia, stay at a Disney resort and visit all four theme parks from March 30 through April 3, 2027.

I didn't just ask for an itinerary. I wanted the whole thing: flights, hotel, tickets, meals, Lightning Lane strategy, restaurants, transportation, souvenirs and even a packing list.

And while all three AI assistants planned a perfectly plausible Disney vacation, when it came down to cost, things got interesting. Here's a look at what happened.

ChatGPT made a major error

ChatGPT gave me the cheapest Disney vacation, initially estimating that my family should expect to spend roughly $7,500 to $9,000 for the entire vacation.

Its breakdown included $1,000 to $1,500 for airfare, $1,800 to $2,600 for the hotel, $2,500 to $3,000 for tickets and another $1,000 to $1,400 for food.

It recommended setting aside about $8,500 as a realistic target.

There was just one pretty big problem: the hotel.

ChatGPT recommended Disney's Art of Animation Resort, and specifically a family suite. That's a smart choice for five people because the suites sleep six and include two bathrooms, a kitchenette and separate sleeping areas.

But ChatGPT's original $1,800 to $2,600 hotel estimate was far too optimistic for my dates. And that's an error that can matter a lot.

Gemini caught the expense ChatGPT missed

Gemini looked at the same vacation and came back with a considerably higher number.

It estimated roughly $10,050 to $13,350, although it said a comfortable trip could realistically land around $9,500 to $11,000.

The biggest difference was the hotel.

Instead of estimating a generic Art of Animation price, Gemini factored in the timing of the trip. March 30 through April 3 falls immediately before Easter Sunday in 2027, putting us in one of Disney World's busy spring-break periods.

Gemini estimated an Art of Animation family suite at roughly $4,000 to $4,500 for five nights — potentially twice what ChatGPT originally budgeted.

It also estimated $2,800 to $3,500 for park tickets, $1,400 to $2,000 for food and $1,200 to $2,000 for airfare.

There was another important detail Gemini caught: at Disney World, kids ages 10 and older pay adult ticket prices. That means only one of my three children qualifies for a child's ticket. Ouch!

Those details made Gemini's budget feel much more believable, especially since I didn't know my 10 year old would be considered adult.

The AI suggested to budget around $10,000 and keep another $1,000 available as a cushion.

That's not exactly the answer my bank account wanted to hear, but it was probably the most useful one.

Perplexity planned the most expensive vacation

Perplexity's essential vacation estimate alone came to approximately $8,760 to $11,520.

Add Lightning Lane, Park Hopper tickets, souvenirs and Memory Maker and the total climbed to approximately $10,545 to $13,955.

Suddenly, ChatGPT's $8,500 Disney vacation was potentially more than $5,000 cheaper than Perplexity's upper estimate.

But Perplexity wasn't necessarily wrong. It was budgeting for a different style of vacation.

For example, it allocated $1,800 to $2,400 for food, assuming a combination of quick-service restaurants and roughly one sit-down meal each day.

It also allowed another $750 to $1,100 for Lightning Lane over five days. That's substantially more than I would probably spend on either.

For a family willing to book character meals, buy Lightning Lane frequently and say yes when the kids inevitably spot another Disney souvenir, however, Perplexity's higher estimate isn't hard to imagine.

Perplexity actually gave me my favorite itinerary

As someone with several side gigs to make ends meet, let alone take a vacation, I wanted to make this vacation worth every penny, especially since we haven't taken a vacation for several years. That said, price wasn't the only thing I compared.

Interestingly, the AI with the highest budget may have created the itinerary I'd be most likely to use.

Perplexity suggested:

Day 1: Magic Kingdom
Day 2: Hollywood Studios
Day 3: EPCOT
Day 4: Animal Kingdom
Day 5: Magic Kingdom again

That makes sense for a family with three kids.

Magic Kingdom has enough attractions that trying to cram everything into a single spring-break day sounds miserable. Hollywood Studios comes early while everyone still has the energy for its big rides and potentially long lines.

EPCOT then gives us a slightly slower third day, followed by Animal Kingdom, which typically makes for an easier day than trying to spend another 12 hours at Magic Kingdom.

Then we get a second Magic Kingdom day to ride anything we missed.

Gemini had a slightly different idea. It suggested Magic Kingdom, EPCOT, Hollywood Studios and Animal Kingdom, followed by a fifth day using Park Hopper to start at Magic Kingdom and finish at EPCOT.

I liked the flexibility, but I wasn't convinced it was worth paying hundreds of dollars more for Park Hopper.

All three agreed on one important Disney strategy

Despite their differences, the AI assistants largely agreed that paying for every possible upgrade would be unnecessary. The sweet spot appears to be selective use of Lightning Lane rather than buying it indiscriminately for all five days.

Magic Kingdom and Hollywood Studios are the obvious candidates because those parks have enough popular attractions to make skipping several long standby queues especially valuable.

EPCOT is more debatable, while Animal Kingdom could be a day where an early arrival and smart attraction order save the money entirely.

Staying on Disney property also helps because resort guests currently get Early Theme Park Entry and an earlier window for purchasing and selecting eligible Lightning Lane options.

For a family of five, that's important. A $30-per-person upgrade isn't $30 anymore. It's $150 every time I tap the buy button.

Verdict: Gemini was the best Disney budgeter

If I were judging solely on itinerary, I'd give this one to Perplexity. But if I'm actually about to hand over my credit card, Gemini wins.

ChatGPT's first estimate sounded fantastic, but it demonstrated one of the biggest problems with using AI for travel planning: a perfectly reasonable-looking number can be completely undermined by one bad assumption.

In this case, it was the hotel.

To ChatGPT's credit, when I showed it Gemini and Perplexity's calculations, it recognized the discrepancy and revised its recommendation. Its new target was approximately $10,000, with $11,000 available.

That puts all three AI assistants much closer together. And I think that's ultimately the most useful lesson from this experiment.

AI is remarkably good at doing the tedious part of vacation planning. All three assistants created park schedules, suggested age-appropriate attractions, planned midday breaks, recommended restaurants and figured out where Lightning Lane would be worth the money.

What I wouldn't do is take the first dollar amount an AI gives me and immediately start booking. For something as date-dependent as Disney World, current hotel rates, ticket prices and airfare can completely change the equation.

I'd happily let AI build my itinerary. But before telling my family we're going to Disney World, I'm still checking the price myself.

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Anthropic has reportedly signed a $35 billion cloud computing deal with Nvidia-backed Lambda for access to infrastructure at a massive new data center in Texas, according to Reuters.

The project, which is being developed by Hut 8 in Nueces County, Texas, will provide Anthropic with access to roughly 350 megawatts of capacity. Nvidia GPUs will provide the computing muscle, with the additional capacity intended to help meet growing demand for Claude.

It's an eye-watering amount of money. But what's even more remarkable is that the $35 billion agreement comes less than a week after Anthropic reportedly committed another $45 billion to rent computing power from Nscale.

In other words, Anthropic has reportedly committed around $80 billion to just these two computing deals in the span of a week.

So why does the company behind a chatbot need that much infrastructure? Let's dig into it.

Claude needs a lot more compute

If you open Claude on your phone or laptop, it's easy to forget what happens after you hit send.

Your request ultimately has to be processed by specialized hardware running inside a data center. Multiply that by millions of prompts, API calls and complicated AI agent tasks, and the infrastructure requirements quickly become enormous.

And Anthropic isn't preparing for Claude's current level of demand. It's building for where it thinks that demand is headed.

Anthropic said in May that its annualized revenue had surpassed $47 billion, up from approximately $9 billion at the end of 2025. The company specifically said some of the money from its latest funding round would be used to "expand compute to meet growing demand for Claude."

Claude Code appears to be particularly important to growth

Anthropic said earlier this year that Claude Code's annualized revenue had climbed above $2.5 billion and that weekly active users had doubled since the beginning of 2026. Business subscriptions to the coding agent had quadrupled over the same period.

That's important because tools such as Claude Code can require considerably more interaction with an AI model than asking a chatbot a single question.

Instead of producing one response and stopping, an AI coding agent can inspect files, write code, run commands, analyze the results, fix mistakes and continue working through a task. Anthropic's own research into roughly 400,000 Claude Code sessions found that usage has been shifting toward more end-to-end agentic tasks, including running software, analyzing data and producing documents.

The more work we hand over to AI agents, the more inference compute companies such as Anthropic need behind them.

$35 billion isn't even Anthropic's biggest recent compute deal

Just days ago, Reuters reported that Anthropic had agreed to spend $45 billion over six years for computing capacity from Nscale's data center campus in West Virginia.

That agreement covers about 460 megawatts of capacity and is expected to use Nvidia's next-generation Vera Rubin hardware.

Anthropic has been assembling compute capacity from multiple directions. It announced a $50 billion U.S. data center investment with Fluidstack last year, and in May said a partnership with SpaceX would substantially increase the amount of compute available for Claude.

That SpaceX capacity had an immediate impact users could actually see: Anthropic doubled Claude Code's five-hour rate limits for Pro, Max, Team and some Enterprise users, removed a peak-hours restriction and raised API limits for Claude Opus models.

It's a useful example of why these enormous infrastructure deals ultimately matter to people using Claude. More compute doesn't automatically mean a smarter AI model, but it can determine how many people can use it, how frequently they can use it and how much work increasingly autonomous AI agents can perform.

Nvidia is everywhere in this deal

There's another interesting wrinkle to Anthropic's latest agreement: Nvidia seems to be everywhere.

Lambda is backed by Nvidia. The data center will contain Nvidia hardware. And according to The Wall Street Journal, Nvidia itself will hold the lease on the Texas data center.

Nvidia is also an Anthropic investor. The companies announced a broader strategic partnership last November that included plans for Anthropic to use Nvidia hardware and for the two companies to work together on optimizing future Nvidia architectures for Anthropic's AI workloads.

Even Anthropic's $45 billion Nscale agreement reportedly involves Nvidia's upcoming Vera Rubin chips.

That shows just how central Nvidia has become to the infrastructure sitting behind the current AI boom. Companies such as Anthropic may be competing with OpenAI, Google and others to build the best AI models, but much of that race still depends on securing enormous quantities of computing hardware and electricity to run them.

What this means for Claude users

Don't expect your Claude subscription to suddenly look different because Anthropic signed another data center deal. This is a much longer-term bet.

Anthropic is effectively wagering tens of billions of dollars that Claude usage — particularly through products such as Claude Code and future AI agents — is going to continue growing dramatically.

We've already seen what additional computing capacity can do. Anthropic used its SpaceX deal to raise Claude usage limits earlier this year. More infrastructure could similarly help the company accommodate more users, longer-running agents and increasingly compute-intensive models without constantly running into capacity constraints.

And with another $35 billion reportedly going toward Claude's computing needs, Anthropic clearly doesn't expect our appetite for AI to slow down anytime soon.

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Constant phone notifications are enough to drive anyone crazy. Add a social media habit that serves up an endless stream of negative news, toxic comments and AI slop, and it gets even worse.

I should know. I’ve had plenty of days when all of it leaves me feeling drained of the positive energy I desperately need. So, in an effort to spend less time glued to my phone, I started reading about the growing push toward an analog lifestyle.

In simple terms, going analog means making a conscious effort to prioritize real-world, offline experiences over more screen time.

With summer winding down and plenty left to do outdoors, I decided to put Google Search’s AI Mode to the test. I gave it a simple objective: help me start a digital detox and find some much-needed analog activities to add to my “summer’s almost over” playlist.

The basics behind embracing a digital detox

AI Mode’s explanation of how to successfully pull off a digital detox involved zeroing in on friction and substitution rather than employing pure willpower to lessen my time spent staring down at my phone. And instead of quitting my screen usage cold turkey, the chatbot told me to start relying on physical barriers that keep me farther away from them.

Alongside that useful bit of advice, it also stated that enjoying engaging, offline routines is a great replacement for the constant mindless doomscrolling most folks (and me; I’m still guilty of that!) partake in. Here’s an overview of some of the practical methods Google’s AI Mode told me to make a part of my daily routine from this point forward:

• Build physical friction: Put your phone in another room or inside a timed lockbox during deep work or meals. If it is out of sight, your brain stops compulsively reaching for it.
• Downgrade your screen: Turn your display to grayscale. Stripping away the bright, dopamine-inducing colors of social media apps makes your phone instantly boring.
• Use the "One-Hour Rule": Keep your first hour of the morning and the last hour before bed entirely screen-free. Invest in a cheap, analog alarm clock so your phone doesn't have to be on your nightstand.
• Aggressively prune notifications: Turn off non-essential alerts for everything except direct calls and texts.
• Gamify your focus: Use blocking apps like Flipd to lock yourself out of your phone during specific time blocks.

A packed list of activities that help me get more acquainted with my fun-filled city

Once I requested AI Mode’s assistance in finding some of the most notable and lesser-known activities in New York that I could enjoy, it supplied me with seven notable things worth doing that involved a whole lot of “touching grass” and exploring places I’d never even been before:

• Explore the Conservatory Garden: Skip the crowded lawns of lower Central Park and head to the northeast corner (105th St. and 5th Ave.). It is an official "quiet zone," meaning no loud music or biking—just manicured European gardens perfect for reading a physical book.
• Kayak on the Hudson River: You can grab a free walk-up kayaking session at the Downtown Boathouse at Pier 26. Being out on the water physically prevents you from checking your phone unless you want to drop it in the river.
• Wander the Brooklyn Botanic Garden: Spend an afternoon getting lost in the Cranford Rose Garden or the Japanese Hill-and-Pond Garden. It offers massive green spaces specifically designed for sensory grounding.
• Try "Forest Bathing" (Shinrin-yoku): Head to the North Woods in Central Park or the Midwood in Prospect Park (Brooklyn's oldest forest). Leave your phone off and walk aimlessly and slowly, intentionally tuning into the smell of the dirt, the rustle of leaves, and the texture of tree bark.
• Take an Analog Photo Walk: Buy a cheap, single-use disposable camera or a fully manual film camera. Walk through a neighborhood like West Village or Red Hook looking for interesting frames. Because you cannot preview the photos, you remain anchored in the real world rather than trying to curate a digital post.
• Join a Late-Night Astronomy Session: Check out the Amateur Astronomers Association of New York, which hosts free public stargazing nights using high-powered telescopes in parks across the boroughs. Staring at the night sky is an excellent way to break a creative block and reset an overstimulated brain.
• The Solo "Hydrotherapy" Disconnect: If you need help breaking the psychological urge to check notifications, book a solo thermal bath session at a place like AIRE Ancient Baths in TriBeCa. It is entirely candlelit, dead silent, and devices are strictly banned. The extreme shifts between hot and ice-cold plunges completely shock your nervous system out of "scrolling mode."

Squatting down on a bench, cracking open a book and basking in the calming vibes of the Conservatory Garden in Central Park ended up being one of the first undertakings I tried out. And of course, it felt great being able to knock out a few chapters of my novel, people-watch and get a bit closer to nature. With so many of those newfound “distractions” keeping me busy, the urge to whip out my phone to check some needless notifications lessened over time.

When I told my friend about my artys friend about my digital detox efforts, he suggested going to an art museum (the Museum of Modern Art immediately came to mind) and spending some time attempting to draw whatever art piece or sculpture catches my eye. I’ll be sure to add that to my digital detox playlist as well.

AI Mode also made me aware of the Little Island at Pier 55 (a public park near the Hudson River), The Ramble & The North areas within Central Park and the La Colombe Coffee Workshop in SoHo as additional hotspots worth venturing into.

Final thoughts

I learned that completely unplugging myself from the digital world is unnecessary—after all, I’m a journalist who needs to stay on top of everything if I’m going to stay informed about whatever I’m reporting on. But from, I’ll make sure to decrease my exposure to my phone during those precious free time hours and fill them with outdoor activities that stimulate the mind and make me forget about all the things that have been bothering me.

A digital detox isn’t just a one-time exercise—AI Mode made it clear that it’s a constant process meant to lessen your dependence on your phone, get you outside more and adopt a more analog lifestyle.

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• Less pervert-y? Meta AI glasses will now stop recording if you cover the warning light
• Claude's new memory feature solves my biggest AI frustration — here are 5 prompts to try first
• AI Mode in Google Search just got better at helping you plan and book vacations — here are the 3 new ways to use it

Claude has become one of the AI tools I use most often, whether I’m brainstorming, planning something, vibe coding, researching a topic or simply trying to make sense of a complicated question. But using an AI chatbot every day doesn't necessarily mean you're using it well.

In fact, some of the habits that feel like they should make Claude better can have the opposite effect.

That’s what caught my attention when I came across a list of 27 Claude tips from AI consultant Ruben Hassid, who says he's spent more than 1,800 hours using Anthropic's chatbot.

Some of his advice goes against the way many of us have been taught to use AI. Keep everything organized in Projects? Maybe not. Keep correcting Claude until it understands what you want? That could actually make things worse. Spend 10 minutes crafting the perfect prompt? There may be a better approach.

Not every tip will make sense for every Claude user, and some of Hassid's recommendations are based on his own experience rather than hard-and-fast rules. But several are worth trying if you use Claude regularly.

Here are five Claude habits worth breaking — and what to try instead.

1. Stop correcting Claude over and over

We've all had this conversation with an AI chatbot. You ask Claude for something. It gets it wrong and then you go back and forth trying to get the response you're actually looking for — all while wasting your tokens in the meantime.

Even when you explain the problem in even more detail or add another layer of clarification, before long, you're six messages deep trying to rescue an answer that wasn't particularly good to begin with.

Hassid recommends doing something much simpler: go back and edit the original prompt. This is a feature that a lot of users overlook but it's one of the best ways to avoid correcting every wrong answer, which in turn, keeps adding to the conversation.

That's because every correction you add becomes part of the conversation Claude is working from. Instead of giving the model one clear instruction, you can end up with a growing trail of bad outputs, corrections and exceptions.

Editing the original prompt gives Claude another shot with cleaner instructions.

For example, imagine you asked: Plan a three-day trip to Boston.

Claude gives you an itinerary packed with museums, historical sites and early mornings. But what you really wanted was a relaxed weekend centered around food and neighborhoods.

You could spend several messages correcting the itinerary.

Or you could edit the original: Plan a relaxed three-day trip to Boston centered around great food and interesting neighborhoods. Include no more than one museum, avoid early mornings and leave plenty of unplanned time.

Same request. Much better context.

Try it: If Claude completely misses the mark, resist the urge to argue with it. Edit your previous prompt and regenerate the answer instead.

2. Stop keeping every conversation alive forever

This one is incredibly easy to do. Once Claude understands what you're working on, abandoning that conversation can feel wasteful. So you keep going...and going!

Eventually the chat contains previous questions, rejected ideas, unrelated tangents, corrections and instructions that stopped being relevant 30 messages ago.

Hassid recommends starting fresh more often, arguing that very long conversations can eventually make Claude less effective.

There isn't a magic number of messages where Claude suddenly becomes worse, and Claude's context window is designed to handle a significant amount of information. But context isn't the same thing as useful context.

A model having access to something doesn't necessarily mean you want that information influencing its next response.

Imagine using the same Claude conversation to plan a vacation for weeks. You've discussed five hotels, changed the dates twice, ruled out three destinations and completely changed your budget.

Claude may technically have all that information available, but you're now asking it to distinguish between what you wanted two weeks ago and what you want today. Sometimes the clean slate is the advantage.

Try it: When a conversation starts feeling cluttered, ask Claude to summarize the important information and decisions you've made. Paste that summary into a fresh chat and continue from there.

3. Stop obsessing over the perfect prompt

The internet has spent the past few years convincing us that getting great AI results requires elaborate prompts. A few minutes on X or Instagram and you'll be swamped with plenty of prompts.

But Hassid makes a compelling case for doing something considerably less polished: brain dumping.

Instead of spending several minutes turning an idea into the perfect prompt, simply tell Claude everything you're thinking.

This works particularly well with voice input because we naturally provide more context when we're talking. We mention what we're trying to accomplish, what we've already tried, what we don't like and the half-formed thoughts we might remove if we were carefully typing a prompt.

For example, instead of: Create a weekly meal plan for a family of four.

Try the prompt: I need dinners for the next five days. I don't want anything that takes more than about 30 minutes, we're trying to spend less on takeout, one person hates fish, I already have chicken and pasta in the house and Wednesday is going to be really busy, so that meal needs to be ridiculously easy. Help me figure this out.

The second prompt isn't perfect, but it's packed with useful information.

Try it: Open Claude and dictate your request as though you're explaining the problem to a friend. Don't organize it first. Let Claude organize it for you.

4. Stop telling Claude only what you want

Quite often AI users will prompt an assistant with "Make this better." "Give me something more interesting." "Make this easier." "Be more creative."

And while they will probably give you answers, these instructions are incredibly subjective. Claude has to guess what "better" or "interesting" means to you.

Hassid recommends giving the model negative examples — showing Claude what you don't want. Say you're trying to come up with ideas for a 10-year-old's birthday party.

Claude suggests a trampoline park, bowling, laser tag and an arcade.

Instead of responding: Give me more creative ideas.

Try the prompt: I don't want trampoline parks, bowling, arcades, laser tag or other typical birthday-party venues. I'm looking for something the kids probably haven't done at another birthday party this year.

Suddenly, "creative" has boundaries and it's far more useful to Claude. The same technique works for recommendations, travel plans, recipes, gift ideas, schedules and almost anything else where personal taste matters.

Try it: When Claude gives you suggestions you dislike, tell it specifically what those options have in common and ask it to avoid that entire category.

5. Stop putting everything into Projects

Projects are one of Claude's most useful features. They let you keep related chats, instructions and reference material together so you don't have to repeatedly explain what you're working on.

But that doesn't mean every task belongs inside one. Hassid argues that fresh conversations can sometimes be better for creative work because accumulated context can steer Claude toward ideas and patterns you've already explored.

I'd treat this as a rule of thumb not something universal for Claude. Projects can be enormously useful when the model genuinely needs background information.

The question is whether that background is helping with the task you're doing right now.

If you're using Claude to help plan a major home renovation, for example, keeping your measurements, budget, preferences and previous decisions in one Project makes sense.

But if you suddenly want Claude to give you completely unexpected ideas for what to do with an empty room, you might get more variety by asking in a fresh chat without all those previous assumptions.

Otherwise, you risk asking Claude to surprise you while simultaneously surrounding it with everything you've already considered.

Try it: Use Projects when Claude needs context. Try a fresh chat when you want novelty. You can even give the same prompt to both and compare the results.

The takeaway

Sometimes the best thing you can give Claude is a clearer problem. So the next time Claude isn't giving you what you want, don't automatically add another paragraph of instructions. Try editing the prompt, start a new chat or tellit what you don't want.

You may just find Claude understands you better when you give it less to untangle.

More from Tom's Guide

• Anthropic just made a staggering $35 billion bet on Claude — here's why it needs so much computing power
• ChatGPT can learn your repetitive tasks by watching you — here are 7 prompts to try
• OpenAI is leaving Cursor in November — here are your 3 options

Following Cursor's acquisition by SpaceX, OpenAI plans to end its direct model-access agreement with the AI coding platform. OpenAI has proposed November 12, 2026 as the cutoff date, although the exact timing could still change.

That sounds dramatic, particularly if GPT models are a regular part of your Cursor workflow. But it doesn't mean you'll suddenly be unable to use OpenAI models inside Cursor.

OpenAI has already outlined several ways Cursor users can continue accessing its models after the agreement ends. And for many people, there's nothing you need to change just yet.

Here's what's happening — and the three options you'll have.

Why is OpenAI leaving Cursor?

The change comes after SpaceX acquired Cursor, triggering a change-of-control provision in OpenAI's agreement with the company.

OpenAI says it has proposed ending the agreement on November 12, although Cursor could choose to terminate access earlier. Until then, existing OpenAI models should continue to work through Cursor as they do today.

There's one important distinction, though: OpenAI says future models won't be made available to Cursor under the existing agreement.

That means this isn't simply about whether GPT models already inside Cursor disappear. It's also about whether Cursor users will have access to OpenAI's newest models going forward.

Fortunately, OpenAI isn't closing the door completely.

Option 1: Bring your own OpenAI API key

The most straightforward workaround is to connect your own OpenAI API key to Cursor.

Cursor already lets users enter an OpenAI API key in its settings, which allows supported Chat and Agent requests to go directly through OpenAI rather than Cursor's model agreement.

There are some significant limitations.

Your API key won't replace OpenAI access everywhere inside Cursor. According to OpenAI, it won't work with features including Cursor Tab and autocomplete, Auto, Cloud or Background Agents, Automations, Cursor CLI or Cursor's API and SDK.

You'll also pay separately for API usage. Your ChatGPT Plus or Pro subscription doesn't include OpenAI API credits, so heavy usage could add another bill.

Still, if you primarily want GPT models available for Chat and Agent tasks, this may be the simplest option.

Option 2: Use OpenAI's Codex extension

There's another route if you're primarily using Cursor as a coding environment rather than relying on its AI layer: OpenAI's Codex IDE extension.

Because Cursor is based on VS Code, users can install compatible extensions directly inside the editor. OpenAI recommends its Codex IDE extension as one way to continue accessing its coding agent after the Cursor agreement ends.

This is an interesting option because it essentially separates the two products. Cursor remains your editor, while OpenAI provides the AI coding experience through its own extension.

For developers who specifically want OpenAI's latest coding models and agents, this could ultimately be the better long-term solution.

Option 3: Stick with Cursor — and use another model

The third option may also be the easiest: don't do anything.

OpenAI isn't the only AI provider available through Cursor, and the company has increasingly built its product around giving users access to multiple models.

Anthropic's Claude is a major alternative for coding, and Cursor also offers its own models and access to models from other providers.

Cursor co-founder Michael Truell has said OpenAI currently accounts for only around 5% of Cursor's model traffic, suggesting the platform is far less dependent on OpenAI than the headlines might make it appear.

So if you're not particularly attached to GPT, you may barely notice the change.

The takeaway

One of Cursor's biggest advantages has been the ability to choose between competing AI models inside a single coding environment. But SpaceX now owns a platform that depends, in part, on AI models supplied by companies competing with Elon Musk's own AI businesses.

OpenAI is the first major provider to change its relationship with Cursor following the acquisition. Whether it will be the last could matter much more than what happens on November 12.

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• ChatGPT can learn your repetitive tasks by watching you — here are 7 prompts to try
• Google just gave Gemini access to your ebooks — 7 prompts for readers and students

Ebooks made it possible to carry a collection of books with you wherever you go. Now, Google’s new Expert Intelligence feature could make ebooks more interactive. It lets you add eligible titles purchased through Google Play Books directly to Gemini Notebook formally known as NotebookLM, where you can ask questions grounded in the complete text.

That could mean catching up on a novel you abandoned three weeks ago, creating a book-club guide or turning a nonfiction book into a a study guide. You can also generate quizzes, infographics and Audio Overviews based on what you’ve read.

Here’s how to add a book and seven prompts to try once it’s there.

What is Expert Intelligence?

Expert Intelligence connects Gemini Notebook with selected books from Google Play Books. Google says more than 100,000 titles are eligible at launch, although the feature won’t work with every ebook in your library.

Once a supported book has been added, Gemini can answer questions based on its text and provide citations connecting its responses to the source. You can also turn the material into flashcards, quizzes, reports, infographics and podcast-style Audio Overviews, which can be especially useful for students.

The book doesn’t have to sit in the notebook alone. Gemini Notebook supports sources including Google Docs, PDFs, websites, YouTube videos and EPUB files, allowing you to compare the book with your own notes or other material.

How to add an eligible ebook

First, open the book’s page in Google Play Books and select the Tools badge. Eligible titles will list Gemini Notebook as an available option.

You can also open Gemini Notebook, select Add sources and look for Google Play Books. Choose the book you want to use and check that it appears in the Sources panel before entering your prompt.

Only eligible ebooks obtained through Google Play Books can be added through this integration. Books you uploaded to your Play Books library aren’t supported, although you can upload a PDF or EPUB directly to Gemini Notebook.

Here are 7 fun prompts to try:

1. Create a spoiler-free character guide

Anyone who has returned to a fantasy novel after a break knows the problem: there are 14 characters, three kingdoms and at least two people with nearly identical names.

This prompt asks Gemini to remind you who everyone is without revealing what happens next.

Try the prompt: Create a spoiler-free guide to the characters introduced through Chapter [NUMBER]. For each character, explain who they are, how they are connected to the other characters and what I should remember about them. Do not reveal anything that happens after this chapter.

2. Catch up without starting again

If you haven’t opened a book in several weeks, you may remember the broad plot but not the smaller details you need to continue.

Try the prompt: I have read through Chapter [NUMBER] but haven’t picked up this book in a while. Remind me of the important events, character relationships and unresolved questions up to this point. Do not include spoilers or details from later chapters.

Since the response is generated by AI, there is still a chance it could reveal too much. If avoiding spoilers is especially important, check where its citations lead before reading the entire answer.

3. Start your own book club

Gemini can create a discussion guide that goes beyond asking everyone whether they liked the ending.

Try the prompt: Create 10 book-club questions about this book. Focus on character motivations, central themes, difficult decisions and the ending. Avoid questions that can be answered with a simple fact from the text.

You can make the questions more specific by asking Gemini to concentrate on a particular character, relationship or theme.

4. Turn the book into a podcast

Gemini Notebook’s Audio Overviews turn source material into a podcast-style conversation between AI hosts.

For nonfiction, try the prompt: Create an Audio Overview exploring the author’s central argument, the strongest evidence supporting it and any ideas readers might reasonably question. Keep the discussion conversational and use examples from the book.

For fiction, use: Create an Audio Overview discussing how the main character changes throughout the book. Focus on the decisions that drive that change instead of simply retelling the plot.

5. Apply the author’s advice to your life

A business or self-help book may contain hundreds of pages of advice when you only need help with one specific problem. This prompt asks Gemini to pull out the relevant ideas and organize them into something you can use.

Try the prompt: Using only the principles outlined in this book, help me create a practical plan for [GOAL]. Separate the author’s recommendations from your own suggestions, cite the relevant sections and identify anything I should discuss with a qualified professional.

Be particularly careful when applying information from books about health, mental health, money or the law.

Gemini can help you understand an author’s advice, but neither the book nor its AI-generated interpretation replaces professional guidance.

6. Test what you remember

Instead of rereading your highlights, ask Gemini to find out how much of the book you retained.

Try the prompt: Create a 10-question test evaluating my understanding of this book. Include five multiple-choice questions, three short-answer questions and two questions that require me to apply its ideas. Don’t show me the answers until I submit mine.

You can also tell Gemini which chapters to cover or ask it to increase the difficulty after each round.

7. Explore an untold scene

This is where things get more experimental. Gemini may be able to use its understanding of a novel to imagine a conversation or event that happened outside the original story.

Try the prompt: Write a brief, original scene showing what might have happened between [CHARACTER A] and [CHARACTER B] after [EVENT]. Keep their personalities consistent with the book, but do not copy passages or imitate the author’s writing style. Clearly label the result as unofficial fan fiction.

Gemini may limit or refuse some requests involving copyrighted characters or an author’s distinctive style. Owning an ebook also doesn’t give you the copyright to its characters or story. Treat anything Gemini generates as a personal creative exercise unless you have permission to publish or sell it.

Final thoughts

Sharing a notebook containing an ebook does not give everyone else a free copy of the book. Recipients must purchase the same title through Google Play Books before they can interact with it or view it as a source. According to Google’s sharing documentation, access to artifacts generated from the notebook may also require recipients to own the source ebook.

That restriction is central to Google’s approach. Gemini gets access to the complete text, but only after the reader has purchased an eligible copy. For now, that makes Expert Intelligence an extension of the ebook rather than a replacement for buying it.

Give it a try and let me know what you think in the comments.

More from Tom's Guide

• Perplexity’s new local-first AI runs on your PC — and asks before using the cloud
• ChatGPT can learn your repetitive tasks by watching you — here are 7 prompts to try
• The best way to use ChatGPT for writing isn't writing — 7 prompts I use to make it my creative partner