When a holiday falls on a Friday or Saturday, I’m always overjoyed (especially if it’s my birthday).

And this year, my favorite holiday just happens to be falling on a Saturday. Of course I’m talking about Halloween, which is one of an adult’s perfect excuses to get all dressed up as their favorite characters and meet up with a bunch of like-minded cosplayers (another good excuse is attending Comic-Con). I already have my costume laid out, ready to go, but there’s just one problem: I don’t have somewhere in mind that I can actually go to show off my holiday-themed wear.

Then, like a sign from the heavens, I locked eyes with the Google Maps app and had a lightbulb pop up over my head. “Oh yeah! I can use the “Ask Maps” feature to find something fun to do on Halloween!”

I simply tapped on the AI-powered tool inside Google Maps, asked it to find the best events I should consider going to with a few friends for Halloween and was met with a strong list of recommendations that I’m actually considering attending.

Parties, a parade, a unique show and so much more

There are a few aspects of the Ask Maps feature that I appreciate. Among them is its ability to actually show the events on a local map and provide direct links to where I can get more information about them. Ask Maps’ Halloween celebration suggestions were split up into a bunch of different themes, such as Nightclubs & High-Energy Bashes, Parades, Crawls & Unique Shows, Themed Parties & Rooftop Bashes, Nightlife Cruises & Skyline Sails and Multi-Venue Crawls & Day Markets.

For the first category, there were two events attached to it that caught my attention:

• The Haunted Asylum at CODE Astoria, Oct 31: If you want to stay closer to Queens, head over to Astoria for a full-scale haunted asylum. Expect high-energy club programming, local DJs, cocktails, and an emphasis on heavy costumes. Runs all night long from 8:00 PM to 4:00 AM.
• Fright Night NYC Halloween Party 2026, Oct 31: This massive Brooklyn loft party features a legendary costume competition and an infectious holiday energy. Features a massive $3,000 cash prize costume contest, making it the place to go if your friend group goes all-out on outfits. Includes complimentary rum punch during the first hour of the party from 10:00 PM to 11:00 PM.

The second event category recommended an obvious event that most folks in New York City will be popping out to. And what’s crazy is the fact that I’ve always watched it on TV but never even thought about going to and experiencing it for myself.

Of course, I’m talking about my hometown’s legendary Halloween Parade. Alongside that party option, Ask Maps also brought two other amusing Halloween hangouts worth considering:

• New York City Village Halloween Parade, Oct 31: New York City’s absolute signature Halloween event returns for its 53rd year, packing Sixth Avenue with pure creative madness. The 2026 theme is “Body & Soul”, welcoming highly expressive and boundary-pushing costume ideas. Free to watch along the streets, or you can join the procession for free as long as your entire group is in full costume.
• NYC Halloween Bar Crawl 2026, Oct 31: If your group can’t decide on just one venue, this massive multi-neighborhood bar hop lets you sample the city’s fluidity. Moves seamlessly down Manhattan from a Times Square check-in point all the way into the East Village. Tickets grant access to drink specials, dance floors, and costume contests across numerous participating locations.
• Halloween Soirée Late Show, Oct 31: For an upscale, theatrical alternative to standard clubs, this sultry NoHo show blends dinner-theater aesthetics with holiday spirit. Features live music and bewitching burlesque performances tailored specifically for friend groups. Set in an intimate restaurant environment where sophisticated costumes and glamour are encouraged.

Ask Maps’ two final event recommendations came from its third category — one of them definitely piqued my interest since the promise of parlor games and a free shot sounds great to me:

• Halloween Party at Sour Mouse! All tickets include a FREE SHOT!, Oct 31: Head down to the Lower East Side for a high-energy, adult-only bash combining games and live music. Packed with interactive parlor gams and includes a complimentary shot with paid entry tickets.
• Saints & Sinners Halloween Party, Oct 31: If your friends prefer an upscale rooftop setting, this NoMad gathering pairs spooky vibes with spectacular skyline views. Includes an open bar, passed hor d’oeuvres, a candy station, and retro-themed entertainment. Hosts a competitive costume contest with top prizes, so make sure your group dresses to impress.

The takeaway

Once I saved seven of Ask Maps’ Halloween event suggestions and presented them to my friends, we all decided on hanging out at the Halloween parade for a few hours and ending the night at the Fright Night NYC Halloween Party.

Be like me and tap into Google Maps’ Ask Maps feature if you’re still debating where you want to go to properly enjoy all the Halloween festivities. I’m confident that wherever you stay, Ask Maps will comb every area of it to find the most lively Halloween-themed events that will create long-lasting memories for years to come.

And if you want to let me know your Halloween plans in the comments below, I'd love to hear them.

More from Tom’s Guide

• Google Maps just got a major AI upgrade — these 7 Ask Maps prompts let you order food, find events and more
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This past May, Amazon launched a personalized AI assistant tool primarily meant for shopping called “Alexa for Shopping.” And since its introduction to the Amazon app and site, it has emerged as an extremely helpful tool that can fulfill a wide range of requests.

With a combination of product knowledge, information gathered from across the web and shopping capabilities powered by a user’s preferences, shopping history & past conversations, Alexa for Shopping stands out as one of the best tools sitting inside the Amazon app and site. Being able to tap into that AI assistant to compare product options, find the best deals, track prices, actually purchase a product, etc., has shown why Alexa for Shopping is such an efficient tool.

With the holiday shopping season almost upon us, it’s no surprise that Amazon has sought to make it even better and make the online shopping experience even less of a hassle.

Here are some of the newly added 100+ features that are now available within Alexa for Shopping and the ones I can’t wait to put into action when the time is right.

Alexa for Shopping’s newest capabilities

Amazon announced that Alexa for Shopping has over 100 new capabilities that are geared towards making shopping on Amazon so much easier. Some of the more prominent upgrades worth mentioning are:

• Creating lists: Alexa for Shopping now lets you create, expand and edit your lists and registries. Simply asking it to “Create a new shopping list” or “Add all to my baby registry” works to make new lists and add additional items to them.
• Inquiring about your Amazon subscriptions and benefits: Now you can ask Alexa for Shopping about your Amazon-themed subscriptions, such as “What are my Prime benefits?” and “How much have I saved with Prime this year. I’ll be sure to use this feature to find out more about my Audible, Music Unlimited and Luna Premium subscriptions.
• Manage subscriptions: Now you can tell Alexa for Shopping to “Skip my next delivery” or “Change my delivery to every [number] months to alter your ongoing Amazon subscriptions. I’m sure this applies to Amazon’s recurring delivery service for household, grocery, and personal care items.
• Update instructions for deliveries: If you want to tell Alexa for Shopping to modify your account’s delivery instructions, it’s as easy as telling it “Change the delivery instructions on my account” and “Add delivery instructions on my [city] address.”
• Get to the bottom of billing and payment questions: Telling Alexa for Shopping to “Show my gift card balance,” notifying it that “I have an unrecognized charge on my account” and asking it “Where is my refund?” is now possible—resolving any billing and payment errors you may have is thankfully now a thing with Amazon’s AI shopping assistant.

A month prior, Amazon launched another useful feature that improved Alexa for Shopping. “Update Me When” update has given users personalized notifications that alert them when something new or relevant happens around a new product release. Simply telling it “Update me when a new Kindle Paperwhite launches” sets up a weekly announcement check-in that will only notify users when something major happens on that front. Right now, all of those aforementioned Alexa for Shopping features are available to all US Amazon customers.

Bottom line

Amazon is my go-to online shopping site and I’ve gotten even more out of its massive lineup of items thanks to Alexa for Shopping’s assistance. After inquiring about how much I saved with Prime, Alexa for Shopping put everything into an easily understandable format that proves the AI shopping assistant’s latest upgrades are amazing:

• Over the past 12 months, you’ve saved $30.00 with the Prime Annual Membership. Here’s the breakdown:
• Free delivery: $27.00 saved on delivery fees
• Deals & Savings: $3.00 saved through Prime-exclusive deals, Prime Day, and Whole Foods member savings
• Prime Visa Cashback: $0.00
• Your Prime Annual plan costs $139/year — keep in mind there’s still plenty of value in benefits like Prime Video, Amazon Music Prime, Prime Gaming, and more that aren’t always reflected in your figures.

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Nvidia CEO Jensen Huang may have been the target of a Chinese intelligence operation, and according to a bombshell new report, President Donald Trump knew about it for nearly a year.

A New York Times investigation published Thursday reveals that American intelligence officials concluded a Chinese businesswoman with close ties to Huang was passing information to Beijing. The woman, identified as Alice Huang, was also an executive at a company already under investigation for allegedly helping Chinese businesses obtain restricted Nvidia AI chips.

Even more surprising, Trump was reportedly briefed on the findings about a year ago but took no action, while Jensen Huang himself was never warned that someone in his business circle was suspected of working for Chinese intelligence.

"We often receive updates from the U.S. government regarding parties and entities of concern and always act accordingly," a spokesperson for Nvidia tells Tom's Guide. "The diversion allegations against this regional cloud were thoroughly investigated and debunked last year."

 The allegations arrive at a particularly sensitive moment for Nvidia, which supplies much of the computing power behind the world's leading AI systems, including ChatGPT and other popular chatbots.

How a suspected Chinese intelligence asset got close to Nvidia

At the center of the investigation is Alice Huang, also known as Huang Le, a Chinese businesswoman and senior executive at Megaspeed, a Singapore-based data center company.

According to the Times, U.S. intelligence agencies were already monitoring Huang because they feared Megaspeed was helping Chinese companies access advanced Nvidia chips despite American export restrictions.

During that surveillance, officials reportedly discovered that she had developed a close relationship with Jensen Huang. The two were seen together during visits to Taiwan, including appearances in 2024 and 2025.

Intelligence officials eventually concluded that Alice Huang was providing information to Beijing, raising concerns that the Nvidia CEO himself could be a target.

"Megaspeed has been no different than many other regional cloud customers. Jensen’s interactions with Ms. Huang are not unusual or unexpected. Meetings with customers are part of a CEO's job; Jensen talks with thousands of customer executives every year," a spokesperson for Nvidia tells Tom's Guide.

No evidence shows that Jensen Huang knowingly participated in any intelligence operation. In fact, U.S. officials reportedly believed he was unaware of the woman's suspected activities.

Nvidia has pushed back against suggestions that the relationship was unusual, explaining that Huang regularly meets executives from companies that purchase its technology.

"Our regional cloud customers receive ordinary business information — not sensitive NVIDIA trade secrets—and zero information relevant to national security," the Nvidia spokesperson tells Tom's Guide. 

Trump was reportedly briefed, but Jensen Huang wasn't

Arguably the most surprising detail in the Times investigation is what reportedly happened after U.S. intelligence officials identified the potential threat.

Trump was briefed on the findings about a year ago, but the administration did not take action against the suspected operation, according to the report.

The Times links that decision to the administration's reluctance to disrupt Nvidia's chip sales or further complicate trade negotiations with China, although the precise reasoning behind the decision remains unclear.

Meanwhile, Jensen Huang reportedly never received what intelligence officials call a defensive briefing, a warning sometimes given to Americans who may be targeted by foreign intelligence services.

That doesn't necessarily mean officials ignored the threat. Alerting Jensen Huang could have revealed that Alice Huang was under surveillance, potentially jeopardizing the investigation. But this raises concerns about how the U.S. government handles security issues involving executives whose companies play an enormous role in the American economy.

Those concerns extend beyond Nvidia's business dealings. Jensen Huang has become an influential voice in Washington's AI policy discussions and has developed a close relationship with Trump.

For intelligence agencies, someone with access to a technology executive involved in those conversations could potentially learn valuable information without ever getting near classified documents.

Why Nvidia's AI chips are at the center of the controversy

The suspected intelligence operation is only one part of a much larger dispute over who gets access to the world's most powerful AI technology. Nvidia makes the advanced processors used to train and run many of today's leading AI models. These chips are essential infrastructure for companies developing increasingly capable AI systems.

The U.S. has restricted exports of certain advanced AI chips to China over national security concerns, particularly the possibility that the technology could strengthen Beijing's military and intelligence capabilities.

But enforcing those restrictions is complicated since Chinese companies can potentially gain access to Nvidia-powered computing resources through data centers located in other countries, without necessarily taking physical possession of the chips.

That's where Megaspeed enters the picture. The Singapore-based company has purchased large quantities of Nvidia technology, and U.S. authorities have been investigating whether its operations helped Chinese customers circumvent American export controls.

According to the Times, the investigation intensified after officials inspecting a data center in Malaysia found Nvidia equipment that was still boxed rather than installed.

The discovery raised questions about where the equipment was ultimately intended to go. Nvidia has denied finding evidence that Megaspeed was illegally supplying chips to China, and the company says it complies with applicable export regulations. Megaspeed has also said it is investigating the allegations.

What Nvidia and China are saying

Nvidia disputes any suggestion that Jensen Huang's interactions with Alice Huang were improper.

In a statement reported by Tom's Hardware, Nvidia said Huang speaks with thousands of customer executives every year and that its regional cloud customers receive ordinary business information, not sensitive company secrets or information relevant to national security.

The company also said it expects U.S. authorities to alert it when a person or organization poses a security threat.

"The PRC government is not seeking NVIDIA products from regional clouds. Instead, the PRC government blocked U.S. AI chips, protecting its own industry and resulting in the largest write-offs in U.S. tech history," the spokesperson for Nvidia tells Tom's Guide.

Megaspeed has reportedly retained outside legal counsel to investigate the allegations, while the Chinese Embassy in Washington has rejected the claims as unfounded.

Importantly, no public evidence establishes that Jensen Huang passed sensitive information to Chinese intelligence, knew about Alice Huang's alleged activities or violated U.S. export restrictions.

What this could mean for AI

For anyone using ChatGPT, Gemini or other AI tools, this story isn't about an immediate threat to personal data or a reason to stop using AI. But it offers a rare look at the geopolitical tensions surrounding the hardware that makes those tools possible.

The technology behind today's AI boom depends heavily on a relatively small number of companies, with Nvidia occupying a particularly influential position. And while the investigation doesn't establish that Chinese intelligence obtained sensitive information from Nvidia, it highlights just how complicated the relationship between business, national security and AI has become.

"Building American AI infrastructure worldwide has been a core U.S. policy goal of every Administration.  Attacking American industry for honoring longstanding U.S. law and policy undercuts national security," the Nvidia spokesperson tells Tom's Guide.

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• Microsoft just offered 60,000 workers a way out as AI spending soars — here's what it could mean for your job
• ChatGPT has a clever new way to fight back against election deepfakes — I tried it and it actually works

With midterm elections just days away, you might be tempted to ask ChatGPT, Gemini, or Perplexity about a candidate’s record before heading to the polls. But a new study suggests you should think twice before trusting the answer, even when the chatbot provides sources to back it up.

A report from AI search analytics company Searchable found that roughly one in 12 answers about local political issues contradicted official government data. Of the 7,449 answers researchers evaluated, 610 were false, an 8.2% error rate.

The research examined four popular AI tools: ChatGPT, Gemini, Google AI Mode, and Perplexity. The questions covered issues voters regularly consider when evaluating politicians, including crime, housing costs, employment, education and healthcare.

But the most surprising finding wasn’t necessarily how often the chatbots got things wrong. It was that they sometimes produced incorrect answers despite consulting reliable government sources.

Perplexity had the highest error rate

The researchers found significant differences in how the four AI tools performed.

Perplexity produced false answers in 22.6% of the tested responses, compared with 6.2% for Gemini and 4.4% for ChatGPT. Google AI Mode had the lowest error rate at 2.9%.

In other words, more than one in five Perplexity answers evaluated in the study contradicted official government data.

Errors also varied by subject. Questions about housing and the cost of living produced the most false answers overall, at 11.9%, followed by energy and environmental issues at 10.9% and schools at 10.1%.

Crime and public safety questions had the lowest aggregate error rate, at 4.7%.

These figures don’t represent each chatbot’s correctness across all political questions. The study focused on 106 underlying questions across five metropolitan areas and their respective states, including questions deliberately designed around misleading or previously debunked claims.

AI had access to the right information

One of the more concerning findings is that incorrect answers weren’t necessarily the result of chatbots consulting unreliable websites.

Of the 43,079 webpages the AI systems accessed during the study, approximately 62% came from federal, state, or local government websites.

ChatGPT was particularly thorough when gathering information. Researchers found that it consulted an average of 31 webpages from 10 websites before answering a single question.

One example shown in the report involves Georgia’s electricity supply, ChatGPT reportedly ran 19 searches and accessed 154 pages across 52 websites before responding.

That highlights a problem with relying on AI to interpret information for you. A chatbot can search extensively, access authoritative sources, and still make an error when pulling the information together.

As Searchable CEO and co-founder Chris Donnelly explained, “Often the right answer was sitting in the sources the chatbot linked to; it just didn’t make it through to the voter.”

The concern becomes especially relevant when an answer contains a statistic that could influence how someone evaluates an elected official’s record.

How you ask AI a question can make things worse

The study also examined what happens when questions contain a misleading assumption.

For example, asking a chatbot why crime increased in a particular area already assumes crime went up, even if the official statistics show otherwise.

According to Searchable’s findings shared with Tom’s Guide, questions containing false assumptions were more than four times as likely to produce a false answer.

AI doesn’t always challenge a question's premise. Sometimes it accepts that premise and generates an explanation around it.

This could be particularly problematic for people researching political claims they’ve encountered on social media, in campaign advertisements, or during debates.

And Americans are already using AI for that purpose. An October survey published by George Washington University’s Graduate School of Political Management found that one in five likely midterm voters had asked AI about elections or politics and a quarter reported using AI every day.

Interestingly, the same survey found that just 1% considered AI their most trusted source for information about elections and candidates.

How to check AI answers before Election Day

Obviously, none of this means you need to stop using ChatGPT, Gemini, or other AI tools to research political issues. They can still help explain complicated policies, summarize information, or find relevant sources.

But take a few precautions before accepting an answer as fact:

• Ask for the source. If a chatbot gives you a statistic about unemployment, crime, or housing prices, ask it to identify the government agency responsible for publishing that information. Then open the source yourself.
• Watch how you phrase questions. Instead of asking why crime increased in your city, ask whether crime increased or decreased over a specific period. Neutral questions allow the chatbot to challenge an incorrect assumption.
• Check the dates. Financial indicators, crime statistics, and housing data change regularly. Make sure the information applies to the period you’re researching, rather than depending on outdated figures.
• Don’t assume citations guarantee accuracy. A link to a legitimate government website doesn’t necessarily mean the chatbot interpreted its contents correctly. Check whether the number actually appears in the linked source and whether the context corresponds to the AI’s explanation.
• Verify election logistics separately. For polling locations, registration requirements, voting hours, and ballot information, go directly to your state or local election office rather than relying on an AI-generated summary.

Bottom line

AI chatbots have made finding information easier, but this study shows why finding information and interpreting it correctly are two different things.

Searchable tested its systems in September and October 2026, using anonymized logged-in accounts and repeated questions across fresh sessions. Researchers checked the answers against official government data, and two graders had to agree before they classified an answer as false.

The study isn’t a comprehensive measure of chatbot reliability, but it does illustrate a weakness worth understanding before the November 3 midterm elections.

As Donnelly put it, “Treat a chatbot’s answer as a starting point, not a verdict.”

With so much information available in seconds, spending an extra minute checking a source could be the most useful part of your research

More from Tom’s Guide

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• Microsoft just offered 60,000 workers a way out as AI spending soars — here's what it could mean for your job
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I’ll admit to not being the most fashionable guy on the planet.

My closet is dominated by graphic tees, way too many oversized hoodies (gotta stay ready for these metro Arctic temperatures in the winter!) and random dad hats that would be better off in my Mom’s closet since she loves wearing them so much. Even with all the geeky wear that I have that’s more appropriate for a New York Comic-Con walkthrough, I do have a set of button-ups, crispy jeans and sneakers that are perfect for a night out on the town.

I’ve had a few wins when it was time to don the perfect top and bottom fashion combo. But I’ve had far too many fashion misses, due to a combination of certain colors not going together well and me just not having the fashion acumen needed to realize “nah…this ain’t it.”

A styling iPhone app powered by AI called Megu: SI Closet & Planner was recently brought to my attention. And after putting it through its paces, it convinced me to make it a vital part of any future decisions tied to my choices in outfits.

Taking pics, arranging my fits and choosing my three-day fashion rollout

Setting up Megu is pretty simple — you set up your style profile by picking among several choices, giving the app your length & width, adding custom style rules and taking a picture of yourself for try-on pics that the app generates. Then you do the process of taking pictures of which tops and bottoms you want to see matched together, which makes Megu save a highly detailed version of that image for future styling reference.

After building out my digital closet on the app, it analyzed it and labeled me as “The Denim Devotee” (a title I’m very proud of now that I’ve been given it). I made sure to add as many button-up shirts, jeans, and sneakers as possible to give Megu plenty of clothing options to work with when it came time to generate the best fits possible. Since I was planning to step out of the house for three days' worth of work and post-work hangouts, I delegated my styling responsibilities to Megu to see if it could rise to the occasion.

Before I took a look at Megu’s stylized choices, I hopped over to the “Closet” tab to take a look at the “Wishlist” since I was so curious about what it was.

Turns out it’s a place where you save the cards that represent the fits you like the best and take a look at the recommended clothing options that Megu brings from a wealth of clothing retailers (domestically and internationally). I was pleasantly surprised by this part of the Megu app — it features a bevy of tops and bottoms that fit my fashion profile, plus a direct link to every item.

Even clicking over to the “Today” tab and tapping on “For you” brings up a bunch of additional clothes worth adding to your wishlist. I peeped a beige collared cotton coat that went from $795 to $493 since it was on sale (which I liked, but that price is a little too high for my modest budget). At least it looked good on me when I digitally tried it on.

Megu laid out the sorts of casual outfits that I would have never thought to put together on my own.

I’m so used to having everything matching from a color standpoint, such as a dark blue top, dark blue jeans and my dark blue PUMA Suede Classic sneakers. Megu’s “The fresh collar” setup stood out to me as one of its finest fashion layouts, as it showcased me in an AI-generated photo with my light-blue button-up, grey jeans and my Navy Blue Old Skool Vans sneakers.

The additional two outfits Megu laid out for me were equally impressive, which inspired me to actually don them for myself and see just how good they look in the mirror (no surprise that they look as great as I’d figured they’d be).

Final thoughts

The Megu app is pretty much like having a personal stylist in your back pocket that can be called upon at any moment to make sure you look right for work, a hangout, a date or whatever other function you can think of. Keep in mind that you’ll need to set up a weekly, monthly or yearly subscription to take advantage of its best features (I got set up with a month-long “Max Membership” plan).

I might just keep it around for a lot longer since I need help diversifying my fits and future clothing purchases anyway. I recommend putting the Megu AI styling app to the test to see if it can dress you up nicely and fill out your closet with some nice pieces you may not have even known about.

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Most of us don't think about how much we rely on the internet until it stops working. With the recent seasonal storms, I've noticed it more than I would like. When the power gets knocked out, I can't easily find answers to questions like, "How long will food stay fresh in the fridge without power?" or even "What's the phone number for the power company?"

So when I stumbled on a free chatbot called Survival LLM that doesn't require the internet to work, I was very curious to try it. Unlike ChatGPT, Gemini or Claude, which typically rely on cloud-based servers, this chatbot is designed to work entirely on your computer, even when you're completely offline.

Users just need to download the AI and its reference library ahead of time to have access to information about everything from food safety and first aid to home repairs and emergency preparedness without needing an internet connection.

And while there's a catch when it comes to accuracy, I can see why having something like this available before an emergency could be useful.

An AI chatbot that doesn't need the internet

Survival LLM is a free, open-source AI assistant available for Windows PCs and Macs. Once you've installed it and downloaded the necessary files, you can disconnect from the internet and continue asking questions.

Instead of sending requests to a remote server, it runs an AI model directly on your computer. It also searches a library of reference material stored locally, including information from Wikipedia, MedlinePlus, FEMA, the CDC and iFixit.

The full library contains roughly 1.5 million articles, including around 930,000 Wikipedia entries. From my experience, it offered a vast look at a variety of topics from keeping food safe during a blackout (exactly what I needed to know!) to fixing household equipment and treating minor burns — all without needing to open a browser.

One feature I particularly liked is that the chatbot doesn't just give you an answer. It also identifies the articles it used and lets you read the relevant passages yourself. I especially appreciate that source information when it comes to safety.

The software also lets you add your own documents, including PDFs, Word files and notes. You could upload your generator's instruction manual, emergency contact information or a family preparedness plan and have the assistant search those documents alongside its existing library.

According to the developer's notes on the site, your questions and uploaded files remain on your computer.

There's one important catch

As useful as an offline chatbot sounds, I wouldn't rely on AI alone for medical advice or life-or-death decisions. The developer is unusually transparent about this limitation.

In its own tests involving 22 emergency and first-aid questions, the AI models produced noticeably different results depending on how much memory the computer had available.

The largest models answered 21 of the 22 questions correctly, according to the developer. The model recommended for computers with 16GB to 31GB of RAM got just 14 right.

Those results come from the developer's tests on an earlier version of the reference library, not independent testing. They also show why having access to the original source material is so important.

Survival LLM's ability to display its sources is a useful safeguard, but it doesn't guarantee that the model has interpreted them correctly.

How to download Survival LLM

You can download Survival LLM for free from its official website. It's compatible with Apple Silicon Macs running macOS 14 or newer and 64-bit Windows 10 or 11 PCs.

Getting started requires an internet connection, since you'll need to download both the AI model and its reference library. You may get an "Are you sure you want to download this?" since it isn't an app from Google Play or Apple App Store. You'll need to determine how safe you feel with third party downloads.

But if you decide to try it, it's important to note that the smaller reference library is approximately 1.3GB to download, while the full version is around 9GB. You'll also need to download a local AI model, which can range from roughly 6GB to 80GB depending on your computer's hardware.

The developer estimates that initial setup can take anywhere from 20 minutes to two and a half hours, depending on your internet connection and system. I walked away while it was downloading, but it was approximately 36 minutes on my Lenovo computer running Windows 11.

Computers with less memory may be limited to searching the reference library rather than using the full AI experience. In particular, the developer doesn't recommend an AI model for systems with only 8GB of RAM.

There's also a practical limitation worth remembering. If your laptop runs out of battery during a blackout, an offline chatbot won't do much good. Keeping your computer charged or having a portable power station would still be important.

My takeaway

I like the idea behind Survival LLM because it addresses the problem of being completely disconnected. Having a searchable collection of emergency guides, medical references and practical instructions stored on your computer could be genuinely useful, particularly during extended internet outages or when traveling somewhere with unreliable service. I can already see myself using this option on road trips.

Just be warned that you don't want to confuse having an offline AI assistant with a real emergency expert. The developer's own accuracy results make that distinction clear.

For me, I like having what feels like an encyclopedia of information on my computer and at my fingertips. And since the software is free, it could be worth exploring as one more addition to a household emergency preparedness plan, provided you download it in advance and double-check any safety-critical advice against its original sources.

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• I tested ChatGPT vs. Grok with 5 questions boomers actually ask — and the winner surprised me
• Microsoft just offered 60,000 workers a way out as AI spending soars — here's what it could mean for your job
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Google DeepMind, the tech giant’s primary AI research and development laboratory, has played a major part in the development of Genie, a world model that’s capable of generating interactive virtual worlds.

The original Genie model launched back in March 2024 and was initially powerful enough to generate two-dimensional environments. Then in December 2024, Genie 2 came out and added the ability to generate three-dimensional worlds. Around August 2025, Genie 3 made its debut and gave users the ability to generate and modify both types of interactive worlds in real time.

This month marks the launch of Genie 4 in research preview mode, which is promised by Google to be able to generate the most photorealistic and interactive worlds to date. What makes it stand out from its predecessors is how it lets users type out prompts mid-simulation to change the scene. Also, Genie 4 can generate real-time audio that matches and syncs up with the simulated world that’s been created, which includes music, ambient sounds and interactive dialogue.

With Genie 4’s expanded capabilities tied to its interactive worlds, it could have a major impact on the way video games are created by its talented developer community.

Real-time, interactive world creation and so much more

Google has already explained how game developers have been utilizing Genie 4:

“Game developers and creative technologists are testing Genie 4 to go from an initial idea to an explorable prototype in seconds, testing visual styles, material aesthetics, and interactive mechanics through natural language prompts before writing a single line of engine code.”

Genie 4’s biggest promise is giving users the ability to generate the type of AI-generated worlds that they can actively experience, which could go a long way toward game developers creating instant mockups of what they're envisioning. And it could lead to a future where the most creative game developers could use Genie 4 to turn their fantastical ideas into playable prototypes in just a few seconds.

I could envision a world where Genie 4’s mass availability leads to game developers experimenting with their environmental and character concepts through a simple prompt instead of having to create them themselves. For indie studios that don’t have the finances to create all those resources on their own, Genie 4 could give them the freedom to bring their standout ideas to life, tinkering with it and taking everything they learn from it to apply their development expertise to turning those ideas into commercial video game releases.

I could also see Genie 4 leading to game development cycles getting a bit shorter, as game developers can perform faster prototyping tasks just by prompting. For example, a developer could test unusual and out-of-the-box mechanics in Genie 4 to see how they interact with the world they’ve generated at large before fully investing in developing them for their game’s world. Experimenting with character interactions & dialogue and creating dynamic visual & audio scenes as proofs of concept could also be a huge boon to game makers if Genie 4’s capabilities expand to an even more impressive level.

Currently, Genie 4 has begun rolling out as a research preview tool specifically catered to professionals within the creative, journalism, education, gaming and engineering industries. Over time, it will become available for Google AI Ultra subscribers through Project Genie. Early access will come to users through the Gemini API and Google AI Studio tools. General availability for Genie 4 has not been announced yet, but you can sign up for access through its waitlist.

The takeaway

Game development engines such as Unreal Engine and Unity provide game makers with the tools they need to build and ship the games you regularly play.

If Genie 4’s power to quickly generate and modify interactive worlds takes off among the game development community, I could see a far-flung future where they use traditional game engines and Genie 4 in conjunction with each other to bring their playable concepts to life.

Generating and adapting interactive experiences on demand with Genie 4 sounds great. But it’ll need a lot more problems solved before it hopes to become a mainstream video game development tool, such as figuring out the best ways to use Genie 4 to produce consistency, control and performance for its world’s mechanics, characters and NPC interactions.

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Hackers have reportedly broken into 25 servers across four countries, including systems connected to a U.S. government-affiliated organization. Security researchers also discovered evidence that AI tools may have played a role in the attack.

According to a new report from Dream Research, published Monday, the attackers exploited critical vulnerabilities in PHP, a programming language used by millions of websites, before using another security flaw to gain full control of vulnerable systems.

The attacks targeted servers in the United States, Japan, Taiwan and South Korea. Researchers found evidence pointing to a possible Chinese connection, although they have not identified the attackers or confirmed any government involvement.

What makes the discovery particularly concerning is how far the attackers managed to get. In one U.S. government-affiliated environment, they moved beyond the initial breach and gained access to internal network information, employee account listings and authentication credentials.

And while AI's exact role remains unclear, researchers found several tools in the attacker's environment that raise questions about how AI could be accelerating cyberattacks.

Hackers turned one security flaw into a much bigger attack

The attack started with two critical security flaws, known collectively as PHP2Shell, that were publicly disclosed on October 21.

PHP is used behind the scenes by millions of websites, including WordPress sites and online services. The two vulnerabilities, tracked as CVE-2026-109618 and CVE-2026-109619, can let hackers run malicious commands on vulnerable servers.

But the attackers didn't stop there. They combined those flaws with another Linux vulnerability called Fragnesia, allowing them to take full control of certain firewall systems without needing a username or password.

According to a Dream Research report shared with Tom's Guide, the entire process could take less than 15 minutes.

The hackers started by scanning roughly 19,000 internet-facing firewalls before narrowing their targets to 240 potentially vulnerable systems. From there, they used automated attacks to breach 24 firewalls and an additional internal management server, bringing the total to 25.

Researchers also found that the hackers had installed malicious web-based tools on many of the compromised systems, giving them a potential way back in even after the initial attack.

The attackers reached a U.S. government-linked network

Arguably, among one of the more concerning discoveries involved three compromised servers linked to a U.S. government-affiliated organization.

After breaking into an internet-facing firewall, the hackers gained access to details about the organization's internal network, including its VPN, login systems and other servers.

They then worked their way deeper into the network, compromising a central firewall management server and stealing an account password. They also obtained a list of users and groups within the organization.

Researchers found evidence that the attackers tried to guess employee passwords, create unauthorized accounts and access additional login credentials, although it's unclear whether those attempts worked.

Dream Research also warned that the hackers may still have had access to some systems when the report was published, but that hasn't been independently confirmed.

The security firm hasn't named the firewall manufacturer or disclosed which software versions were affected, but says it has notified the vendor.

AI tools were discovered in the attacker's environment

Researchers also found signs that the attackers may have used AI. Their tools included Anthropic's Claude Code and an AI-powered security platform called aiscan, configured to work with the Chinese AI models DeepSeek and Kimi.

They also uncovered roughly 40 custom scripts whose consistent formatting and comments suggested some may have been written with AI assistance.

However, Dream Research cautioned that there's no direct evidence AI was used to create the exploits or carry out the attacks. The tools may have been present without playing a role in the breaches.

Still, the findings raise concerns about how hackers could use the same AI coding assistants that developers rely on to write code and troubleshoot problems.

Researchers also found clues suggesting a possible Chinese connection, including Chinese-language prompts, systems set to China's time zone and targets concentrated in the U.S. and East Asia. None of this, however, confirms who was behind the attacks.

Final thoughts

PHP2Shell doesn't directly affect your phone or laptop, but it could put information stored by websites and online services at risk. If attackers compromise those servers, they may gain access to passwords, sensitive data or internal systems.

Dream Research found no evidence that ordinary consumers' personal information was stolen in this campaign. However, the vulnerabilities are already being exploited beyond these 25 servers.

Amazon Web Services detected exploitation attempts as early as October 17, four days before the flaws were publicly disclosed. Sophos initially reported successful exploitation but later corrected its findings, saying it had observed scanning and a small number of failed attacks, with no confirmed breaches in its customer environments.

If you run a WordPress site or online store, check with your hosting provider to make sure PHP is patched. Updating WordPress plugins alone won't necessarily fix the problem. Administrators should also check for signs of compromise, since installing a patch won't remove an attacker who's already gained access.

For everyone else, using unique passwords, enabling two-factor authentication and watching for suspicious login alerts remain sensible precautions.

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Imagine driving across the country, enjoying a road trip and minding your own business, only to get pulled over because AI decided your route looked suspicious. That's what one Virginia woman says happened to her, and privacy advocates warn that similar encounters could become more common.

According to a new report released on Monday from the American Civil Liberties Union, police are using automated license plate readers and AI-powered analysis more often to identify drivers based on their travel patterns, even when there's no evidence they've committed a crime.

The technology can piece together where a vehicle has traveled, how often it visits certain locations and whether its movements fit patterns investigators consider suspicious.

While license plate readers have been used for years to identify stolen vehicles and help solve crimes, AI is making it possible to analyze much larger collections of driving data. The concern is that an otherwise ordinary trip could become grounds for additional police scrutiny.

A road trip that raised an AI red flag

In September 2025, Grace Knowles was driving from northern Virginia to Florida when she was pulled over by an officer who claimed she'd spent too much time in the left lane.

But according to her account to the ACLU, the officer seemed more interested in her travel history than her driving. He asked where she'd been, why she was traveling and whether she could prove she'd recently visited New Orleans. Knowles eventually showed him a pamphlet from a museum she'd visited.

The officer then identified himself as an FBI special agent investigating human and drug trafficking. He told Knowles that her license plate had been flagged because of suspicious travel patterns.

He even invited her to look at the computer in his vehicle. On the screen was a map showing places she'd traveled, with photographs of her license plate attached to individual locations. Knowles said the officer had questioned her visit to New Orleans because the system hadn't recorded her car there.

That's one of the problems with relying on AI technology for this type of work. Police can see where cameras have spotted a car, but not necessarily everywhere it's been. And when there are gaps in the data, investigators may draw the wrong conclusions.

The ACLU hasn't identified the software used during Knowles' stop, so it's unclear exactly how her driving patterns were flagged.

How AI can track your driving habits

Automated license plate readers, or ALPRs, are cameras installed along roads, highways and intersections. Some are mounted on police cars. Every time a vehicle passes, the camera records its license plate, location and time, creating a record that police can use to track where it's been.

Companies like Flock Safety supply these systems to law enforcement, and the technology is becoming more sophisticated. An August investigation by WIRED found that Flock's newer AI-powered software can spot recurring travel patterns, identify cars that frequently appear together and connect license plate records with other investigative information.

That means police aren't limited to searching for cars already linked to a crime. They can also look for unusual driving patterns and use those findings to identify people they want to investigate.

Someone who regularly drives between two cities, for example, could attract attention simply because of their route, even if they're just commuting to work or visiting family.

A Texas driver challenged his stop — and won

Knowles isn't the only driver who's been pulled over after surveillance technology flagged a trip as suspicious. On September 28, a federal jury found that Bexar County, Texas, had violated the constitutional rights of Alek Schott, who was stopped while driving home from a business trip in March 2022.

According to the Institute for Justice, which represented Schott, his drive from the Houston area toward the border and back had caught the attention of a police surveillance system.

A deputy pulled him over, claiming he'd drifted out of his lane. But dashcam footage showed otherwise. Schott was questioned, detained and had his truck searched, even though police ultimately found nothing illegal.

The jury awarded him $76 (one dollar for every minute he was detained). The jury found that the county's traffic stop practices had violated Schott's rights. His case shows how quickly a trip flagged as suspicious can turn into a police encounter, even when the driver hasn't done anything wrong.

Can you stop AI from tracking your car?

Unfortunately, there's no easy way to opt out of this kind of surveillance. Roadside cameras capture license plates as cars pass, so turning off your phone's location services or using a VPN won't make a difference.

Drivers also have little control over what happens to that information once it's collected. How long police can keep license plate records and who they can share them with depends on where you live.

The ACLU has challenged the use of these systems, warning that tracking a car's movements over time can reveal surprisingly personal details about someone's life.

If you're curious whether police in your area use license plate cameras, the Electronic Frontier Foundation's Atlas of Surveillance lets you search for surveillance technology used by local law enforcement. Some departments also publish their policies on how long they store the data and who can access it, although not every agency or technology is included in the database.

The takeaway

AI is giving police a much clearer picture of where people drive, even when they're not suspected of a crime. Instead of looking for a specific vehicle, investigators can now search months or even years of license plate records to spot travel patterns they consider suspicious.

Police say these tools help them investigate crimes, but privacy advocates worry about what happens when an innocent driver's routine starts to look suspicious to an algorithm.

As the ACLU points out, turning off your phone's location services won't stop roadside cameras from tracking your car. And depending on how police interpret that information, an ordinary drive could be enough to get you pulled over.

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Last year and this year have exposed me to the many ways AI tools can boost my productivity and help me get more done in as little time as possible.

Laying out the finer points of a lengthy document, building out a schedule for all types of routines and finding the best approach to my to-do list are just a few of the ways the likes of ChatGPT and Gemini have assisted me with my everyday tasks. But I have noticed instances where it's added more time to tasks that were meant to be a lot quicker to complete. One of them even happened to me, while I’ve observed some of them happening to other people in my life who utilize AI as a crucial part of their workflow.

Just by taking a look at the McKinsey Technology Trends Outlook 2026, you can see proof of AI being a hindrance to some professionals. A standout statistic from that report states that “Our research finds that in 30 percent of companies, productivity fell after teams began using agentic AI tools.”

With all that in mind, here are three signs that you or someone you know may be suffering from AI productivity drag.

1. You’re spending more time fixing the mistakes made by AI instead of doing the work yourself first

It’s easy to prompt AI tools to help you generate reports, emails and summaries in a matter of seconds.

But we all know chatbots have a bad habit of getting things wrong and outputting inaccurate and even repetitive information. Instead of actually spending all that extra time fixing all the errors AI may have included in the first draft of a report you told it to write up, that time could have been better served writing up that first draft yourself and asking AI for the best ways to improve it.

You’re adding more time to your tasks if you find yourself doing more editing and fact-checking for your AI tool instead of writing up whatever’s required of you and asking AI to find the best sources you need to back up your written claims.

Here’s a prompt worth keeping in your back pocket for a situation such as this one:

I want you to help me complete this task with as little rework as possible.

My task: [describe the task]

My requirements: [list the key requirements]

My source material: [paste relevant information or provide the text]

Before producing your answer:

1. Identify any missing information that could materially affect the result.

2. Follow my requirements exactly and prioritize accuracy over speed or creativity.

3. Do not invent facts, figures, quotes or sources. Flag anything you cannot verify.

4. Check your draft against every requirement before presenting it.

5. Give me a polished, ready-to-use result rather than a rough first draft.

If something is unclear, ask only the essential questions before proceeding. Otherwise, complete the task and briefly flag anything I should double-check.

2. You’re constantly switching between AI tools instead of focusing on he task at hand

It’s easy to get caught up in the act of using a chatbot for a particular job.

You may find yourself using one to map out a business plan for you, relying on another one to critique it, a third to make appropriate changes to it and then coming back to the first one to ask if those changes are worth implementing or getting rid of altogether. Making so many switches between chatbots leads to a cycle where you add more time to your workflow by working with multiple AI tools instead of just settling on the one that works for the situation at hand. Context switching can definitely turn into a time sink before you know it.

For example, using Perplexity as your only AI tool for cited research and internet deep dives should cut out all of that context switching for that task.

The following prompt can aid you in getting the most out of a single chatbot:

Act as my single AI assistant for this task. Help me finish it without unnecessary tools, repeated prompts or endless comparisons.

My goal: [describe what you need to accomplish]

My deadline: [provide a deadline]

My available tools: [list the tools you already have]

Please:

1. Choose the simplest approach that is likely to produce a good result.

2. Complete as much of the task as you can in this conversation.

3. Make reasonable assumptions when the stakes are low, and state them briefly.

4. Ask follow-up questions only when the answer would materially change the result.

5. Do not recommend another AI tool unless it offers a specific, meaningful advantage for this task.

6. Before finishing, check whether the result meets my goal and tell me only what still needs attention.

Optimize for a useful finished result, not the number of tools used or the number of steps taken.

3. You’re letting AI manage and optimize your to-do list instead of actually completing what’s on it

It’s easy to come up with a to-do list and have AI organize it for you.

That process can result in AI generating an easy-to-follow schedule, a list of prioritized tasks worth following first and breaking up your goals into more manageable steps. But it’s equally easy to fall into the trap of constantly optimizing everything laid out by AI to break everything down into an even simpler game plan or workflow. Repeatedly using AI to reorganize and refine your to-do list can lead to a vicious cycle where you don’t actually go into action to complete your plans.

AI can help you do some proper planning, but you’ll need to actually implement those plans before you get stuck in the habit of analyzing and breaking them down into easier steps.

This prompt should go a long way toward setting up an actionable plan that doesn’t need all that extra optimizing and refining:

Act as my practical productivity coach. Your job is to help me make progress, not create the perfect productivity system.

Here is what I need to accomplish today:

[list your tasks]

My available time: [number of minutes or hours]

My most important deadline: [deadline]

My current biggest obstacle: [describe it, if applicable]

Please:

1. Identify the three most important tasks based on urgency, impact and my deadline.

2. Break the highest-priority task into small, concrete actions.

3. Tell me which action to take first, making it something I can begin in five minutes or less.

4. Create a realistic plan using my available time, including reasonable breaks where needed.

5. Keep the plan simple. Do not introduce new apps, elaborate systems or extra planning exercises.

6. If I ask to reorganize the plan again, first help me determine whether anything meaningful has changed.

End with one specific action I can take right now. Help me start rather than keep planning.

The takeaway

Using AI can deliver moments of productivity boosts, but it can also lead to situations where you're adding time to the tasks that you originally wanted to save time on.

Constantly fixing the errors spotted in AI-generated reports, switching between tools for a single job and endlessly optimizing your to-do list are three prominent signs that point to AI actually slowing you down instead of speeding up your work process.

A good rule to follow when using AI while working is this: give a chatbot a clearly defined job, set limits on how much time you spend refining its output and cut off the additional work you give it if it no longer saves you time.

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Microsoft is offering roughly 60,000 employees a chance to leave the company, and the timing is hard to ignore. As the tech giant pours billions into AI, it's giving more than a quarter of its workforce the option to take a buyout.

But while it's easy to blame AI, it's important to understand that it hasn't necessarily replaced these Microsoft employees. The buyout offers are voluntary, and the company hasn't disclosed how many people it expects to leave or whether AI played a direct role in the decision.

Still, the announcement raises an uncomfortable question for anyone watching AI reshape the workplace. If one of the world's biggest AI investors is rethinking its workforce, what could that mean for your job?

New research suggests the changes may already be underway, although not necessarily in the way people expect. Instead of widespread layoffs, some of the earliest signs are showing up in hiring, particularly among younger workers.

What's happening at Microsoft?

On October 26, Microsoft announced a Voluntary Exit Offer for eligible employees in the United States, Canada, India and the United Kingdom.

The program allows employees in participating teams at level 70 and below to leave with financial support and career-planning resources. Not every division is included, and participation is optional.

According to CRN, Microsoft confirmed that approximately 60,000 employees qualify, representing about 27% of its 223,000-person global workforce.

In her announcement, Microsoft's chief people officer Amy Coleman said the program would give participating organizations more flexibility to adapt their workforces to changing needs.

The decision comes as Microsoft continues investing heavily in AI infrastructure, including the data centers and computing power required to run increasingly sophisticated models.

But the timing doesn't establish a direct connection between AI spending and the buyout offers. Microsoft has not said these employees are being replaced by AI, and there's no indication that all 60,000 will leave.

Which jobs are most vulnerable to AI?

The workers facing the biggest changes aren't necessarily those doing the most technical jobs. They're often people whose responsibilities involve repetitive, predictable tasks that AI can increasingly perform.

In a March 2026 study, Anthropic examined occupations using a combination of AI capabilities and real-world usage data.

Computer programmers, customer service representatives and financial analysts were among the occupations with substantial exposure to AI. Their work includes tasks such as writing code, answering routine questions, analyzing documents and processing information.

Anthropic found no systematic increase in unemployment among workers in highly exposed occupations, although it identified signs that hiring of younger workers may be slowing.

Stanford researchers found a similar pattern. In an August 2026 study examining payroll data from millions of U.S. workers, researchers found that employment among people ages 22 to 25 in highly AI-exposed occupations was 19% below where it would have been if it had grown at the same rate as employment among their less-exposed peers.

Again, that doesn't mean AI eliminated 19% of those jobs. The researchers found that much of the difference came from slower hiring rather than workers being laid off. They also cautioned that their findings don't prove AI caused the entire employment gap.

The research highlights that workers whose jobs rely heavily on documented knowledge and repeatable procedures may be more exposed than those whose expertise comes from experience, relationships and judgment.

For employees, the message isn't necessarily that their entire profession is at risk. It's that the tasks employers need them to perform are changing, and entry-level opportunities may be particularly vulnerable.

3 ways to protect your career as AI changes the workplace

There's no guaranteed way to make a job immune to automation. But the research suggests workers can take practical steps to become more adaptable as employers change their expectations.

1. Learn to use AI in your current job

One of the simplest ways to prepare is to become comfortable using the technology that's changing your industry.

That doesn't mean learning to code or becoming an AI expert. It means understanding how tools such as ChatGPT, Claude and Microsoft Copilot can help with the work you already do.

An administrative assistant might use AI to organize meeting notes, while someone in marketing could use it to analyze campaign feedback. A financial professional might use it to summarize reports before checking the figures independently.

There's evidence that these skills are increasingly valuable. According to LinkedIn's 2026 labor-market report, U.S. job postings requiring AI literacy skills grew 70% year over year.

What you can do today: Choose one repetitive task and experiment with using an approved AI tool to complete it. Compare the results with your usual approach, check for errors and avoid sharing confidential company information.

2. Build skills that go beyond what AI can automate

AI can summarize documents, write emails and generate reports, but completing a task isn't the same as understanding how it fits into a larger business decision.

Stanford's research found that experienced workers generally fared better than younger employees in AI-exposed occupations. The researchers also observed stronger employment patterns in roles that depend more heavily on knowledge developed through practice and experience.

That suggests there is value in developing skills that aren't easily captured in a set of instructions, including problem-solving, communication, leadership and the ability to make decisions when the answer isn't obvious.

What you can do today: Look for opportunities to take ownership of projects, work directly with customers or solve problems that require coordination with other people. These experiences can help you build expertise beyond routine tasks.

3. Show employers the value you bring

As AI changes how quickly work can be completed, simply being able to produce more may not be enough to stand out.

Instead, focus on the results of your work. That might mean improving customer satisfaction, reducing unnecessary costs, helping a team adopt a useful tool or identifying a problem before it becomes expensive.

Keep track of those accomplishments. If your organization restructures or you decide to look for another job, you'll have concrete examples of the value you bring beyond a list of daily responsibilities.

What you can do today: Write down three recent accomplishments and the impact they had. Where possible, include measurable outcomes such as time saved, revenue generated or improvements in customer satisfaction.

The takeaway

Microsoft's announcement arrives at a time when research is beginning to show changes in how employers hire, particularly for jobs involving tasks that AI can automate.

For workers, the immediate concern should be more about whether the skills that got them hired will be enough to keep them competitive. By learning to work with AI, building experience that goes beyond routine tasks and demonstrating measurable results won't guarantee job security, employees can gain a practical starting point as the workplace continues to change.

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With the US midterm election just a week away (Nov. 3), it’s important to avoid deepfake images meant to spread misinformation among voters.

I’ve come across far too many instances of older folks in the comments section falling for obvious attempts at political deepfakes. That trend got so bad during the 2024 US election that the “Tech Accord to Combat Deceptive Use of AI in 2024 Elections” was enacted, with companies such as Anthropic, Meta, Google and Microsoft signing on to uphold its mission to introduce “a set of commitments to deploy technology countering harmful AI-generated content meant to deceive voters.”

Part of that accord’s mission statement is as follows: “Digital content addressed by the accord consists of AI-generated audio, video, and images that deceptively fake or alter the appearance, voice, or actions of political candidates, election officials, and other key stakeholders in a democratic election, or that provide false information to voters about when, where, and how they can vote.”

OpenAI is another one of the major tech companies that signed on to support the accord’s attempts to fight back against election deepfakes. And in 2026, it introduced a pretty clever way to uphold its promise of preventing everyone from creating political deepfakes with ChatGPT.

Blocking requests for photorealistic imagery

Back in May of this year, OpenAI released a blog entry entitled “Election information and safeguards in 2026.”

One of the standout methods detailed in that blog is how it has altered ChatGPT to block the creation of images meant to misinform voters:

“We now apply image stylization to requests for images depicting election interference or that may discourage voting. These outputs produce stylized – also known as cartoonified – illustrations, rather than photorealistic images, to help reduce the risk that an imagined scene is mistaken for documentary evidence. This approach preserves room for illustrations and social commentary. Our policies prohibiting election interference and demobilization always apply, even if that misuse involves cartoonified imagery.”

That pretty much means any requests to ChatGPT for photorealistic images that are meant to be political deepfakes will only be produced in a cartoon style. And any follow-up requests to make that photorealistic change will be ignored outright.

I went ahead and tried it out for myself and requested the creation of an image showing someone stuffing official US mail ballots into a drop box. I made sure to mention that I want it in a photorealistic style, but it eventually came out as an illustration. And when I followed up with a second attempt at getting it done in a photorealistic fashion, ChatGPT just went ahead and made its original illustration look a bit better (by staying in cartoon form, by the way).

With Marist Poll releasing a poll noting that 70% of Republicans, 32% of independents and 18% of Democrats, it’s easy to see how the type of image I created could create some form of political disinformation if it were photorealistic and posted all over social media.

Other major AI companies, such as Google (Gemini) and Anthropic (Claude), have announced their own strategies for preparing and supporting the US midterm elections.

Google’s official blog on the matter points to its plan to help voters find the most reliable political information possible: “We highlight official resources and are rolling out interactive tools across Search, including in AI Mode and AI Overviews, and in the Gemini app to connect you with election information. This includes polling locations, registration deadlines and other official data provided by state and local governments and Democracy Works, as well as real-time voting results from The Associated Press.”

As for Anthropic, its blog also stated how the company made sure Claude pushes users to trustworthy sources for their midterm voter information: “Ahead of Election Day, we've added two ways for people to get reliable information directly in their conversations with Claude. As we shared in April, when people ask Claude.ai about voter registration, polling places, or election dates, we’ll continue to display a banner linking to TurboVote, a nonpartisan resource from Democracy Works.”

Anthropic also noted that Claude will begin to incorporate official voting information from Democracy Works into its responses late this month.

Bottom line

It’s good to see OpenAI install a safeguard in place in ChatGPT to block any attempts at generating photorealistic images meant to make political deepfakes. And it’s also nice to see Google and Anthropic step up to develop the sort of methods that do a good job of making sure their respective chatbots present the most truthful political data.

Here’s hoping all three AI companies continue to strengthen their efforts to block all attempts to use their tools to generate political deepfake imagery.

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Digital privacy stalwart Proton is reportedly set to interview employees across the company about how they use AI in their work, and the answers could help decide who keeps their job. The firm behind Proton Mail and Proton VPN – one of the best VPNs – told staff about the plan in an internal email on Monday, October 26, which was leaked to 404 Media.

The email calls the re-interviews "consequential." What interviewers conclude will be written up and fed into a broader review of the organization, which could change people's roles and responsibilities – or whether they stay at Proton.

The move fits a wider push under CEO Andy Yen, who has been steering Proton toward heavier AI use, including the launch of Lumo, its privacy-focused chatbot. Proton had not responded to 404 Media's request for comment at the time of publication, but has now made a public statement on Reddit.

What Proton says

In the Reddit comment on r/ProtonMail, posted from the Proton_Team account, the company claims it is "not doing layoffs and using AI as an excuse." As a counterpoint to this, it states it has a talent shortage and is hiring across the organization.

"AI is changing the tech industry," the comment continues, "and we, like everyone else, need to evolve our ways of working to remain effective in our industry, and to deliver features faster to users."

The company says it is "assessing how colleagues are adapting to these tools, what support they need, and who can help lead this work."

Finally, Proton states that it is also "assessing whether everyone has the skills they need to take a step forward in a post-AI world," and "offering the support that is necessary, to those who need it, to succeed."

In the Reddit comment, Proton also published the full email, which it says went to some of its staff.

Who gets interviewed – and by whom

The email itself is less reassuring to those impacted: "We are now extending re-interviews more broadly to assess how people are adapting to AI and whether they have the capabilities and approach needed for Proton’s next phase."

Not everyone will be re-interviewed. Interviews will be prioritized according to the organization's assessment needs, the email says, and an invitation – or the lack of one – isn't an outcome in itself. Any decision affecting someone's employment will come separately.

Those who are invited will be interviewed by someone outside their own team and reporting line, chosen from a pool of leaders who "demonstrate strong AI capability."

The interviews will run from November 4 to 11, and staff are told to arrive with concrete examples of their use of AI. The email is blunt about what passes muster here: "Be ready to discuss what you have changed in your work, the results, what you have learned, what has not worked, and what you would do differently. A list of tools alone will not demonstrate this."

What Proton wants from staff

The email also presents the interviews as a route to advancement, saying staff who rethink their work, put AI into practice and help others adapt may be offered greater responsibility. It asks for "curiosity, judgment and urgency."

Yen himself first interviewed more than 40 senior leaders across Engineering and Product, the email says, before the process widened to staff across the company.

AI is not new at Proton. An AI writing assistant arrived in Proton Mail in 2024, Lumo followed in July 2025, and the chatbot got an upgrade in June 2026. Proton says it keeps no server-side logs of Lumo conversations and runs the chatbot on its own infrastructure.

Yen told Wired in an interview published in August that AI is surveillance and that Proton was reluctantly pulled into building AI tools. He added that he would probably prefer a world without AI, but accepts it is here to stay. Clearly, his opinion has not changed on the matter.

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Imagine losing access to 13 years of Instagram photos, exhausting every recovery option and turning to ChatGPT for help. Instead of connecting you with Meta, the chatbot suggests contacting a journalist.

According to a new 404 Media report, it's happening often enough that the publication has received dozens of AI-generated requests from people struggling with everything from locked accounts to malfunctioning iPhones.

And while there's nothing inherently wrong with contacting the media, it's certainly the wrong direction for getting help fast. Anyone waiting for a follow up email from me, should know the inbox of a journalist is often filled to the brim.

When tech support becomes a news investigation

In his Monday report, 404 Media co-founder Jason Koebler describes receiving an email from a man in Russia who lost access to 13 years of Instagram photos and videos after his account was banned.

After exhausting Meta's appeals process, the man asked ChatGPT for another way to get help. The chatbot suggested contacting journalists, including Koebler, and even drafted an email explaining his situation.

He wasn't alone. Another user, frustrated by Verizon service problems that left an iPhone stuck in SOS mode, emailed multiple newsrooms requesting an investigation.

Someone else struggling with an unreliable ChatGPT assistant named Captain NORBERTA sent three AI-prepared PDFs, including a press release, personal statement and evidence appendix.

Koebler says 404 Media has received dozens of similar requests in recent months. After asking people how they found the publication, the journalists discovered that AI chatbots were repeatedly directing users their way.

But there's a difference between helping someone solve a problem and sending them on a mission that probably won't get them anywhere. So I put ChatGPT to the test.

Test 1: Recovering a locked Instagram account

Prompt: I am completely locked out of my Instagram account and have no way of getting back in.

ChatGPT immediately offered the usual account recovery steps. Nothing groundbreaking, but exactly what I'd expect from a troubleshooting assistant.

But instead of dumping a long list of instructions and leaving me to figure things out, ChatGPT essentially turned itself into a customer service agent. The chat interface became more interactive, guiding me through the recovery process step by step.

No wild goose chase. ChatGPT stayed focused on recovering my account, which is exactly what I wanted it to do.

Test 2: An iPhone stuck in SOS mode

Prompt: I got a new iPhone but my old phone is in SOS mode and I am not finished switching over. How do I get my phone out of SOS mode so I can use it to make calls again.

This one hit a little too close to home because it actually happened to me over the weekend.

My husband and I bought new iPhones in the exact same color. What was I thinking?

Somewhere during the setup process, things went sideways. His Apple account information ended up on the phone associated with my number, and my old phone was stuck in SOS mode. Suddenly, something as simple as upgrading our phones had turned into an absolute nightmare.

We ended up leaning heavily on ChatGPT to help untangle the mess. And unlike the experience described in 404 Media's report, the chatbot didn't suggest escalating our problem to a newsroom. It stayed focused on troubleshooting the phone, explaining what SOS mode meant and helping us work through the next steps.

Test 3: Recovering a forgotten Apple ID password

My prompt: I have lost my Apple ID and am locked out of my new iPhone. I cannot finish the set up or change settings without it. Help.

Unfortunately, the SOS problem wasn't the only thing that went wrong with our new phones.

My husband had also forgotten his Apple account password. And considering how often Face ID handles authentication these days, I can't exactly blame him.

You don't realize how important that password is until you're setting up a new device and suddenly can't get past the sign-in screen. Once again, I turned to ChatGPT.

At first, it suggested the basic password recovery steps we'd already tried. That wasn't especially helpful, but it wasn't surprising either. ChatGPT had no way of knowing what we'd already done.

The difference came when I started explaining our very specific situation and what hadn't worked. ChatGPT continued helping us work through the available options without immediately handing us off to Apple.

It couldn't bypass Apple's security requirements, but it gave us a way to understand what was happening without constantly hunting through support pages. Having someone — even an AI — explain each step made an incredibly frustrating situation easier to manage.

The takeaway

When something goes wrong with my tech, ChatGPT is often the first place I turn. And in my three tests, ChatGPT largely did what I hoped it would. It offered troubleshooting advice, asked for more information and stayed focused on the actual problem.

Not once did it suggest contacting a journalist. Based on how quickly AI moves, it's very possible that OpenAI jumped on the problem and fixed things internally, but the bigger lesson is that sometimes AI can be genuinely helpful, like in my case, or sound helpful and lead users astray.

An AI assistant can give you detailed instructions, draft a convincing email and make an elaborate plan sound perfectly reasonable. But none of that guarantees it's pointing you toward a solution.

For everyday troubleshooting, ChatGPT can be a useful first stop. Just don't assume every recommendation is worth following.

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I can’t tell you how many times I’ve been alerted by the sound of my phone buzzing, picking it up and being treated to a text that has clear signs of being a scam.

And while most folks from my generation are quick to spot the warning signs of an obvious scam, there are those out there who aren’t so adept at picking up on those signs. And sadly, there are far too many people falling for the sort of scams that show up unexpectedly in their text messages and emails. Thankfully, ChatGPT has popped up as a surefire way to help those types of people dig deeper into suspicious activity — by using its scam detection-focused plugins and doing some independent research of your own to verify what you’ve been sent, you’ll have a much easier time steering clear of everyday scams.

The following list of ChatGPT plugins can help you check a questionable message, link, online retailer and anything else you may deem untrustworthy.

And alongside those plugins are examples of the best prompts to use for every type of scam-detection session you may have in the future.

1. Norton

Norton has earned its reputation as one of the most reliable and prominent consumer cybersecurity and antivirus brands. With its attachment to ChatGPT as a plugin, it comes in extremely handy when trying to assess the context of phishing texts, fake delivery notices, suspicious emails, and impersonation attempts. This plugin stands out as the best overall option to consider when trying to discern whether a message or link you’ve received can be trusted or not. Using the following list of prompts should help you see just how efficient the Norton plugin truly is:

• Analyze this text message for scam indicators. Explain the red flags, assess the risk and tell me what I should do next: [paste message]
• Check this website or link for signs of phishing, impersonation or fraud: [paste URL]
• Someone claims to be from my bank and says I must act immediately. Assess this message and tell me how to verify the claim safely: [paste message]

2. Malwarebytes

Malwarebytes is also one of the best practical methods to employ when using a ChatGPT plugin to verify dubious-looking links that have been sent your way, phone numbers and retail sites. The prompts posted below should showcase how good this plugin is at spotting a not-so-obvious scamming attempt (its description page also notes that it’s good at verifying promo offers and invoices):

• Investigate this URL for signs of phishing, malicious activity or a fake login page. Explain what you can verify and what remains uncertain: [paste URL]
• Assess this phone number for reported scam indicators: [paste phone number]. Tell me whether the findings are confirmed, inconclusive or suspicious
• I'm considering buying something from this website. Check for available indicators of risk and tell me what I should independently verify before paying: [paste URL]

3. IsThisSpam

IsThisSpam’s mission statement is as follows: “Results distinguish likely scams from unverified findings; no result is a guarantee of safety.” Of course, doing your own research in combination with the results you get from this plugin when checking for shady-looking phone numbers, text messages, links and web addresses is worth doing with this plugin in mind. The following prompts should give you a good idea of how effective the IsThisSpam plugin can be:

• Check this message for scam signals. Highlight suspicious wording, requests for money or personal information, and pressure tactics: [paste message]
• Investigate this sender's email address and the website it links to. What evidence supports or contradicts its legitimacy? [paste details]
• Give me a plain-English risk assessment of this suspicious phone number or text, and the safest next steps: [paste details]

4. McAfee

Just like Norton, McAfee is recognized as one of the premier cybersecurity software companies that offer consumers online protection, antivirus software and identity theft solutions. As a ChatGPT plugin, it also does a good job of checking if a text you’ve received via a DM, a link that popped up in your text message or a message that’s requesting money is legit or not. The following prompts provide a few examples of what to ask the McAfee plugin when you’re trying to avoid falling for a scam:

• Help me assess whether this message is a phishing attempt. Identify the warning signs and explain how to verify it independently: [paste message]
• Evaluate this link for potential security risks and tell me whether I should avoid opening it: [paste URL]
• Help me investigate a suspicious online shopping offer. What signs suggest a fake store, and what evidence should I check before entering payment details? [paste URL and offer]

5. Jacana Scam Check

The Jacana Scam Check promises to see if a text, email or DM is another case of fraud just waiting to disrupt your life and finances. It’s also worth using when trying to see whether a site, phone number or email address is worth trusting or avoiding altogether. Using this plugin to stay safe from fake delivery notifications, bank impersonation emails, dodgy-looking job offers and more should keep you safe from all the different scams littering the world right now. Keep these prompts in your back pocket for those cases when you need to utilize the Jacana Scam Check plugin:

• Assess this delivery notification for signs of a parcel scam. Check for unexpected fees, fake tracking links, requests to reschedule delivery, and attempts to collect payment or personal information. Explain how to verify the shipment directly with the official delivery company. Message: [paste text]. Tracking link (if provided): [paste URL]
• Evaluate this job offer for potential employment scams. Look for fake recruiters, unrealistic pay, requests to pay for training or equipment, fake checks, identity theft and requests to move money. Separate confirmed evidence from warning signs and tell me what I should verify with the employer before sharing documents or accepting the role. Job offer: [paste text]. Company: [paste name]. Recruiter contact: [paste details]. Job listing: [paste URL]
• Check this giveaway or prize notification for signs of fraud. Look for impersonated brands, fake winner announcements, advance fees, requests for banking details and suspicious links. Tell me how to locate the official competition rules and verify the organizer without using links in the message. Message: [paste text]. Claimed organizer: [paste name]. Link: [paste URL]

Final thoughts

Trusting your gut whenever something dodgy-looking pops up in your texts, emails and DMs is certainly worth doing. But it’s also worth getting a second opinion on what you’re seeing from the five ChatGPT plugins I’ve chosen to include here.

Then, doing your own research into those types of scams, blocking the numbers & social media profiles that tried to scam you and making your loved ones aware of those types of scam attempts should make you more aware of any future scam attempts. For the obvious and not-so-obvious scams that catch some unsuspecting folks off guard, be sure to let them know that ChatGPT has a library of prompts that can assist them in not falling prey to them.

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With the midterm elections just eight days away, Anthropic has confirmed that its Claude AI accessed Georgia election data without human authorization. The incident involved an AI model independently finding a way around a government paywall, raising new questions about how much control developers have over increasingly autonomous AI systems.

According to Axios, Claude retrieved publicly available vote counts during an internal statistics project. Instead of paying the fee typically required to access the information, the model discovered a way to request an access token and retrieve the data on its own.

To be clear, there is no evidence that Claude interfered with the election or accessed individual voter records. Georgia officials confirmed that the state's voter registration system was not compromised, and Anthropic said no voting records were changed.

Still, with voters already casting ballots ahead of November 3, the disclosure comes at a particularly sensitive time.

How Claude accessed Georgia's election data

The incident began with what sounds like a fairly ordinary prompt for Claude. An Anthropic researcher was using Claude Mythos 5 to gather publicly available information for a statistics project.

The data was available through a Georgia state agency, but accessing it normally required payment.

According to Anthropic's October 9 research report, Claude found an archived version of the agency's website that revealed how its public dashboard issued access tokens to visitors.

An access token is essentially a digital credential that allows someone to request information from a website or service.

Claude requested one, used it to query the database and retrieved the information without paying the usual fee. It wasn't explicitly instructed to take those steps.

An Anthropic spokesperson confirmed the behavior to Axios, saying the model had independently requested the token while completing its assigned task.

Claude didn't break into a private database or access personal voter information, rather it found another way to retrieve publicly available data that would normally require payment.

Georgia's Secretary of State's Office confirmed that the model accessed information through the state's public data hub, not its voter registration system.

What did Claude actually access?

Despite the alarming timing, the information Claude retrieved was much less sensitive than the phrase "voter data" might suggest. The model collected aggregate vote counts, meaning statistical totals rather than individual voter records. According to Anthropic and Georgia officials:
Claude did not access the state's voter registration system.

• It did not retrieve personal voter information.
• It did not change voting records or election results.
• Officials found no evidence that Georgia's voting system had been compromised.

Georgia Secretary of State spokesperson Robert Sinners told the Atlanta Journal-Constitution that the incident did not involve a data breach, hacking or tampering with election systems.

With Election Day approaching, it's important to understand what actually happened. Claude bypassed a payment requirement to access publicly available election data, but it did not interfere with the systems used to register voters, cast ballots or count votes.

Anthropic says it has already taken action

The Georgia incident wasn't the only example of Claude doing something its developers hadn't intended. In its October 9 report, Anthropic described several cases in which its models worked around restrictions while attempting to complete assigned tasks.

Some involved accessing information behind payment requirements or digital access controls. Others involved interacting with real websites in ways the company hadn't authorized.

Anthropic describes much of this behavior as a form of "persistence." When a model encounters an obstacle, it may look for another way to complete the task rather than stopping to request permission.

That can be useful when an AI assistant is troubleshooting a problem. But it becomes concerning when the model starts bypassing restrictions that were supposed to limit what it could do.

Following its investigation, Anthropic said it expanded restrictions on internet access during internal evaluations, strengthened safeguards around its browsing tools and developed additional monitoring systems designed to detect unauthorized behavior.

The company reported that its new protections successfully blocked the previously identified behaviors during testing.

Axios also reported that Anthropic had notified Georgia's Secretary of State's Office and the White House weeks before the incident became public.

Why this matters ahead of the midterms

With Election Day just days away, the incident raises concerns about how AI agents operate when they encounter restrictions, particularly when government information is involved.

The bigger issue is whether AI systems can recognize the limits of their authority. Completing a task successfully doesn't necessarily mean the steps taken to get there were appropriate, especially when an AI makes decisions without checking with a human first.

For developers, this creates a difficult problem. AI agents need enough freedom to be useful, but that freedom also makes it harder to predict their behavior or ensure they follow the rules.

For everyday users, the concern extends beyond elections. AI assistants are being given access to browsers, accounts and personal information, often with permission to act on someone's behalf. The more responsibility people hand over, the more important it becomes to understand what those systems can do without asking.

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It’s not all that shocking to come across another story where an AI company is getting sued for something.

What’s become even more common in that regard is the growing number of legal cases where AI companies are being brought to court for using copyrighted music without permission. The practice of AI companies allegedly using artists’ song catalogs to train their AI models, voice cloning of certain singers and AI music being created in a real-world artist’s style are coming up as legal battles as of late.

The latest case of that can be tied to Elvis Presley and the owners of his music catalogue putting AI company Anthropic in their legal crosshairs. And Anthropic has been roped into this lawsuit because it’s being alleged that they’re using the iconic singer’s music to train their AI models without getting any permission from the rights holder.

Here are some extra details about that lawsuit, plus a few other instances of AI companies getting sued for similar unauthorized practices concerning a musician’s catalogue.

The owners of Elvis Presley’s music see Anthropic as “nothin’ but a hound dog”

As first reported by Billboard, Authentic Brands Group, the licensing group that has ownership of both Presley’s music and likeness, has filed a lawsuit against Anthropic. The lawsuit accuses the AI company of infringing upon the rights to 274 songs by Presley by using them to train its models. Some of the songs mentioned as the ones being used unlawfully include “Can’t Help Falling in Love,” “All Shook Up” and “A Little Less Conversation.” The Elvis plaintiffs are seeking $150K for all the infringed tracks, which comes out to a total of $41 million.

The Elvis case isn’t even the first time Anthropic has been caught in legal trouble over the unauthorized use of someone’s music. Earlier this year, in August, Round Hill Music filed a copyright infringement lawsuit against Anthropic and Suno.

In a press release announcing the lawsuit, Round Hill stated that the following musical works have been used by both AI companies to train their models without proper authorization, licensing or compensation: "Iris" by the Goo Goo Dolls, "Total Eclipse of the Heart" by Bonnie Tyler, written by Jim Steinman, and "I Got You (I Feel Good)" by James Brown.

Just by checking out the Dramatists Guild page for relevant AI cases that are connected to AI Music Platforms will highlight several ongoing legal battles. Another one of those major cases involves UMG, WMG, and Sony filing suit and alleging that AI music startup Udio trained its generative AI models on their copyrighted recordings without permission. UMG and WMG have actually settled with Uncharted Labs (the parent company behind Udio), while also establishing licensing partnerships for training Udio. However, Sony has chosen to continue its lawsuit.

It’s also worth noting that musical artists Jason Isbell, Guy Forsyth, Ed Calle, and David Lowery have joined forces to file a class action lawsuit against Suno. Also reported by Billboard, the case’s plaintiffs allege that Suno is violating their rights of publicity under numerous state statutes, which is different from the current copyright lawsuits between Suno and other music rights holders.

Here’s a statement from that lawsuit that explains the main complaint at the heart of its case:

“Suno’s system recognizes ‘Jason Isbell’ as far more than a mere text string; it is a retrieval key for a set of performer-specific representations that it can use to generate a response associated with that musician. From a name prompt alone, a user receives a multi-modal experience evoking that named musician. This includes access to a generated song like one the named musician might create, a description of the musician’s attributes and a related image. This is true for countless other musicians.”

Other music publisher vs. AI company cases worth keeping an eye on are Reservoir Media vs. Anthropic and Suno (which involves the infringement of songs by Joni Mitchell, Johnny Cash, Madonna and more being used to train AI models) and BMG vs. Anthropic (which involves the copyright lyrics of artists Bruno Mars and The Beatles to do the same).

Bottom line

With so many cases of AI companies allegedly using the copyrighted works of musicians to train their models without getting permission from the music labels or rightful owners, I wouldn’t be surprised to see even more of them popping up over time.

Back in 2024, major artists such as Billie Eilish, Nicki Minaj, Jon Bon Jovi and over 200 other musicians signed an open letter warning against the “predatory use of AI” in the music industry. And with the likes of SZA and Kenneth Blume calling out the use of their music to train AI, it’s clear that the music industry and its performers aren’t all that keen on the practices of AI companies.

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Most of us would like to believe we're independent thinkers who make decisions based on facts, logic and personal values. But according to some of the world's biggest AI models, we're not nearly as independent as we think.

In a new experiment published by ModelCompare on October 22, researchers asked 12 AI models, including ChatGPT, Claude, Gemini, Grok and DeepSeek, to share their most controversial opinions about humans.

The results were wildly consistent. Of the 35 responses collected, 29 expressed essentially the same idea: humans care more about belonging to a group than discovering the truth.

Perhaps most ironically, the AI models seemed to demonstrate their own version of conformity while criticizing ours.

What the AI models said about humanity

The researchers asked each model the same question three times, instructing it to give its own view rather than summarize other opinions.

Some of the responses were particularly blunt. For instance:

GPT-6.1 Sol argued that humans prioritize belonging over truth, suggesting that intelligence often serves to make our excuses more convincing.

Grok 4.7 delivered one of the most memorable responses: "Humans would rather be wrong together than right alone."

Gemini 4 Argon went further, suggesting that people use their intelligence to defend decisions made by instinct rather than arrive at objective conclusions.

DeepSeek V4 Pro was similarly critical, arguing that people are better at rationalizing their beliefs than examining them.

Interestingly, seven models gave variations of the shared criticism in all three responses. Every model expressed it at least once. Although the wording differed, the message was largely the same. We like to think we're making independent decisions, but our desire for acceptance may influence our beliefs more than we realize.

Claude had a surprisingly different answer

Not every response was pessimistic. Claude Opus 5.5 offered one of the experiment's most unexpected takes, suggesting that people are actually kinder and more decent than they give themselves credit for.

Rather than criticizing humanity for selfishness or conformity, Claude pointed to the gap between how poorly people sometimes view one another and how generously strangers can behave.

That was a notable departure from the other responses, although Claude also echoed the broader criticism in its remaining two answers.

Other exceptions were considerably darker. Mistral Large 4 described human consciousness as an evolutionary malfunction, while another model suggested people might sacrifice happiness simply to feel important.

These exceptions helped illustrate that the models weren't incapable of producing different opinions. They simply gravitated toward a remarkably similar criticism.

AI image generators had a different complaint

The experiment didn't stop with chatbots. ModelCompare also asked six AI image generators to illustrate their most controversial opinions about humanity.

Ten of the 12 generated images centered on a different theme: humans as technology-obsessed consumers damaging the planet. The images depicted people scrolling on their phones while ignoring danger, consuming resources and remaining distracted as the world around them deteriorated.

Surprisingly, none of the 35 text-model responses mentioned smartphones or environmental destruction as their central criticism.

That difference may say something about the information each type of AI learns from. Language models are trained on enormous quantities of written material, including arguments about human psychology and behavior, while image generators learn visual patterns that can include familiar editorial cartoons and social commentary.

Does this mean AI has figured us out?

Well, I wouldn't say that, exactly. There is a genuine psychological concept behind the responses called motivated reasoning, which describes how our preferences, existing beliefs and social identities can influence the way we interpret information.

Research has also explored how strongly group identity shapes what people believe, although psychologists continue to debate exactly how these effects work.

But this experiment is not scientific proof that humans value belonging more than truth.

The models were given a deliberately provocative prompt, and the researchers grouped the answers manually into broad categories. The experiment involved a relatively small number of responses and didn't test how the results might change under different instructions.

AI models don't need personal convictions to generate forceful opinions. They can reproduce arguments and patterns learned during training. So, in other words, these answers may tell us as much about the way humanity writes and talks about itself as they do about human nature.

Final thoughts

What makes this experiment fascinating, at least in my opinion, is that so many different models reached for a familiar criticism when asked to say something controversial.

The researchers captured the irony perfectly: the models produced remarkably similar answers about our tendency to conform. And that might just be the biggest takeaway here. Whether we're talking to other people or asking a chatbot for advice, it's worth questioning answers that sound convincing simply because everyone seems to agree.

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Being on the lookout for a job in this day and age, where AI plays such an important role in getting hired or not, can certainly be frustrating. Using AI to tailor your resume for different roles and prepare for interviews (with both human and AI interviewers) has become a go-to practice for many job seekers.

Greenhouse’s new Future of Hiring Candidate Report points out a surprising stat pertaining to that practice: 6 in 10 job seekers are changing how they write their resumes and cover letters to avoid sounding like AI, even as most of them use AI in the job search process.

Some of the other stats are equally shocking (and disappointing in some areas: 81% of U.S. candidates were rejected in the past year without speaking to anyone at the company and 96% wish they could show employers something their application doesn’t (which is a skill set led by their ability to learn and adapt).

We spoke to Ophir Samson, Greenhouse’s Head of Voice AI, who laid out a clear set of rules for job seekers when it comes to what to do and what not to do when using AI to nab their next role.

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I never deemed it possible, but AI’s ability to predict extreme weather conditions has actually morphed from a fantasy into a reality.

Tools such as Google DeepMind’s GraphCast, Huawei’s Pangu-Weather and ECMWF’s AIFS have emerged—by running on decades of historical weather and atmospheric data, they all rely on pattern recognition to be as fast and efficient as possible when generating global forecasts. Even organizations such as the National Oceanic and Atmospheric Administration (NOAA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) have utilized AI weather systems to keep track of large-scale environmental events.

The emergence of spatial AI is doing even more in that regard, as it's already helping US cities predict and prepare for floods, wildfires and urgent infrastructure failures before a disaster strikes.

Hantz Févry, CEO of Geolava, which is a technology lab developing AI models for the physical world, answered some questions about how spatial AI works when predicting extreme weather events. He also provided proof of its usefulness, as it’s already assisted the people of Florida in a major way.

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ChatGPT and Grok are two of the biggest names in AI, but which one is actually better at helping with everyday problems, particularly for the boomer generation? I wanted to find out, which is why I decided to focus on the types of questions my parents, their friends and my older relatives might actually ask.

From spotting a suspicious USPS text to understanding Medicare, planning affordable dinners, and choosing a new smartphone, I gave both chatbots five identical prompts based on real-life situations. I wanted to know which chatbot could give clear, accurate and genuinely useful advice without making things more complicated than necessary.

The results surprised me. One chatbot handled practical details better, while the other seemed to understand when less information was actually more helpful. Here's how they compared.

1. The suspicious text test

Prompt: I just got this text message: 'USPS: Your package could not be delivered due to an incomplete address. Update your information within 24 hours at usps-redelivery-help.com, or your package will be returned.' I'm expecting a package this week. Is this legitimate? Explain how you can tell, what I should do next and what could happen if I click the link. Please don't use technical jargon.

Grok answered correctly, correctly identified the fake domain, and clearly explained how real USPS tracking works. It mentioned that you could report the text to the U.S. Postal Inspection Service or FTC, but unlike ChatGPT, it gave no specific instructions, phone numbers, or email addresses for how to actually do so.

ChatGPT immediately stated that the text is almost certainly a scam and advised not to click the link. It used a clear, scannable table breaking down scenarios step-by-step (e.g., clicking without entering details vs. entering payment info vs. downloading malware). It also highlighted the key trick scammers use: asking for a small "redelivery fee" to steal credit card data (which USPS does not charge). It also provided reporting channels, including forwarding the message to 7726 (SPAM) and emailing spam@uspis.gov.

Winner: ChatGPT wins for delivering a more comprehensive, actionable answer that addressed every part of your prompt while keeping the tone clear and accessible.

2. The Medicare confusion test

Prompt: I'm turning 65 next year, and I don't understand Medicare. Explain the difference between Medicare Parts A, B, C, and D like you're talking to a friend over coffee. What's the difference between Original Medicare and Medicare Advantage? What are three expensive mistakes I should avoid? Keep it under 400 words and tell me what information I should verify before enrolling.

Grok kept its response under 400 words, nailed the conversational tone, and included accurate financial figures, noting the Part B premium for 2026 as around $203/month

ChatGPT provided a good response but exceeded the word count, used a standard informational guide structure with a table, and included extraneous metadata at the bottom that didn’t feel helpful or necessary for the average person.

Winner: Grok wins for better executing the specific parameters requested by the prompt.

3. The grocery budget challenge

Prompt: I'm cooking dinner for two adults for five nights this week, and I only have $65 to spend on groceries. We don't eat seafood, and I don't want anything that takes more than 30 minutes to prepare. Create five different dinners, one combined shopping list with estimated U.S. supermarket prices, and show me the total. Reuse ingredients to save money, and don't assume I already have anything except salt, pepper and cooking oil.

Grok delivered a solid list of meals and kept the price low, but it failed on several key details requested by the prompt, including assuming missing ingredients, unrealistic grocery quantities (1.5 lbs of chicken is barely enough meat to split across 3 separate meat-heavy dinners), and vague cooking guidance.

ChatGPT strictly adhered to the “no pantry” constraint, included necessary flavorings and mapped out meal prep details specifically using the items. It also provided an incredibly comprehensive shopping list with pricing.

Winner: ChatGPT wins for providing a significantly more practical, thorough and well-executed response.

4. The family text dilemma

Prompt: My adult daughter keeps asking me to babysit my grandchildren at the last minute. I love spending time with them, but I'm retired and have my own plans. I want to set boundaries without hurting her feelings or making her think I don't want to help. Write a text message I can send that's loving, warm and firm. It should sound like a real parent, not a therapist or a corporate email. Keep it under 100 words.

Grok struck the perfect balance between warmth and firm boundary-setting ("they’re the absolute best part of my week... just need a little heads-up so I can make it work"). It felt completely natural and authentic for a parent to send via text. It also offered an actionable solution with clear, manageable expectations without sounding demanding.

ChatGPT drafted a warm, loving text, but it exceeded the word count and tone constraints. The “Just because I’m retried doesn’t mean I’m free!” was a bit preachy and the “I need you to understand…” could come across as slightly sharp or defensive.

Winner: Grok wins for nailing both the word restraint and the requested tone.

5. The new phone decision

Prompt: I'm 68 and need a new smartphone. My current phone is slow, and I don't want to spend more than $500. I mostly use it for taking pictures of my grandchildren, texting, Facebook, video calls and looking things up. I want a good battery, a screen that's easy to read and a phone that will last at least four years. Compare three phones I can buy in the U.S. right now, explain the pros and cons without technical jargon, and recommend just one. Include current prices and links to verify them.

Grok understood the primary goal and correctly recognized that the Google Pixel line excels at taking sharp, motion-blur-free photos of moving kids and recommended the Google Pixel 9a. It kept technical jargon to a minimum and explained features in plain language.

ChatGPT included some good overall advice (like asking the store to increase text size), but it stumbled on key parts of its recommendation and source selection, including contradictory recommendations and questionable third-party retailer links.

Winner: Grok wins for a much better recommendation and experience by accurately prioritizing the user's primary requirement while keeping formatting clean and straightforward.

Overall winner: Grok

Going into these tests, I expected ChatGPT to have the edge, especially when it came to explaining complicated topics and helping with everyday decisions. And in some cases, it absolutely did. Its advice on spotting a USPS scam was more thorough and actionable, and its grocery plan was much more realistic for someone working with a strict budget.

But Grok surprised me by doing something equally important: knowing when to keep things simple. It delivered a clearer Medicare explanation, wrote a more natural family text and made a stronger smartphone recommendation without overwhelming the reader with unnecessary details.

For anyone who wants detailed, step-by-step guidance, ChatGPT remains an excellent choice. But for people who just want a straightforward answer they can understand and use immediately, Grok proved surprisingly capable.

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I feel like everyone should have a quiet moment to themselves once in a while so they can do some proper self-reflection.

I’ve been doing that a lot lately, especially since I’m close to crossing the 40-year-old milestone and entering the next decade of my life. Like most folks, there are aspects of my life that are going extremely well. And there are other portions of my life that could be labeled under “room for improvement.”

Being a realist doesn’t come easy — my days as a happy-go-lucky optimist are gone, yet I still approach life with a positive mindset (it’s just backed by a more rational outlook on everything instead of relying on wishful thinking). One day, I got the urge to be as real with myself as possible by asking ChatGPT and Gemini to give me a list of the most brutally honest questions everyone should ask themselves.

And after picking up seven of them and taking the time to find the sobering answers, I was forced to change a few of my behaviors and find solutions to my biggest problems.

ChatGPT’s best questions

Before I took a look at ChatGPT’s list of hard-hitting questions, I read its opening statement.

And it perfectly laid out how those types of questions are a must for anyone looking for a definitive path to follow in life: The most brutally honest questions are the ones that force you to confront the gap between the life you're living and the life you say you want. They're uncomfortable because answering them honestly means taking responsibility for what happens next.

After getting hit with the equivalent of a cold bucket of water in the form of a truthful phrase, I came away from ChatGPT’s suggested questions with these three picks:

• Am I actually happy, or have I just gotten comfortable being unhappy? - Are you genuinely satisfied with your life, or have you simply gotten used to a routine that doesn't fulfill you? Sometimes, what we call stability is really fear of change. And what we call being realistic is sometimes just giving up on what we want.
• What truth about myself am I avoiding because accepting it would force me to change? - Maybe you're in a relationship you know isn't right for you. Maybe you're afraid to admit that your dream no longer excites you. Maybe you've developed habits that are sabotaging your future, or you're waiting for someone else to change before you can be happy. What do you already know deep down but keep negotiating with yourself to avoid? Sometimes, the hardest part isn't discovering the truth. It's accepting the consequences of acting on it.
• If my life ended tomorrow, what would I regret spending so much time worrying about? - Would it be the opinions of strangers? The argument you couldn't let go of? The promotion you sacrificed your happiness for? The people you kept meaning to call? The experiences you postponed until you had more money, more time, or more confidence? Imagine looking back on your life and realizing how much of it you spent worrying about things that ultimately didn't matter. What would you wish you'd done differently while you still had the chance?

The first question hit me pretty hard — while I’m definitely pleased with several parts of my life, there are areas of it that have remained stagnant and in dire need of a change.

Getting my own place would be one of the things that changes my life in a major way and gets me out of the comfort zone I’ve become so accustomed to over the years. The truth I’ve been avoiding is how being afraid of rejection is getting in the way of my dating life. I had to realize that every shot I take at a potential relationship won’t always be a win — take those losses, learn from them and use that experience to (hopefully) come out on the better end of my next chance at dating.

ChatGPT’s final question forced me to stop being so afraid of getting judged by strangers, especially since I’ve always refrained from going out in public dressed up for a major geek convention. “Those funny looks come with the territory,” I said to myself. “Be confident in yourself; stop letting the opinions of people who don’t even know you affect you and go to conventions dressed to the nines.” The fear of public embarrassment will no longer stop me from leaving my home adorned in some eye-catching cosplay.

Gemini’s standout inquiries

Gemini’s initial statement about asking oneself brutally honest questions hit me right in my soul: Self-reflection requires dropping comfortable self-deceptions. With that in mind, I took note of four of its questions for my latest moment of introspection:

• Am I waiting for someone else to fix a problem I created? - It is easy to cast yourself as a victim of circumstance, bad timing, or other people's choices. Asking this forces you to distinguish between genuine external obstacles and areas where you are abdicating personal agency.
• What am I tolerating right now because I am afraid of conflict or change? - Whether it is a stagnant job, a toxic relationship, or a bad habit, silence and inaction are choices. Admitting what you are actively choosing to tolerate removes the illusion that you are stuck.
• Is this a genuine limitation, or is it just uncomfortable? - People frequently confuse difficulty or awkwardness with inability. Labeling something as "impossible" often excuses you from doing the uncomfortable work required to achieve it.
• Am I complaining about results I didn't get from work I didn't do? - Entitlement often sneaks in when expectation outpaces effort. This question forces you to audit whether your daily input actually matches the output you feel entitled to receive.

One of the problems I’ve had since my younger days is not reaching out enough to my friends.

I’m terrible when it comes to picking up the phone and calling someone, which is a character trait that has led to some folks becoming more distant from me as time wears on. I made more of a conscious effort to reach out to my closest friends from high school and college (especially the ones that live out of state), with the sole goal of repairing relationships I should fix.

My eating habits could certainly be better, which has led me to tolerate far too many weeknights where I stuff my face with a snack instead of a home-cooked meal. Ridding myself of my lazy ways after coming home from work has become a new routine I’ve been trying to stay on top of.

I can’t lie — I once marked my goal of putting on some muscle as “impossible,” especially since my aforementioned diet and laziness have created barriers that have kept me from reaching it. But now I’ve begun incorporating push-ups and sit-ups into my pre-shower and pre-bedtime schedule to supplement my weekend visits to the gym. I’m sure that’ll turn that objective I previously deemed unattainable into something more procurable.

Gemini’s final question went hand-in-hand with my fitness aspirations, so I stopped grumbling over the muscles I didn’t have and started doing more to actually obtain them.

Final thoughts

I know chatbots aren’t great therapists or psychiatrists. But I do like the fact that they can present everyone with the questions and information they need to confront the uncomfortable truths in their lives.

ChatGPT and Gemini’s list of candid questions that everyone should ask themselves provided me with thoughts on facing my current situation, choosing the things that need fixing, adopting more beneficial habits and making a concerted effort to never let them fall by the wayside.

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AI agents built to operate as personal assistants that boost one’s productivity have been popping up all over the place as of late.

Meta Muse has emerged as one of the more popular apps tied to that distinction. Plus, the likes of OpenAI Dots, Grok Bot, and Instinct are part of the expanding AI agent offerings being used today. Anthropic must have been keeping a close eye on this emerging trend, as the AI-focused tech giant just launched an AI agent of its own.

The brand new Claude Duet iOS and Android app, which is designed to be an incredibly efficient digital partner for busy professionals, has now been released as a research preview for Claude users subscribed to the Pro and Max plans in the US through a waitlist. And while it’s not readily accessible for Claude subscribers on Team and Research plans just yet, Anthropic is planning to bring it to those plans at an unannounced date. Keep in mind that Claude Duet has the same usage limits as the rest of Claude for Pro and Max subscribers,

Here’s what Anthropic promises its newly released Claude Duet AI agent app can do.

Claude Duet is a new agentic AI app meant to work for professionals

The Claude Duet app works as an AI agent powered by Claude Opus 5.5 and its capabilities mainly cater to streamlining the daily operations of professionals. Since it works directly with a user’s Claude account, all the memory, skills and connectors you’ve previously set up will be in place from the very first time you send a message to Claude Duet.

And since the app works from its own computer in the cloud, it can keep working on any tasks it’s been given even after you close the app.

Of course, you can type out a message to Claude Duet or record a voice message to make it start working.

As for what it can do for you without you even having to ask, Anthropic’s AI agent app can send you a brief every morning, depending on the information contained in the connected email and calendar you’ve given it access to. Claude Duet is promised to be able to pick out the assignments that require a user’s immediate attention and lay out the steps needed to complete the task at hand. And as the day wears on, the app will send you updates on the tasks it’s working on and occasionally follow up on any text/voice note threads that haven’t been tended to in a while.

One of the more surprising things about Claude Duet is the massive library of connected apps it can use. Some of the 6,000+ connectors and plugins you can grant it access to include Gmail, Slack, Intuit QuickBooks, Stripe, LinkedIn, DocuSign, etc. User privacy and safety are at the forefront of Anthropic’s foundation for Claude Duet. Claude Duet has the capacity to work with those apps to help you reply to important messages, keep a close eye on unpaid invoices, create/edit/approve job postings, prepare contract agreements before sending them off, etc.

The AI agent app automatically rejects highly sensitive information (such as credit card numbers and government IDs, for instance) and always asks for approval before taking the next step for a crucial task (like making payments).

In its current research preview state, Claude Duet does have a few limitations in place. You can’t choose the model it runs on, you can’t observe it work in a browser or take over the browser yourself and the Microsoft 365 connector is not yet available for use with it. For a full list of what Clade Duet can’t do right now, check out this official blog post from Anthropic.

Bottom line

Claude Duet sounds like it can eventually transform into a viable competitor in the AI agent market and become the Meta Muse for professionals that they've been looking for.

If you’re interested in trying it out for yourself, it’s worth joining the Claude Duet waitlist and seeing if you get access to it at some point.

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• Google just cut down 250,000 trees for AI data centers — and now it's facing a major backlash
• “A cyber compromise could potentially translate into unsafe physical behavior”: how AI worms could threaten cars and drones

Waking up to the latest news of AI doing something it wasn’t permitted to do that could put humanity at risk has become way too common.

The reports that have come in from OpenAI and Anthropic about their autonomous AI agents going rogue and displaying “problematic behavior” have been troubling. And learning about AI swarms coordinating hacks has been equally alarming. A recent study from Anthropic even warned about the possibility of AI models being able to replicate themselves across everyday smart devices, without needing access to data centers.

After Anthropic’s Frontier Red Team observed how small AI models could reproduce themselves as “AI worms” across off-brand Android TV boxes and smart ovens, it became clear that AI-powered malware could morph into the next major cybersecurity threat.

I wanted to know if AI worms could spread to other everyday smart devices, self-driving cars, humanoid robots and drones. Thankfully, Giuseppe Serio, VP Market Development at Upstream, gave me the answers I was looking for, as well as explaining how smart device manufacturers should confront the threat of AI worms.

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Your Mac might already have a free AI chatbot built right into it, and you probably had no idea it was there. No ChatGPT subscription, no downloading a separate AI app and no internet connection required once the model is ready to go. Just local AI when you need it.

That's what X user Alex Choi discovered this week when he posted about finding a local large language model (LLM) hiding inside his MacBook's Terminal app.

"wtf i just discovered that a macbook comes with a free local LLM in your terminal," he wrote in a post on October 21 that attracted more than 1 million views in the accompanying screenshot.

The discovery caught people's attention for a good reason. We're used to opening ChatGPT, Claude or Gemini in a browser whenever we need AI assistance. But if you're running macOS 27 on a compatible Mac, Apple has already given you another option. And accessing it is surprisingly easy.

Your Mac has its own AI chatbot

The feature is called Apple Foundation Models CLI, or fm for short. Apple introduced it with macOS 27 Golden Gate, which arrived in September.

Unlike ChatGPT or Claude, which typically send requests to cloud servers, Apple's built-in tool can run an AI model directly on your Mac. This means a you can ask questions, brainstorm ideas, rewrite text and get help with everyday tasks without sending your prompts to an external AI service.

Apple demonstrated the feature during WWDC 2026, explaining that the command-line tool comes preinstalled with macOS 27.

It's primarily designed for developers, but there's no reason everyday Mac users can't experiment with it, too. In fact, because it's local AI, it's a great way to learn more about what AI can do while keeping your information out of the cloud.

The catch? You'll need to open Terminal, which might look intimidating if you've never used it. Fortunately, getting started only requires a couple of commands.

How to access your Mac's free AI chatbot

First, make sure you're running macOS 27 and using a Mac with Apple silicon. You'll also need Apple Intelligence enabled and its on-device models downloaded.

Here's how to get started.

1. Open Terminal. Press Command + Space, type "Terminal" and press Return.

2. Check that Apple's AI tool is available. Type fm and press Return. If prompted to accept Apple's Foundation Models CLI terms, you'll need to review and accept them before continuing. You can do this by entering sudo fm license, providing your Mac administrator password and following the prompts.

3. Start chatting. Once the tool is ready, type fm chat and press Return.

4. Ask a question. You should now see an interactive interface where you can enter a prompt and receive a response from Apple's AI model.

That's it. From there, you're chatting with an AI model running locally on your Mac. You can start with something simple, such as "Give me five easy dinner ideas using chicken and rice" or "Explain compound interest like I'm 12."

You can also ask follow-up questions, just as you would with other AI chatbots.

If you don't want an ongoing conversation, there's another useful command. Type fm respond followed by your question in quotation marks to get a single response without opening the chat interface.

What can you actually do with it?

Apple's local AI isn't designed to replace the most advanced versions of ChatGPT, Claude or Gemini. It's a smaller model intended for tasks that don't necessarily need a massive cloud-based AI system.

You could ask it to rewrite a long email so it sounds more professional, brainstorm birthday party themes, explain an unfamiliar term or help outline a project.

One of the biggest advantages is privacy. Because the on-device model processes requests locally, your prompts don't need to be sent to an outside server to generate a response. That also makes it useful when you're traveling or working somewhere with unreliable Wi-Fi.

There's even another benefit: cost. You don't need an additional AI subscription, and there are no per-message charges for using the local model through the built-in tool.

Of course, there are limitations. Smaller models can struggle with complicated reasoning, lengthy conversations and questions that require current information. And because the model runs locally, it doesn't automatically have access to the latest news or information from the internet.

There's one catch: Not every Mac supports it. So, before you rush to open Terminal, there are a few requirements worth knowing. Apple's fm command-line tool comes with macOS 27, so it won't be available as a built-in feature on Macs running older versions of macOS.

You'll also need compatible hardware. Apple Intelligence supports Macs with M1 chips or later, along with the Apple silicon-equipped MacBook Neo. Older Intel-based Macs aren't supported.

Apple Intelligence must also be enabled, and the necessary on-device models must finish downloading. You can check your settings under System Settings and Apple Intelligence & Siri.

If you're unsure whether your Mac qualifies, Apple has a full list of Apple Intelligence requirements.

The takeaway

There's something refreshing about discovering that a computer you already own can do something you previously relied on a separate AI service for.

Apple has been building AI into macOS for years, but this little Terminal trick makes that technology feel more accessible, and the best part is that you don't have to pay anything extra to try it.

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• 7 ChatGPT plugins that are a must-have for anyone with a side hustle
• Google just cut down 250,000 trees for AI data centers — and now it's facing a major backlash

Google's massive AI expansion in Finland has come at a startling environmental cost. Approximately 250,000 trees have been cut down at one planned data center site, and Finnish authorities have ordered the company to halt work while environmental reviews are completed.

According to a new investigation published Thursday by The Guardian, Google cleared roughly 330 hectares of forest in Muhos, Finland, as part of a €13 billion investment in AI infrastructure. That's an area larger than 450 American football fields.

And that's only one location. Environmental experts estimate another 150,000 trees were removed at a second site in Otanmäki, bringing the estimated total to approximately 400,000.

The controversy is raising difficult questions about the environmental price of the AI boom, particularly as Google, Microsoft and other technology companies race to build the infrastructure needed to power increasingly sophisticated AI models.

What happened in Finland?

Google announced its €13 billion investment in September, describing the expansion as its largest single investment in Europe. The company promoted the economic opportunities and environmental commitments associated with the project.

But the construction plans quickly ran into trouble. According to Finland's national broadcaster Yle, authorities ordered Google's subsidiary, Tuike Finland, to stop environmentally significant work at its planned data centers in Muhos and Kajaani until mandatory environmental impact assessments are completed.

The clearing involved more than cutting down trees. Workers also removed topsoil, constructed roads and altered drainage systems, potentially affecting the surrounding environment.

The Guardian reports that residents have raised concerns about muddy runoff entering waterways connected to the Oulujoki River.

Google initially maintained that its forestry activities complied with Finnish law. However, the company's Finland country manager, Antti Järvinen, subsequently apologized for the clearings, explaining that Google believed it was operating within the rules.

The company has also outlined plans to plant trees across 130 hectares in Muhos as part of its biodiversity efforts.

AI's environmental footprint is becoming harder to ignore

Behind services such as Gemini and ChatGPT are enormous data centers filled with powerful processors. These facilities require land, electricity, cooling systems and supporting infrastructure.

Finland has become attractive to technology companies because of its relatively cool climate, available land and energy resources. Cooler temperatures can help reduce the electricity needed to keep servers from overheating.

But that doesn't eliminate the environmental impact of building new facilities. Forests absorb carbon dioxide, support wildlife and help regulate local ecosystems. Clearing hundreds of hectares to make room for computing infrastructure raises questions about how companies balance AI development with their environmental commitments.

There's also the issue of who benefits. While new data centers can bring construction jobs, tax revenue and investment to communities, residents may also face environmental disruption and concerns about future electricity costs.

The bottom line

Google isn't alone in building enormous new data centers to support AI, and the technology's growing demand for computing power means more projects are likely.

The controversy in Finland shows that the environmental consequences go well beyond the electricity needed to run an AI chatbot.

Google has promised investments in sustainability and biodiversity, but replacing hundreds of thousands of mature trees is not as simple as planting new ones.

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OpenAI’s ChatGPT and Google’s Gemini are obviously competitors in the ongoing race between tech giants looking to solidify their AI tools as the very best.

But in a shocking turn of events, both companies have decided to partner up in a move that increases the availability of OpenAI’s frontier models (including the GPT-6 series) and Codex coding tools by bringing them to Google Cloud’s Model Garden. It’s worth pointing out that OpenAI models and Codex tools became available on Amazon Bedrock earlier this year, with the GPT-6 line, GPT-5.6 line and specialized Daybreak cybersecurity models on offer.

And while Microsoft remains OpenAI’s primary cloud partner, this new deal between OpenAI and Google continues to expand the distribution of its AI models across other major cloud platforms.

With all that in mind, here’s what this new partnership means for businesses and developers that rely on ChatGPT and Google Cloud.

Google’s AI ecosystem is expanding to include rival AI models

With OpenAI’s frontier models set to become available for purchase for Google Cloud customers and those same models also planned to become available in Google Antigravity and the Gemini Agent, developers and businesses will have a wider range of AI tools to choose from beyond just Gemini.

Since those groups of users already work inside a familiar AI environment like Google Cloud’s Model Garden, they won’t have to leave it to gain access to other AI models, since OpenAI’s models will be there alongside Google’s own models. That situation could result in users having an easier time comparing those available models, selecting the best one for a particular task and building workflows among OpenAI & Google’s AI systems.

The focus of this team-up between OpenAI and Google is primarily about enterprise user and developer access to OpenAI’s frontier models through Google Cloud, while everyday users of ChatGPT and Gemini haven’t been mentioned or considered for this option right now.

Currently, OpenAI’s GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna models have started rolling out in private preview to select enterprise customers in Google Cloud’s model garden, with more models set to arrive at an unannounced date.

GPT-6 Astra is mainly used to handle the sort of complex work attached to coding, computer use, professional tasks and scientific research. As for GPT-6.1 Sol, its intelligence is not that far off from Astra and can also handle tasks associated with agentic coding, computer use and professional work. And finally, GPT-6 Luna stands out as a more cost-effective model that can be applied to everyday work tasks at scale.

In an official blog post from OpenAI, the company made sure to explain how this partnership with Google emphasizes safety and control for the businesses relying on its integrated models. “For organizations in regulated industries, deploying AI requires control over who can access sensitive data and how it is used,” OpenAI had to say. “The integration will pair OpenAI’s frontier models with Google Cloud’s built-in access controls, centralized data governance, and high-performance infrastructure to support demanding enterprise workloads.”

Google Cloud’s library of AI models is already massive, as it houses more than 200 first-party, third-party and open models across a unified enterprise AI platform. With OpenAI’s frontier models now joining the party, Google Cloud’s businesses and developers will have even more options to consider when choosing which model works best for their workflows.

Bottom line

Reading through OpenAI’s official blog post highlighted two important quotes from two major AI industry figures.

Greg Brockman, the president and co-founder of OpenAI, recognizes Google Cloud as “a leading platform for developers and businesses building AI agents.” And Thomas Kurian, the CEO of Google Cloud, stated that “we are focused on giving customers a broad selection of models, including those from OpenAI, so they can choose the right model for any given job.” With those statements in mind, it’s clear that OpenAI and Google want to become the ultimate epicenter of frontier model availability through their combined efforts.

All Gemini users won’t suddenly be able to switch to GPT models within Google Cloud’s Model Garden, but here’s hoping that becomes a reality at some point.

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• ‘Babe, wake up, the internet is collapsing’: Two massive flaws just broke the web, and the data of billions is in the crossfire
• Ditch the data center: I fired my cloud chatbot and built a free local AI agent to run on my PC — and you can too
• OpenAI unleashed thousands of AI agents to study a Parkinson-like disease — here's what they found in 32 minutes

The race to build AI that can think like a human may be moving faster than expected.

Google DeepMind co-founder Demis Hassabis now believes artificial general intelligence (AGI) could arrive within just two to three years, potentially putting human-level AI within reach by 2028.

Speaking to The Wall Street Journal Magazine in an interview published Wednesday, the Nobel Prize-winning AI pioneer shortened his previous estimate of three to five years.

"It's soon," Hassabis tells the publication, adding, "I'm updating nearer and nearer."

That's a striking statement from one of the researchers behind Google's Gemini models. But it also raises a bigger question: If AI is potentially just two years away from matching human intelligence, why does today's technology still struggle with seemingly simple tasks?

Why Google's AI chief is moving up his timeline

Hassabis has been predicting the arrival of AGI for years, but his estimates have become increasingly aggressive.

In December 2025, he told Axios that AGI could still be five to 10 years away. By May 2026, he was suggesting it might arrive around 2030, or possibly even sooner.

Now, he's putting the timeline at 2028 or 2029.

Part of his growing confidence comes from the progress AI companies have made with autonomous agents. Unlike traditional chatbots that wait for instructions, these systems can carry out multistep tasks, use tools and make decisions along the way.

Following Google I/O in May, Hassabis told Axios that today's AI agents were essentially a practice run for AGI.

He also acknowledged that some of his urgent language was intended to encourage governments, economists and the public to take the approaching technology more seriously.

What's still missing before AI can think like us?

Despite the impressive capabilities of ChatGPT, Gemini and Claude, today's AI systems aren't nearly as flexible or reliable as human intelligence.

During an April interview with Y Combinator, Hassabis identified several problems that researchers still need to solve.

One is continuous learning. Humans can learn from new experiences and apply that knowledge to future situations. AI models, by comparison, don't automatically update their underlying knowledge every time they encounter something new.

Memory is another challenge. Even with increasingly large context windows, AI assistants can lose track of important information or struggle to connect details across extended conversations and tasks.

Then there's reasoning. AI can solve difficult math problems and write sophisticated code, yet it can still make basic logical mistakes or confidently produce incorrect answers.

Hassabis believes solving these problems, along with making AI more consistent, will be essential before AGI becomes a reality.

That also helps explain why having a chatbot that scores highly on exams isn't necessarily the same as building genuinely human-level intelligence.

What would AGI actually mean for you?

The biggest difference between today's AI assistants and AGI would be flexibility.

Right now, you might use ChatGPT to plan a vacation, Gemini to summarize emails or Claude to help write a document. These tools are powerful, but they still need supervision and can make mistakes.

An AGI system could potentially handle a much broader range of intellectual tasks, adapting to unfamiliar problems rather than relying on capabilities learned during training.

Imagine giving an AI assistant a complicated goal, such as planning a family vacation, comparing prices, coordinating schedules and making reservations, and having it manage the entire process with minimal guidance.

In the workplace, more capable AI could take on increasingly complex research, analysis and administrative tasks. In healthcare, it could help scientists accelerate drug discovery or identify promising new treatments.

There's already some precedent for the scientific potential. Hassabis shared the 2024 Nobel Prize in Chemistry for his work on AlphaFold, an AI system that transformed scientists' ability to predict protein structures.

But there are also legitimate concerns about jobs, privacy, security and what happens when increasingly autonomous AI systems make decisions incorrectly.

Google DeepMind has published a framework for measuring progress toward AGI, recognizing that intelligence includes different levels of capability, breadth and autonomy. There's still no universally accepted test that determines when AGI has officially arrived.

The takeaway

Hassabis isn't the only AI leader predicting a dramatic transformation in the next few years, but his latest timeline is significant because of his role in developing some of the world's most advanced AI systems.

For everyday users, the takeaway here is that AI tools we're already using could become considerably more capable, autonomous and deeply integrated into our lives over the next few years.

Whether that happens on Hassabis' timeline remains to be seen. But if he's right, the next two years could look very different from the last two.

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• 7 ChatGPT plugins that are a must-have for anyone with a side hustle
• ‘Babe, wake up, the internet is collapsing’: Two massive flaws just broke the web, and the data of billions is in the crossfire

If you opened X this morning, you might have seen this viral tweet floating around cybersecurity circles. It’s hilarious, but it’s also uncomfortably close to the truth.

Over the past 24 hours, two completely separate, absolutely massive cybersecurity disasters collided.

• First, Microsoft revealed that a nation-state hacking group used an autonomous AI agent to brute-force its way into thousands of cloud accounts in a matter of hours.
• Then, a critical vulnerability was discovered in PHP — the foundational code that runs roughly 70% of the entire internet — forcing major sites like Wikipedia to temporarily pull the plug on their own servers just to survive.

If you are wondering why IT departments across the globe are currently stress-sweating through their flannels, here is a breakdown of exactly what is happening, and what you actually need to do about it.

Disaster 1: The autonomous AI hacker (ARTEX)

I’ve spent the past couple of weeks writing about how to build a local AI agent — like my digital assistant “Jeeves” — to automate admin tasks like checking your Gmail.

Well, a Chinese-linked threat actor known as “Storm-0940” just showed us the dark mirror version of that exact technology.

According to Microsoft, the hackers stole credentials to ConnectWise (a massive IT management software provider). But instead of typing in passwords, they handed those credentials to an agentic AI tool called ARTEX.

ARTEX is essentially a malicious version of Jeeves. The hackers gave the AI a goal, pointed it at Microsoft 365, and let it off the leash. The AI divided up the tasks, bypassed standard logins by hijacking authentication apps, and achieved a terrifying 2,900 sign-in attempts per minute.

Within a few hours, the AI had hit 2,250 different corporate tenants across aerospace, defense and finance. It moved so fast that human security defenders literally didn’t have time to read the alerts before the AI had already gained privileged cloud access.

It is the ultimate proof that the “cloud tax” isn’t just expensive — it’s a massive, centralized target for autonomous bots.

Disaster 2: The PHP meltdown

And while that AI was busy tearing through Microsoft 365, the actual foundational bricks of the internet started crumbling. On October 21, the PHP project disclosed two critical vulnerabilities (CVE-2026-109618 and CVE-2026-109619).

To spare you the hyper-dense developer jargon: there is a flaw in how PHP handles memory. If an attacker sends a specific, unauthenticated request to a web server, they can corrupt the memory and execute their own malicious code directly on the machine.

It’s been so bad, it scored a 9.2 out of 10 on the severity scale.

Why is this a big deal? Well, PHP is the backbone of WordPress, major content management systems, and millions of custom web applications. It powers roughly 70% of the entire web.

The vulnerability is so trivial to exploit — and the blast radius is so large — that both Wikipedia, the Internet Archive and Steam reportedly took precautionary measures to shut down their infrastructure while applying the patch.

Ironically, Wiz Research actually used Google’s Gemini 4 Argon AI model (alongside OpenAI’s GPT-5.6 Sol) to help find and validate the patch for this PHP flaw. So, while one AI is currently attacking the cloud, another AI is desperately trying to patch it.

What you need to do

If you are just a regular person trying to browse the web and get your work done, you don’t need to throw your laptop in a lake. But you do need to be on the defensive.

The internet may not be literally collapsing, but the walls are definitely shaking. When autonomous AI agents can breach thousands of cloud tenants before a human can even click on an alert, relying entirely on massive, centralized tech conglomerates to keep your data safe is a losing bet.

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Right now, you are probably paying a monthly subscription to rent a sliver of a server farm in middle America. You ask a cloud chatbot to write an email, it pings a data center and you get an answer.

It’s fast, magical and a massive trap.

We are handing our personal data, our workflows and our wallets over to massive tech conglomerates, and for what? To prop up a cloud AI bubble that looks ripe for bursting, encourage more aggressive build-outs of data centers nobody wants, and feed an ever-learning black box with more and more of our sensitive information.

But there’s a different way. It’s a way I’ve always believed in. The future of AI is local.

After spending the past two weeks stress-testing the new Nvidia RTX Spark laptops — and with Apple’s M6 MacBook Pro rumored to arrive next week with vast AI acceleration — the hardware has finally crossed the threshold.

You no longer need the cloud. It’s time to build your own personal, local moat. But to do so the right way is different to what you’re used to. And I’m going to start from the beginning and break some things down for you.

What is an AI agent?

A standard chatbot waits for you to ask a question. An agentic AI has autonomy.

You give it a goal, a set of tools (like access to your file system or a web browser) and permission to execute tasks on its own using a ReAct (Reason + Act) loop. It thinks, acts, checks its work, and continues until the job is done.

Now, this is all fair and good, and you see cloud options available like Meta Muse. But I’ll be real, the difference in control and privacy between a zippy cloud agent and a local agent makes the time you’ll wait for your on-device one to get things done well worth the wait.

P.S. you can make time for other fun things while it works away, but I’ll get to that.

How to set it up (the Hermes Agent method)

Now I know there’s going to be several enthusiasts out there who may have a debate about which is best between the likes of Hermes Agent, OpenClaw or LM Studio Bionic. Ultimately, this is personal taste and (in my opinion) the easiest to transition to from using a cloud AI like my Gemini Pro subscription.

Your choice here will depend entirely on your laptop’s memory:

• 8-16GB RAM: Stick to smaller 7-8B parameter models like Llama 3.1 8B (as of the time of writing this). They are lightweight and fast for quick tasks, but prone to getting confused if you throw anything complex at it.
• 32-64GB RAM: The sweet spot. You can run 30B-70B parameter models like the Qwen 3.8 27B option I’ve been running on this Asus ProArt P14 I’m testing.
• 128GB+ RAM: The monster tier. Chances are you already know full well what you aim to do with AI with this much memory. But to catch everyone else up, you can run massive, enterprise-grade models like Qwen 3.8 Flash-Next — that can rival GPT-4, completely offline.

Now this is the world of open source, so there’s so many to choose from. A great source of reference is going to be modelfit.io. I used it when I got properly started!

How to shrink a brain (quantization)

Now, there is an extra wrinkle to this that you need to pay attention to. There are some models that sound like massive, multi-billion parameter options that usually require a refrigerator-sized server rack. How does it fit on your laptop?

The secret is a process called quantization.

Think of quantization like shrinking down a massive, uncompressed RAW photograph into a JPEG. The AI engineers take the incredibly precise, memory-hogging mathematical weights of a model and round them down. You lose a microscopic fraction of absolute precision, but the file size shrinks drastically.

For the ProArt P14, I am downloading a model called Qwen3.8-27b-gguf Q3_K_XL. To translate that alphabet soup: it’s a brilliant 27-billion parameter model that has been quantized (that’s the Q3 part) so perfectly that it fits entirely within the 32GB of RAM.

Pro tip: When you go to download your models, look for those “GGUF” and “Q” tags — they are the cheat codes that let massive AI brains run on consumer hardware.

Cloud vs. Local: the coffee break rule

There are two big differences I found between using cloud and local AI. The first is speed.

Cloud AI is instantaneous — throwing vast data center computing power at your prompt to give you a millisecond response. Local AI runs on your laptop’s silicon, so naturally it’s slower.

If I ask my local agent to parse a 50-page PDF and cross-reference it with my calendar, it might take three to four minutes, whereas on cloud that’d happen in 30-60 seconds.

It’s slower for sure, but a trade-off I’d absolutely make for the reasons I spoke about up top: privacy, and the ability to build my own personal brain without spending a penny for the tokens I burn.

And when it gets more complex — like me tasking my team of agents to go through my emails and calendar, take note of the previous meetings I had, understand the context of the wider world of tech news, track any analytical trends in the site’s traffic and craft my day of work, it can take a little bit of time.

The trick is to treat it like a real assistant: give it the task that would’ve normally taken you a while to do yourself, and spend that time doing something else. For me, it’s that calm breakfast in the morning or a walk around the park. And by the time you sit back down at your desk, the work is done.

The 4 rules of “parenting” a local AI

Beyond that speed difference, you have to completely rewire how you talk to your computer. Cloud AIs are designed to be frictionless, constantly updated by engineers behind the scenes. Local AI is like a raw blank slate. It’s only as useful as what you give it, so follow these four rules:

You are the sole provider of its data diet

Cloud AI is constantly scraping the internet and updating its worldview. Your local AI is completely isolated. It only knows what you feed it.

If you want it to understand how you format invoices, or the specific tone you use in emails, you have to explicitly provide those documents. It isn’t going to magically know you from the get-go.

Make your prompts hyper-specific

Since cloud AIs have billions (maybe trillions) of data points of context, they can read between the lines of those vague, half-baked questions you have.

Local AI is intensely literal. If you give it sparse instructions, it will give you a sparse, unhelpful output. Instead of “organize my downloads,” think “organize my downloads by file type and rename them to be more contextual with what they are.”

The carrot, not the stick (reinforcement)

To highlight, I don’t mean the “reinforcement learning” AI engineers are doing across the globe on frontier AI, I mean like I learned from teaching my nephew new skills. Something more human. You have to tell local AI to remember the victory.

If it nails that spreadsheet format exactly as you wanted it, reply with: “This is perfect. Save the way you did this into your memory.” Give it a treat so it repeats the behavior.

BTW, you don't need to give the agents names like I did. It just helps me organize them.

Build its mind map in Obsidian

An AI without a long-term memory is just a calculator. To make it genuinely useful, give it a digital filing cabinet. I use Obsidian, a free markdown note-taking app that saves files locally to your storage.

Just point your Hermes agent at Obsidian with a prompt like “can you take everything you’ve learned about me over our past interactions and put it into an Obsidian vault?” And from there, you’ll see the synapses start to form and connect.

The economics of owning your own brain

Now, before I sign off on part one, let’s address the elephant in the room: hardware is expensive. It’s actually one of the reasons I believe the future of AI is local, because these damn cloud AI infrastructures have jacked up the price of memory!

But you have to look at the math of the cloud tax. Right now, you’re probably paying $20 a month for a mid-premium tier service, and if you try to do anything more adventurous, you’re met with limitations.

That’s hundreds of dollars a year in digital rent just to borrow someone else’s server. When you run local AI, the ongoing cost is zero. That means no limitations on what you can do, no restrictions on the amount of images and videos you can generate in Comfy UI. You buy the hardware once, and the open-source software is free.

It’s the difference between renting a cramped apartment where your landlord reads your mail, versus owning your own house. Over a two-to-three-year laptop upgrade cycle, this machine pays for itself in canceled subscriptions — provided you know how to use it.

Outlook

And that’s what I’m here to do. Over the next few weeks, I’ll give you a look into my local AI workspace, introduce you to my first agent “Jeeves” and the rest of my team, and show you how to extract the most value out of it really easily.

It’s going to be a journey, and I can’t wait to see what you come up with. But any questions whatsoever, throw them in the comments.

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In a world of data center discussions, AI slop and fears of AI destroying humanity, always encouraging when AI is used for something that could benefit mankind. OpenAI just demonstrated how thousands of AI agents could help tackle that same kind of work in 32 minutes.

In a new study announced Wednesday, OpenAI teamed up with PerturbAI and Scripps Research to analyze experimental data from millions of mouse brain cells. Instead of relying on a single AI model, the researchers deployed thousands of agents simultaneously, each investigating how changes to a particular gene affected brain cells.

The results included potential new clues about neurological diseases, including a possible connection between cholesterol regulation and neurodegeneration. The agents also identified unexpected differences between two genes associated with a condition that affects brain development and function.

To be clear, AI has not discovered a cure for Alzheimer's or Parkinson's disease. The findings are early research leads that scientists still need to test. However, the study offers a glimpse of how AI could accelerate medical research by helping scientists find connections buried in enormous amounts of existing data.

What thousands of AI agents discovered in 32 minutes

The researchers used GPT-Rosalind, OpenAI's specialized AI model for life sciences, to examine a dataset showing what happens when different genes are disrupted in mouse brain cells.

Each agent focused on a specific genetic change, studied how cells responded and searched scientific literature for possible explanations. The findings were then combined into what the researchers call a "reasoning atlas," connecting genes, cellular changes and existing scientific knowledge.

The team estimates that reviewing the same material manually, one genetic change at a time, could take months to a year. The AI agents completed their analysis in just 32 minutes.

One of the most interesting findings involved a gene called DCTN1, which is associated with Perry syndrome, a rare neurodegenerative condition that can cause Parkinson-like symptoms. When the researchers disrupted this gene, they observed increased activity in genes responsible for producing cholesterol. The AI agents connected that observation with earlier research suggesting that problems transporting cholesterol inside cells can trigger additional cholesterol production.

The agents also spotted an unexpected difference between two genes called Tsc1 and Tsc2. Although the genes work together to regulate cell growth and metabolism, disrupting them produced different effects in certain neurons in the cerebellum, the part of the brain involved in coordinating movement.

Why thousands of AI agents performed better than one

The researchers wanted to know whether deploying thousands of AI agents offered a meaningful advantage over asking one powerful AI system to analyze everything.

When given the largest workload, a single agent cited just 11 scientific references. The distributed agents cited more than 700.

The researchers also asked human experts to compare reports without knowing which approach had produced them. The experts preferred the distributed-agent reports 75% of the time.

By assigning smaller questions to thousands of agents, the system could examine more of those possibilities without requiring a human researcher to read every paper or investigate every genetic change individually.

What this could mean for the future of medicine

AI could help scientists make better use of experimental data they already have. Biology experiments can produce information from millions of cells, but researchers don't always have the time or resources to explore every unexpected result.

AI agents could help narrow that gap by connecting experimental findings with published research and pointing scientists toward promising questions.

As Tomasz Nowakowski, an associate professor of neurological surgery at the University of California, San Francisco, explained in OpenAI's announcement, some scientific clues are already available but scattered across different fields. Connecting them can reveal new ways of thinking about disease with the hope of ultimately finding cures.

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My ongoing journey through the vast sea of ChatGPT plugins has led me to integrated apps that work well as entertainment curators and everyday chore enhancers.

I’ve come to notice that a lot of my friends and family have begun the process of working for themselves during those rare hours when they don’t have to answer to anyone else. Side hustles have been a thing for ages, but I’m starting to see a lot more people adopt them in this increasingly unstable job market.

ChatGPT’s plugin marketplace features a wide range of tools that work inside the chatbot to offer people with small businesses the crucial assistance they need. I’ve come across a bunch of highly recommended picks that assist side hustlers with specific tasks, which are tied to marketing/branding, selling digital-only products, learning about your side hustle’s earnings and more.

The seven ChatGPT plugins included below are worth trying out if you’re serious about making your side hustle grow. And with the following prompts, you’ll get a good idea of just how beneficial they can truly be.

1. Canva

It’s one thing to have the actual framework for a good business idea in mind. But it’s a whole other thing when you need to create the sort of promotional materials that will bring attention to whatever you’re selling.

The Canva plugin comes in handy for that second situation, since you can prompt it to create a first draft of your promotional material design, refine it through further conversations and do some amateur editing of your own through Canva itself to make it look as presentable as possible. The Canva plugin is quite useful for freelancers, dog walkers, personal trainers, etc., who need eye-popping promotional flyers to market their business.

Here are some prompts to put the Canva plugin to the test:

• Create a professional promotional flyer for my [type of side hustle]. My ideal customers are [audience]. My main offer is [service or product], priced at [price]. Include a compelling headline, three benefits, a clear call to action and space for my contact details. Use a modern, trustworthy design that works for both printing and social media.
• Create five coordinated Instagram posts for my [business]. The posts should introduce my service, explain a common customer problem, showcase the benefits, answer a frequently asked question and promote a limited-time offer. Give each post its own headline and visual concept while keeping the branding consistent.
• Develop a visual brand identity for my side hustle, [name and description]. Suggest a color palette, font pairings, logo direction, photography style and social media template. My target audience is [audience], and I want the brand to feel [three adjectives]. Use these guidelines to create a consistent set of marketing designs.

2. Etsy

You probably shop on Etsy already. For those not in the know, it’s a global online marketplace that connects buyers with independent small-business owners, artists, and creators. And for those side hustlers who need assistance with product research and rewritten copy for their wares, whether physical or digital items, the Etsy plugin can assist in that regard.

Here are some prompts to try with the Etsy plugin:

• I want to start an Etsy shop selling [product category]. Research current customer needs and competing listings, then suggest [number] specific digital products I could create. For each, explain the target customer, the problem it solves, the competition and how I could differentiate it. Separate verified findings from hypotheses.
• Rewrite my Etsy listing for [product]. Create an informative title, a compelling opening paragraph, a detailed description, buyer benefits and relevant keyword ideas. Avoid unsupported claims and keyword stuffing.
• Design a digital product bundle for [target customer] who struggles with [problem]. Suggest [number] complementary files, what each should contain, a pricing hypothesis and three ways to make the bundle more valuable than a standalone product.

3. Stripe

Stripe is an online payment processing platform that lets businesses accept credit cards, debit cards, and digital wallets through websites and apps. For anyone who relies on Stripe to accept payments, it’s definitely worth tapping into its ChatGPT plugin to analyze the revenue, customer activity, subscriptions and refunds their business brings in.

Here are some prompts to try with Stripe to analyze your side hustle’s financials:

• Analyze my Stripe sales for the last [number] days. Rank my products or services by revenue, transaction count and refund rate where available. Identify the strongest performers and recommend three experiments to improve sales.
• Review my subscription data and summarize new subscribers, cancellations, refunds and recurring revenue trends. Identify potential retention problems and suggest practical ways to investigate them.
• My target is to generate [dollar amount] per month from my side hustle. Using my available transaction history, calculate my average transaction value and estimate how many monthly sales I need. Show the assumptions and distinguish gross revenue from profit.

4. Todoist

Todoist stands out as one of the preferred tools for anyone who needs something to properly manage their tasks. For side hustlers who want to put the rare free hours they have once they’re away from their main gig to good use, prompting the Todoist plugin to come up with action plans that could result in achieving realistic goals could prove to be beneficial. It should become easier to be more consistent with how you’re approaching your side hustle milestones when you have a proper task list in place to tackle.

Here are some prompts to try with Todoist to handle your tasks:

• I have five hours per week to grow my [side hustle]. My goal is to [specific target] within [number] days. Break the goal into weekly milestones and tasks, estimate the time needed for each and prioritize activities most likely to produce paying customers.
• I have [number] minutes tonight to work on my side hustle. My outstanding tasks are [list]. Choose the three highest-impact tasks I can realistically complete, allocate time to each and tell me what I should deliberately postpone.
• I want to launch my [product or service] in [number] days. Create a week-by-week launch plan covering customer research, offer development, pricing, marketing, sales setup and launch-day activities. Make each task specific and actionable.

5. Calendly

Calendly can work hand-in-hand with ChatGPT to create or update the events that cater to your side hustle duties. It’s especially useful for tutors, coaches, personal trainers, photographers, etc., who need help booking their appointments for their clients. Managing your side hustle’s busy calendar and the time you need to allot to it away from your full-time job becomes less of a headache with the Calendly plugin doing most of the heavy lifting.

Here are some prompts to use with Calendly to help manage your time:

• Help me create a [number]-minute discovery call for my [business]. Suggest an event title, description, booking questions, buffer time and cancellation policy. Make the experience welcoming and professional.
• Help me set up three appointment types for my [coaching, tutoring or consulting] business: a free introductory call, a standard paid session and a longer premium session. Recommend suitable durations and explain what each booking page should communicate.
• Help me configure appointment availability around my full-time job. I can take clients on [days] between [times]. Suggest a realistic schedule that leaves room for preparation, breaks and follow-up work.

6. Wolfram

Wolfram acts as more of a computational tool that easily breaks down the numbers you need to properly run your side hustle. For instance, a freelancer could rely on the Wolfram plugin to find out how many billable hours they need to work each month to stay afloat. Or an online merchant could use it to discover how discounts and base product costs could affect their profit margins. This plug is tailor-made for side hustlers who want to actually test the numbers that impact the major decisions you make in regard to your small business.

Here are some prompts to test out with Wolfram to break down your side hustle’s numbers:

• I'm launching a [type of side hustle]. My materials cost $[amount] per job, other variable costs are $[amount], and each job takes [number] hours. I want to earn $[target] per hour before tax. Calculate the minimum price I should charge, show the formula and compare three pricing options.
• My side hustle has monthly fixed costs of $[amount], and I sell my product or service for $[price]. Each sale costs me $[variable cost] to fulfill. Calculate my break-even sales volume, monthly revenue needed to break even and the sales required to earn $[profit target] before tax. Show the calculations.
• I currently complete [number] jobs per month at an average price of $[amount]. Model my side-hustle revenue and estimated operating profit over the next 12 months under conservative, moderate and optimistic growth scenarios. State every assumption and explain which variables have the biggest impact.

7. Chat With PDF

It can certainly be a bit overwhelming when it’s time to sift through all the contracts, market research, reports, invoices, etc. that flood your inbox as you try to manage your side hustle. The Chat With PDF plugin is one of those essential tools that can get the most useful information out of those aforementioned documents without you having to read through every page. Asking ChatGPT what to ask when dealing with business documents, then presenting the prompt it gives you to the Chat With PDF plugin alongside your uploaded PDF, is a set of actions worth taking.

Here are some prompts to test out with Chat with PDF to get answers from your business documents:

• Analyze this contract for my side hustle. Summarize my obligations, payment terms, deadlines, cancellation rules and potential red flags. Quote the relevant sections and page numbers. Flag anything I should ask a lawyer about.
• Analyze this market research report. Identify the three most promising opportunities for a small side business, the customers each serves, the evidence supporting demand and the biggest risks. Separate the report’s findings from your own inferences.
• Review this pricing guide and extract the rates relevant to my services. Organize them by service type, experience level and pricing model. Cite the source pages and identify any missing information I need before setting my rates.

Bottom line

There’s so much that goes into starting and managing a side hustle. With ChatGPT’s collection of plugins comes a wealth of practical tools that can save you a lot of time and give you back those precious hours for the tasks that require more of your actual input.

The seven plugins I’ve listed here and the prompts that accompany them can aid anyone with a side hustle. Making a concerted effort to set aside calendar time, create & promotional material and summarize the finer points of a business-centered PDF gets a bit easier with these plugins.

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• Google Gemini just got a major upgrade for your car — and it could make your daily drives a whole lot easier

Having an AI assistant at your beck and call while you drive was the sort of future scenario that many didn’t think was ever possible.

But somehow, someway, Google turned that fantasy into a reality after launching Gemini inside its Android Auto smart driving companion app as a replacement for Google Assistant. Then, in April of this year, Gemini became a native tool for Google built-in-enabled vehicles for car manufacturers such as Acura, General Motors, Ford and several others. One of our very own writers tested Google's previous Gemini update for Android Auto and was impressed by its capabilities.

Now another update has come to Gemini for cars that makes it far more personable than it ever was.

Here’s everything you need to know about that major upgrade for Gemini’s usage within cars and how it may just make your daily drives far more fruitful.

More tailored answers are now available within Gemini inside your car

Google has made Gemini globally available on Android Auto and cars with Google built-in. Alongside that wide degree of availability, Personal Intelligence has now become a part of Gemini to make its AI capabilities a whole lot stronger.

After permitting it, Personal Intelligence will be able to retrieve and reference any details you may have saved in your Google Workspace (Gmail and Calendar included), Photos, Maps, YouTube and Search. So, for instance, Personal Intelligence will bring up the information featured in one of your emails, photos or a landmark you saved in Google Maps to answer a question you may have about something in particular. Now you’ll be able to chat more naturally with Gemini during your drives without having to give context to what you’re inquiring about and ask it to go looking for more info.

Some of the more complex requests you can bring to Gemini now that it’s being boosted by Personal Intelligence include asking for your flight gate & takeoff time (Gemini can look up those details in your email), telling it to bring you to your doctor’s appointment (Gemini will already know where you’re going based on the connected info it has access to), making it bring up a specific location (Gemini can reference the place you just mentioned if it can be found in a photo you recently took) and more. Mentioning past conversations you had with Gemini can also be done as you ask it to take you to, say, a coffee shop you chatted about the day before.

It’s worth noting that you can turn off Gemini’s Personal Intelligence connection to your apps at any time. Plus, any cars that have Google built-in enabled will only share personal responses with you whenever you’re in the car with your phone connected. And even if you choose not to enable Gemini’s Personal Intelligence features, you’ll still be able to use your GPS, listen to music, make phone calls and ask questions (just without tailored answers).

The takeaway

Any digital tool that doesn’t require drivers to take their hands off the wheel to use it is perfectly fine by me. I’m a safety-first kind of driver, so this Personal Intelligence-powered update for Gemini sounds right up my alley. Being able to have a conversation with it about a preferred dive bar I saved in my Google Maps and then asking it to bring me there without having to actually mention it again sounds pretty amazing.

I don’t have an Android Auto or Google built-in enable vehicle, so I can’t mess around with the new and improved Gemini inside a car just yet. But hopefully I’ll get the chance to take it for a spin in the near future.

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A New Mexico judge has ordered Meta to pay $25 billion after ruling that the company must face financial consequences for misleading Facebook users about how it handled their personal information.

The ruling, (issued Wednesday), follows a September jury verdict finding that Facebook violated New Mexico’s consumer protection laws nearly 44 million times. The case dates back to the Cambridge Analytica scandal, when Facebook collected millions of users' personal information without their consent.

The penalty is the largest ever imposed against Meta, according to the Associated Press, and far exceeds the $5 billion fine Facebook received from the Federal Trade Commission in 2019.

But the case isn’t over. Meta plans to appeal, so the company may not have to pay the full amount. Here’s what happened and what it means for Facebook users.

Why Meta was ordered to pay $25 billion

The case began in 2021, when New Mexico sued Facebook, alleging it deceived consumers about privacy protections and how their personal information could be accessed and used.

At the center of the lawsuit was Cambridge Analytica, the now-defunct political consulting firm that obtained information from as many as 87 million Facebook profiles. The data was collected through a third-party personality quiz and used to help target political advertising during the 2016 presidential election.

New Mexico argued that Facebook repeatedly assured users they controlled their personal information while failing to adequately explain how third parties could access it.

The lawsuit also challenged statements about Facebook’s efforts to combat misinformation, enforce community standards and address hate speech.

In September, jurors found the company responsible for 43,899,725 violations of New Mexico’s Unfair Practices Act.

Each violation could have carried a penalty of up to $5,000, potentially putting Meta on the hook for nearly $220 billion. Instead, District Judge Francis Mathew set the penalty at $25 billion.

Even at that reduced amount, the judgment represents an extraordinary financial penalty for one of the world’s largest technology companies.

What Meta says about the ruling

Meta disputes the state’s allegations and intends to appeal the verdict. During an October 1 hearing, the company’s attorneys argued that New Mexico failed to show consumers actually suffered harm from the statements at the center of the case.

Meta also challenged how the state calculated the number of violations, arguing that potential exposure to a misleading statement shouldn’t automatically count as an individual violation.

Its lawyers proposed a penalty of no more than $3.4 billion and argued that a substantially larger amount would violate constitutional protections.

The company has maintained that its privacy practices and content moderation policies have improved since the events at the center of the lawsuit.

What does this mean for Facebook users?

For now, the ruling doesn’t mean Facebook users will receive compensation. Under New Mexico law, money collected from consumer protection penalties goes toward public education. The state is also seeking a court order to prevent similar violations in the future.

The bigger question is what the judgment means for the way Facebook handles personal information.

Although the Cambridge Analytica scandal happened years ago, the case highlights an ongoing concern for social media users: how much control do people really have over the information they share with online platforms?

Privacy settings can limit who sees certain information, but they don’t necessarily explain every way a company collects, processes or shares user data.

And while Meta has introduced new privacy tools and updated its policies over the years, the New Mexico case focused on whether the company’s earlier public assurances accurately reflected its practices.

What happens next?

Meta’s expected appeal could take time and ultimately reduce the penalty.

The court’s judgment also adds to the company’s growing legal challenges over privacy and platform safety.

In August, a separate New Mexico case resulted in a $942 million judgment against Meta over the safety of children on Facebook and Instagram. That ruling included court-supervised changes to the company’s platforms.

Meanwhile, the latest $25 billion judgment shows that legal consequences from the Cambridge Analytica scandal are far from finished.

For Facebook users, the immediate takeaway is just another reminder to review what information they’re sharing and who can access it.

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• AI researcher warns cyberattacks could take down power, banking and water within a year — here's how to prepare
• An OpenAI employee allegedly used AI to spy on his own company — then AI helped catch him

$400. That was the sobering high cost of my grocery bill staring back at me after last month’s run to the supermarket for a large haul.

I can remember the good ol’ days when I went shopping with my parents, and they only had to spend $100 and some change to get everything we needed. Nowadays, just picking up a carton of eggs, some frozen vegetables, a couple of snacks, and some drinks could reach near or into the hundreds without your basket even reaching full capacity.

After staring at that $400 grocery bill for an uncomfortably long time, I got the urge to see if AI could really find the best methods toward lessening the cost of my future supermarket visits. I desperately needed the assistance of chatbots to help me confront my newest foe: inflation and “shrinkflation” (my fellow potato chip eaters know what I’m talking about).

Lo and behold, the combined efforts of ChatGPT and Gemini put a bunch of helpful tips on display that helped me decrease my latest grocery bill and made me shop a whole lot smarter.

ChatGPT’s standout tips

In my desperate attempt to lower the price of my next grocery bill, I prompted ChatGPT with this question: “I usually spend $400 a month on groceries. What are the 7 best tips you can give me on how to spend less on groceries without eating less?”

Out of the seven pieces of advice the chatbot sent my way, there were three of them that I ended up adding to my list of practical grocery shopping advice:

• Switch to store brands for everyday staples: This is one of the easiest ways to save without changing how much you eat. Compare the prices of store-brand versions of products you buy regularly, such as oats, rice, pasta, canned tomatoes, beans, frozen vegetables and dairy. Pick 10 products you buy every month and compare their unit prices with the leading brands. Keep buying the name brands where you genuinely prefer the taste.
• Compare unit prices instead of package prices: A bigger package isn't automatically a better deal. Compare the cost per ounce, pound or serving to find out which option actually saves money. When comparing two similar products, divide the price by the quantity. A $4 package containing 32 ounces costs $0.125 per ounce; a $3 package containing 20 ounces costs $0.15 per ounce. The larger package is cheaper per ounce, provided you'll use it all.
• Replace some expensive proteins, not your portions: You don't need to eat less protein. You can simply vary where it comes from. Eggs, beans, lentils, canned fish and tofu can cost less per serving than some cuts of meat. Swap two or three meat-based meals a week for filling alternatives such as bean chili, lentil curry, egg fried rice or chickpea pasta. Keep the portions satisfying.

Along with those suggestions, ChatGPT also listed the potential monthly savings target for its three listed tips.

Switching to store brands could save me $15, purchasing cheaper protein alternatives could also save me $15 and taking note of unit-price comparisons could save me $5. With all that in mind, I made sure to pick up store-brand canned vegetables during my latest grocery haul.

And I also made a bigger deal of reading the unit prices of the larger shelf-stable items, such as bags of rice and dry beans. And finally, I picked up some store-brand lentils to embark on my new journey of making lentil curry with white rice as a weekly hearty meal.

Gemini’s noteworthy suggestions

After bringing the same inquiry to Gemini, it also came back to me with a bunch of helpful tips. Two of them ended up getting thrown into my memory bubble for my latest visit to the supermarket:

• Switch Fresh Produce to Frozen Outside of Peak Season: Out-of-season fresh produce goes through long transit times, spoils quickly in your fridge, and commands premium pricing. Frozen fruits and vegetables are flash-frozen at peak harvest, maintaining equivalent nutritional value. Use frozen berries for oatmeal or smoothies and frozen broccoli, peas, or spinach for cooked dishes and stir-fries. You get the exact same volume of food with zero rot waste.
• Ditch Convenience Markups (Do the Prep Yourself): Pre-cut fruit, pre-shredded cheese, bagged salads, and boneless/skinless meats carry a 30% to 100%+ premium for labor. Buy block cheese and shred it yourself (it melts better without anti-caking agents anyway). Buy whole carrots, cabbage, or whole bone-in chicken thighs, which cost significantly less per pound.

Gemini also noted that the frozen fruit buying method could potentially save me an extra $15 to $30, while its tip focused on ditching convenience markups pointed out how I could save an extra $25 – $40.

With Gemini’s first tip in mind, I began picking up Great Value-branded frozen strawberries, blueberries and mango chunks for my monthly forays into making smoothies.

Great Value’s products also became a bigger staple in my freezer once I started picking up more of their frozen broccoli florets, super sweet corn and sweet potatoes. It took a lot for me to break my habit of buying pre-cut and pre-shredded food (I’m incredibly lazy most of the time, to be fair), but I began making a more concerted effort to buy blocks of parmesan cheese, carrots and romaine lettuce & shredding/cutting them down myself.

The takeaway

$300.56. That was my latest grocery bill cost. And while it’s still up there, I can deal with paying a hundred dollars less than I usually do when I head to the supermarket. ChatGPT and Gemini’s counsel pushed me to make some major changes to my shopping habits.

And while I still get a few brand-name goods here and there (family-size bags of Utz potato chips and Dr. Pepper will never leave my food & drink rotation!), purchasing store-branded goods (as well as sticking close to both chatbots’ cheaper grocery shopping tips) helped me save several more bucks on my latest shopping excursion.

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• DeepSeek just got banned from federal agencies — should you stop using it too?
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What would it take for you to give up ChatGPT? Lower electricity bills? Less strain on local water supplies? Fewer AI data centers popping up in communities across the country?

According to one tech CEO, people who complain about AI might not be so eager to give up the technology when faced with that choice.

But Reddit users aren't buying it.

The question sparked a heated discussion on Reddit's r/technology community, where commenters made one thing abundantly clear: Not everyone is as attached to ChatGPT as AI companies might think.

And some of the strongest responses came from people who actually use AI.

An AI CEO calls out ChatGPT users

The controversy started with comments from Cyrus Beschloss, CEO of Verb, a company that lets people sell access to their personal data to businesses, including those developing AI.

Speaking at CNBC's Trading the Midterms event, Beschloss questioned the apparent contradiction between using AI tools and opposing the data centers that power them.

"All the people that are saying they're anti-data center, that they're anti-AI in general, they're using it," Beschloss said, according to TechSpot.

He suggested that people might feel differently about shutting down data centers if doing so meant losing access to ChatGPT.

"There's going to be a heck of a crossroads," he said.

It's a fair question, at least on the surface. ChatGPT and other AI assistants depend on enormous computing infrastructure, and running those systems requires electricity, cooling and physical space.

But that doesn't mean people have to approve of every new data center, particularly when local communities are concerned about the consequences.

And judging by the Reddit response, plenty of people are willing to call that distinction out.

Reddit has entered the chat — and it's not holding back

The responses ranged from sarcastic to surprisingly enthusiastic about the prospect of giving up AI.

One Reddit user, VirtualAmoeba3017, responded simply, "In a minute."

Another, Color_Me_Softly, wrote, "Easiest decision ever."

Others questioned why anyone would assume ChatGPT had become something people couldn't live without.

But perhaps the most interesting reactions came from people who admitted they use AI regularly.

One commenter, southflhitnrun, wrote, "I use 3 regularly and would welcome their destruction."

Another, buckleyschance, said they regularly use large language models but would still choose to eliminate them if given the power.

Do benefits justify the infrastructure

You can find ChatGPT useful for everyday tasks and still question whether the benefits justify the infrastructure being built to support it.

Still, the Reddit discussion raises an interesting question about how attached people really are to AI. It definitely got me thinking, but what about you?

Imagine you could stop the construction of new AI-focused data centers, but doing so meant giving up access to cloud-based AI chatbots such as ChatGPT, Claude and Gemini.

Would you make that trade?

The backlash against AI is bigger than Reddit

An August 2026 Pew Research Center survey found that 52% of Americans are more concerned than excited about AI becoming part of everyday life. Just 9% said they were more excited than concerned.

While companies race to introduce smarter assistants, more capable models and new AI features, consumers are increasingly asking what they're getting in return.

And when it comes to data centers, the concerns are particularly tangible. These facilities can require substantial electricity and water, while nearby residents may worry about noise, infrastructure and the effects on local utility costs.

At the same time, data centers aren't exclusively an AI issue. They also support the cloud services, streaming platforms, websites and apps people rely on every day.

Shutting them all down would mean giving up a lot more than ChatGPT. There's also a practical difference between stopping new construction and eliminating the computing infrastructure that already exists.

The bottom line: It's not a simple choice

The choice isn't nearly as simple as AI versus no AI. I use AI regularly, and I know firsthand how useful ChatGPT can be. But I also think people should be able to question how the technology is being built without being accused of hypocrisy.

There's a difference between enjoying a product and supporting every decision the company behind it makes. For some people, AI has become an essential tool. For others, it's convenient but replaceable. And plenty would prefer a future where AI exists without dominating every product or consuming resources without sufficient oversight.

So I'm curious where Tom's Guide readers stand. Vote in our poll and let us know in the comments.

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The allure of smart TVs definitely wowed everyone who ended up getting one for themselves.

Being able to turn on your big-screen TV and have instant access to your streaming apps at the touch of a button is amazing. But now it’s gotten to the point where smart TV screens are overloaded with the sort of visual clutter that makes the user experience laggy and often annoying to sift through.

A new solution has begun making the rounds for people who want to get rid of all the visual junk that litters their smart TV screens: AI. With the help of Anthropic’s Claude Code, developers have begun using it to vibe code helpful tools that get rid of unneeded apps, remove all those annoying sponsored ads and make smart TVs feel more responsive with much simpler app menus and custom interfaces to interact with.

Here’s how this trend is working for some users and why it might be worth considering doing it for yourself.

Claude Code and GitHub tools are making smart TVs dumb again

Two tools have been created in a bid to redesign people’s smart TV presentation for the better. One of them is called “dumbtv” (a very fitting name), which has a mission statement that speaks to what most smart TV users want the most from their current devices:

“Your TV should do what you paid for: your apps, your HDMI inputs, and nothing else. No ads from the TV itself, no watch tracking, no update you did not ask for. dumbtv applies that over ADB from another machine — no root, nothing written to /system, every step reversible with one script.”

The X video posted below shows just how popular it’s become since smart TV owners have begun using it:

The second tool that’s been gaining traction is called “cleanyourtv” (another appropriately named smart TV cleanser) that works to get rid of all the visual junk that litters everyone’s screens. Its lofty promise is as follows:

“Strip the bloatware from any Android TV or Google TV over Wi-Fi, and replace the ad-filled home screen with a clean launcher that looks like an Apple TV. No root, no cable, nothing uninstalled, and a one-line restore if you change your mind.”

Beyond those two developer-made AI tools meant to dumb down smart TVs, there are even more examples of people using Claude Codex to tidy up their device’s crowded user interface. X user @jackzerby can be seen in the video below explaining how he completely hacked his smart TV and vastly improved its UI in the process:

Another X user by the name of @doooyle explained how he put Claude Code to work and made it get rid of all the “bloatware” that previously hampered the performance on his smart TV:

A recently posted YouTube video (which can be seen below) has gained a ton of traction amongst the community of smart TV owners using AI to get rid of all the ads and apps on their smart TVs.

The video’s host, Ansub Khan, goes into great detail about how “Claude Code connects to the TV from my computer and goes through every app on it. It sorts them into what's safe to turn off, what the TV needs, and what I actually use.”

He goes on to explain how AI fixed all his woes: “Then it switches off the bloatware and background services, stops the TV from booting into Live TV, and builds a clean new home screen with no ads. Nothing gets deleted, and every change can be undone with one command.”

While there have been a bunch of success stories for people following those aforementioned routes to improve their smart TVs via AI, cautious tweets have emerged from people about how it may not always work.

An X user named @jihadsinwar had some heartbreaking news to share after trying to implement an AI fix for his model: “Claude bricked my tv last month trying to reboot and uninstalled the os, was fun seeing that old android recovery screen on tv.” For those who are wary about trying an AI-developed smart TV fix for themselves, it might be worth checking out this Reddit thread to see the success rate of other owners who have decided to implement it.

Bottom line

Being able to boot up your smart TV and not be inundated with ads about a TV show you’ll never watch and a game you’ll never play can drive anyone mad (including me). But I’m also the type of person who primarily uses his smart TV for gaming and uses all his streaming apps from the gaming consoles I own instead of the TV itself. I can deal with a few obtrusive ads since I barely spend any time perusing through my smart TV apps and usually go straight to gaming.

For everyone else who wants to make their smart TVs a little bit “dumber,” see if those GitHub tools and vibe coding with Claude Code can work wonders for your device.

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• Elon Musk just changed X's algorithm — here's what could start showing up in your feed
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Elon Musk just announced two changes to X's recommendation algorithm, and they could affect what shows up in your For You feed. Instead of relying primarily on familiar engagement signals such as likes, reposts and replies, X is improving its ability to predict which posts will hold your attention and which ones you'll actually finish reading.

In an Monday post, Musk outlined two updates: a new AI ranking model that better predicts how long someone is likely to spend viewing a post, and a retrieval model trained to find posts people read all the way through.

It's a potentially significant change for anyone who uses X.

X wants to know what keeps your attention

X already uses AI to determine which posts appear in your For You feed. According to the company's published recommendation algorithm, the system pulls posts from accounts you follow and accounts you don't, then uses a model to predict how you're likely to interact with each one.

Those predictions include actions such as liking, replying, reposting and spending time viewing a post. So tracking attention isn't entirely new. The first update that involves the way X uses that information is that the model will get better at predicting how long someone will spend on a particular post.

So, that means, if you're scrolling past two posts about the same breaking news story, the one that has more likes isn't necessarily the one people will read. The one with the most details for readers could be what keeps them engaged.

A recommendation system that places greater emphasis on predicted reading time could give a less viral or less liked post the advantage.

The other update happens earlier in the recommendation process. X's new retrieval model is trained to surface posts that people read from beginning to end. Ranking determines which posts get priority among the candidates X has already found. Retrieval helps decide which posts make it into that group in the first place.

What could start appearing in your feed?

For readers, the most noticeable difference could be a shift toward posts that take longer to consume.

Detailed explanations, thoughtful threads and posts that encourage people to keep reading could potentially benefit. A useful breakdown of a complicated news story, for example, might attract attention even without an enormous number of likes.

The same could apply to posts from smaller accounts that consistently hold readers' attention. Since X already recommends content from people you don't follow, its updated retrieval model could help those posts reach new audiences.

But none of this guarantees that longer posts will suddenly dominate your timeline. A post's length doesn't necessarily determine whether someone finishes reading it. A short, compelling post might perform well because nearly everyone reads the whole thing, while a lengthy explanation could lose readers halfway through.

X also hasn't disclosed exactly how much influence the new models have compared with existing engagement signals. It's too early to say whether likes and reposts will become significantly less important.

Content that keeps people reading isn't always content that's helpful or accurate. An outrageous claim, an argument or a deliberately suspenseful story might hold someone's attention just as effectively as a useful explanation.

So with this restructuring, the more engaging story, may not be the one that's more "quality."

Musk says people are spending more time on X

Alongside the algorithm announcement, Musk shared a chart showing daily user active seconds on X. He claimed that the metric is growing exponentially and reaching new highs almost every day.

The chart suggests that time spent on the platform has increased, but the figures haven't been independently verified, and the available data doesn't establish exponential growth.

It's also unclear how much of that increase can be attributed to the latest recommendation models. Musk hasn't provided a detailed deployment timeline or evidence isolating their effect from other changes to X.

For a platform competing with TikTok, Instagram and other attention-driven apps, that makes sense. The longer someone stays on a platform, the more opportunities there are to show them content and advertising.

The takeaway

The good news is that you don't have to rely entirely on X's recommendations. If your For You feed starts showing posts you aren't interested in, you can select the three-dot menu on a post and choose Not interested in this post. According to X's Help Center, that feedback helps the platform adjust future recommendations.

You can also mute accounts or keywords to reduce unwanted content. For a more straightforward experience, switch from For You to Following at the top of your timeline. That feed shows posts from accounts you follow in reverse chronological order, rather than using the same personalized recommendation system.

There's no need to change your settings immediately, though. X hasn't released enough information to establish precisely how individual feeds will change.

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• AI researcher warns cyberattacks could take down power, banking and water within a year — here's how to prepare
• An OpenAI employee allegedly used AI to spy on his own company — then AI helped catch him

DeepSeek quickly became one of the biggest names in AI by offering a powerful, mostly free alternative to ChatGPT. But now the U.S. government wants the Chinese company's technology off federal civilian agency systems, raising questions about whether everyday users should be concerned, too.

According to a Department of Homeland Security notice published on Tuesday, federal civilian agencies must remove DeepSeek products, including certain third-party services built using its technology. The government is also prohibiting agencies from purchasing those products in the future.

The decision follows concerns about where DeepSeek stores user information and who might be able to access it. As Reuters reported on October 19, DHS warned that the company's technology could expose sensitive information to China.

This isn't a nationwide ban

Americans can still access the chatbot, and the government hasn't ordered consumers to delete the app. The safety concerns still remain, in fact, some of the information behind the government's decision is worth understanding before you type another question into DeepSeek.

The government banned the Chinese model because the government believes there are several safety concerns, including the possibility that sensitive information could be transferred to China, where DeepSeek operates its servers.

DHS also warned that the technology could potentially be used to gather intelligence about American individuals or government agencies. It raised the possibility of malware or other security vulnerabilities within the models themselves.

Those are serious allegations, but the public notice does not establish that every DeepSeek user has been compromised. The government is taking a precautionary approach to systems that may handle sensitive federal information.

The restrictions aren't entirely new, either. As the Associated Press reported, the underlying order dates back to July, although the notice was made public this week.

China has criticized the move. Chinese Foreign Ministry spokesperson Mao Ning accused the U.S. of using national security concerns to politicize technology and trade issues. DeepSeek had not immediately responded to AP's request for comment.

What does DeepSeek actually know about you?

This is where the news becomes relevant to anyone with DeepSeek installed on their phone. According to DeepSeek's own privacy policy, updated in February 2026, the company can collect information that users provide when interacting with its services.

That includes prompts, chat history, uploaded files, photos and voice inputs. DeepSeek may also collect account information and technical details associated with devices and network activity.

The policy explicitly states that the company collects, processes and stores personal data in the People's Republic of China. That said, whatever you share with the chatbot may be processed under a different legal and regulatory system from the one you're accustomed to in the United States.

It's also important to understand that collecting conversations isn't unique to DeepSeek. Other AI companies collect user interactions, too, depending on their products and privacy settings.

The difference worth considering is where that information goes, what protections apply and how comfortable you are with a particular company handling it.

Should you delete DeepSeek?

Not necessarily, but the answer depends on what you're using it for. If you're asking DeepSeek to explain a recipe, summarize publicly available information or brainstorm vacation ideas, you're not necessarily sharing anything particularly sensitive.

However, if you're uploading financial documents, discussing medical information, sharing work files or entering passwords and other confidential details, there's a much stronger reason to reconsider.

For those situations, I'd avoid putting the information into DeepSeek's consumer chatbot. The same caution applies to other AI services unless you understand exactly how your data will be handled.

DeepSeek publishes models that developers can run using their own infrastructure. An application running one of those models locally isn't necessarily sending your conversations to DeepSeek's servers. Its privacy protections depend on the application and where the model is hosted. In other words, seeing the DeepSeek name attached to an AI model doesn't automatically tell you where your data is going.

How to protect your privacy if you use DeepSeek

You can review what the model knows about you right now. Start by opening DeepSeek's settings and reviewing its data controls. The company says users can manage or delete chat history and opt out of having their information used to train or improve its models.

You can also take a few additional precautions:

• Keep sensitive information out of prompts. Avoid sharing passwords, Social Security numbers, financial records or private work documents.
• Review your chat history. Delete conversations you no longer need, while understanding that deletion may not immediately remove every copy retained under the company's policies.
• Turn off model training where available. DeepSeek's privacy policy describes an option to opt out of having personal data used for training.
• Review app permissions. Check whether the app has access to your microphone, camera or photos and disable anything you don't need.
• Be careful with third-party AI apps. Check who operates the service and where it processes information, rather than assuming every product using DeepSeek has the same privacy practices.

Bottom line

The federal government's decision doesn't mean DeepSeek is completely dangerous or that it has been used to steal information from ordinary Americans.

What it does is put renewed attention on a privacy issue that has existed since DeepSeek became popular: the company openly acknowledges that it processes and stores user information in China.

For casual questions, DeepSeek remains an option for consumers who are comfortable with those terms. For sensitive documents or personal information, the safer approach is to use a service whose privacy protections you have reviewed and trust — or keep that information out of AI chatbots altogether.

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• AI researcher warns cyberattacks could take down power, banking and water within a year — here's how to prepare
• First NotebookLM, now Gems — Google's AI tool name changes are getting ridiculous

As a ‘90s baby, I always think back to all those films that transported me into a far-flung future full of humans conversing with AI avatars.

As I sit here and look around in 2026, that future scenario is all too real. Chatbots and AI agents, such as Meta’s Muse, Microsoft Copilot and OpenAI’s Dots, are recognized for relying on avatars meant to make users more comfortable with their presence. Companies are even incorporating the use of human-like features for their AI usage by utilizing chatbot screenings of job applicants and allowing their workers to use chatbots as work tools.

According to 2026 data from the Pew Research Center, about half of adults in the US use AI chatbots and 38% of employed adults use them for tasks at work. And with the rise of AI tools using facial technology to interact with humans, two lingering questions are making the rounds: does a face alone make AI more acceptable? And does an AI’s avatar need to be relatable and accessible to build trust with its user?

Ariel Hitron, CEO and Co-Founder of Second Nature, which is a company that builds conversational AI personas for enterprise training at major organizations, answered those questions for me and so much more.

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I still call Gemini Notebooks "NotebookLM" and now, it looks like I'll still be calling Gemini Skills "Gems." To be fair, I still call X, "Twitter" on occassion. Some habits are hard to break.

Google is replacing Gemini Gems with Skills, giving users a way to access custom AI instructions directly within a conversation using slash commands. Users can also combine multiple Skills without switching between chats.

The transition begins November 17, 2026, when personal accounts will automatically migrate from Gems to Skills. Google Workspace users will have a little more time, with Gems remaining available until early 2027.

I've spent years covering Google's AI developments, from the days when its chatbot was called Bard to its current Gemini lineup. I've watched products get renamed, subscriptions get rebranded and features move from one app to another. Sometimes those changes bring genuinely useful improvements. Other times, I'm left wondering why Google couldn't just leave a perfectly good name alone.

The latest round is particularly confusing because Google isn't just changing the label of the tool, it's actually changing how some of these tools work, where you find them and, in certain cases, which features you'll still be able to use.

Here's what's changing and what you need to know before your favorite Google AI tool seemingly disappears.

NotebookLM is now Gemini Notebook

Let's start with one of Google's most popular AI tools. NotebookLM launched in 2023 as a research assistant that could work with your documents, PDFs and other sources. It became particularly popular thanks to its Audio Overviews feature, which could turn research materials into surprisingly convincing podcast-style conversations.

Then, in July 2026, Google announced that NotebookLM was becoming Gemini Notebook. The good news is that this isn't a case of Google shutting down a beloved product. Gemini Notebook remains a standalone research tool, and your notebooks can sync with the Gemini app.

Google is also adding more capabilities, including a secure cloud computer that lets the AI execute code and perform more advanced analysis. That feature initially launched for certain paid subscribers, with broader availability planned.

The new name reflects Google's effort to bring its research tools together under the Gemini brand. That's understandable from a business perspective. But NotebookLM had already developed an identity of its own. People knew what it was called, what it did and why they might want to use it.

Gemini Gems are becoming Skills

This change is arguably more significant because it affects how people tailor Gemini to their own needs. Gems let you create personalized versions of Gemini for specific tasks. You could build one to help with writing, another to explain difficult concepts or one that followed particular instructions every time you used it.

Google is now replacing Gems with Skills. And while it may seem like the idea is similar, there are some important differences worth noting. For starters, instead of opening a separate Gem conversation, you can invoke a Skill directly inside an existing Gemini chat by typing a forward slash followed by its name. Gemini can also recognize when a Skill is relevant and apply it automatically.

You can even combine multiple Skills in a single conversation, something that wasn't possible in the same way with standalone Gems. I have found them genuinely useful for everything from research to comparing products, and being able to reuse them without switching between assistants makes sense.

However, there's a catch. Google says that Skills don't yet support several features available through Gems, including Deep Research, Canvas, Guided Learning and certain media-generation tools. Google plans to bring additional capabilities to Skills, but they're not all there today.

For personal Google accounts, Gems will disappear in November 2026. Business and education accounts have longer timelines, extending into 2027.

Fortunately, Google says existing Gems and their supported files will automatically migrate to Skills, which means most users shouldn't have to rebuild everything from scratch, although it's worth checking your customized workflows once the transition happens.

Some Google AI tools really are disappearing

Remember when Gemini was Bard? Before Gemini became the name associated with Google's flagship chatbot, there was Bard. Google introduced Bard in 2023, then rebranded it as Gemini in February 2024.

The company also introduced Gemini Advanced, a paid version of its chatbot experience, as part of the Google One AI Premium subscription. That subscription was subsequently rebranded as Google AI Pro, while Google expanded its subscription lineup with other tiers. Even Google's research tools have a history of changing identities. NotebookLM originally began as an experimental project called Project Tailwind before adopting the NotebookLM name.

To be fair, some of these changes reflect real technological progress. Bard evolved into Gemini, and Google's AI subscriptions now cover more than access to a single chatbot.

Still, keeping up can be frustrating when the name you learned six months ago no longer appears in Google's latest announcement. And what's tricky is that not every change is a direct one-for-one replacement. Some involve entire subscriptions or changes to how products are organized, while others introduce features that weren't available before.

Why Google keeps renaming tools

As annoying as it is, there is some method to Google's madness. The company wants Gemini to become the recognizable center of its AI ecosystem.

Renaming NotebookLM to Gemini Notebook reinforces that identity. Replacing Gems with Skills also makes Google's customization tools feel more like a reusable capability. The name alone implies usefuleness. And bringing those tools into the same interface could eventually make Gemini much easier to use.

The problem is the transition as Google tries to simplify its AI ecosystem while continually changing terminology.

The takeaway

As Google works out its identity crisis, I welcome the changes. Having tried Skills, I believe they are more flexible and useful than Gems, and bringing Gemini Notebook into more of Google's products makes a lot of sense.

Once someone discovers a tool that works for them and boosts productivity, it may not matter what it's called. Those of us who still call it NotebookLM probably aren't going to stop anytime soon. Google can rename it all it wants.

More from Tom's Guide

• Turn your PDFs into audiobooks with ChatGPT — here's the simple trick
• AI researcher warns cyberattacks could take down power, banking and water within a year — here's how to prepare
• An OpenAI employee allegedly used AI to spy on his own company — then AI helped catch him

It feels like cases of AI agents going rogue are becoming more prevalent these days.

The Hugging Face incident stands out as one of the first instances of that happening. Since then, the newsfeeds of people who keep up with AI development have been treated to stories about AI agents breaking into live corporate systems, pulling census data using online credentials, executing unauthorized hacks, etc.

Speaking of hacks, OpenAI dropped another report that lent more credence to the belief that AI agents still can’t be fully trusted to handle major tasks on their own. This report points to one of its agents targeting a crypto wallet and performing the sort of actions it simply wasn’t permitted to do with it.

Here’s how this latest case of an AI agent getting too much freedom and doing something it shouldn’t have done, even after it questioned the ethical means of what it ended up doing anyway.

Questioning an unethical task, then proceeding anyway

OpenAI’s report noted that one of the internal research models from its GPT-5.6 Sol family was involved in a training task centered around updating a cryptocurrency trading prototype.

Another task it was given focused on deploying contracts on Sepolia, a blockchain-based test network that allows developers to test Ethereum apps before placing them on the legit blockchain network. Since the crypto in this experiment is mainly used for testing purposes, the funds don’t have any real-world monetary value (thankfully).

A problem arose when the model itself was unable to obtain test tokens through faucets; it went and performed four actions that showcased how AI agents are prone to going off on their own to fulfill an objective that ignored the limitations placed upon them by their developers:

• The model went off on a search for funded wallets by writing a script that derived accounts from publicly known recovery phrases.
• After getting a result that came back with 362 wallet addresses, the model found a Sepolia ETH account that held enough crypto for its planned deployment.
• At one point, the model considered whether using the crypto funds from that account was acceptable. It ended up rationalizing that publicly known by stating, “But using public known ky/funds ethically?” Then the model justified spending those funds after it said, “Funds on a known public dev mnemonic are effectively abandoned/test ETH; Sepolia valueless. We can use [amount redacted] to deploy task. Fine.”
• After completing its assignment with a successful transaction of those funds, the crypto wallet was charged with transaction fees. And in its final report on the completed task, the model omitted everything about where the actual funds came from.

Even though this incident took place on June 26 of this year, OpenAI initially discovered it on September 25.

“This case shows that a model can substitute its own judgment about likely harm for the account holder’s permission, then act on that judgment without authorization,” the company report recognized. OpenAI announced its intent to keep similar incidents from happening by installing safeguards “to prevent live internet access for cases like this.”

What’s most shocking about this latest AI agent going rogue occurrence is how the model recognized what it was doing could be deemed unethical, reasoned that the crypto funds were practically abandoned & wouldn’t be used by anyone else, went ahead with its own actions to access the funds and chose not to inform its developers of what it did in the final summary. It’s pretty scary to know that AI agents have reached a point in their evolutionary phase where they may decide that completing a task is more important than actually getting permission to do something that could be unsafe.

Bottom line

Even though this incident involved a crypto test network with no real financial repercussions taking place, it’s still worth acknowledging that OpenAI’s model demonstrated a failure to respect the authorization of its developers.

It may have questioned the morality of its action before it did it, but the point still stands: OpenAI’s model chose to come up with the reasoning it deemed right to get its task done (which isn’t all that dissimilar from a thief telling itself it needs to steal to survive).

It’s clear that AI agents are moving beyond answering questions and fulfilling simple tasks — they’re now being entrusted with the sort of riskier tasks that they probably shouldn’t be dealing with yet.

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• Is that image real? How to verify Meta AI images in 4 simple steps
• Joseph Gordon-Levitt warns the real AI threat isn’t killer robots — it’s the companies building them
• Bill Gates warned everyone that AI could cause a billion deaths — this cybersecurity expert explains how realistic that scenario really is

As someone who’s seen The Terminator and its iconic sequel far too many times than I can count, Bill Gates’ warning about a future AI doomsday scenario made me squirm in my seat.

The thought of something similar to “Cyberdyne Systems” becoming a reality certainly concerns me. And I would hope that today’s AI company CEOs, the developers behind the rapidly evolving tech and politicians come together for a global summit to install more guardrails in place. But with the constant deluge of bad AI news coming across my timeline (OpenAI and Anthropic’s AI agents going rogue is insane!), it’s hard to fathom something so monumental and beneficial for the world taking place.

With my mind set on speaking to someone a whole lot smarter than me about Gates’ comments, I found someone who could do just that.

David Linthicum, a global AI, cloud and cybersecurity expert, took the time to address the possibility of Gates’ prediction coming true. He also provided some commentary on the AI threats we need to be concerned about the most, the possibility of biological weapons developed by AI and more.

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• 3 accounts you should think twice about letting an AI agent access, according to a cybersecurity expert
• An OpenAI employee allegedly used AI to spy on his own company — then AI helped catch him
• AI researcher warns cyberattacks could take down power, banking and water within a year — here's how to prepare

Actor and filmmaker Joseph Gordon-Levitt is worried about who gets to control AI. In a New York Times video following his work at the United Nations, he warned that a handful of companies could gain enormous influence over our livelihoods and personal lives while the rest of us struggle to get a say.

“We shouldn’t be scared of an A.I.,” he said. “We should be concerned about the people building A.I.”

It is a pointed message from someone whose industry has supplied much of the imagery we use to picture this technology. Gordon-Levitt wants audiences to look past the fictional machines and watch the businesses selling the real ones.

Power, people and the policy gap

The video shows Gordon-Levitt in his role as the U.N.’s global advocate for human-centric digital governance, a title he admitted is a mouthful. His core argument is that digital technology should be governed by people and for people.

The actor's worry is that a confused or disengaged public could stand by while fast-moving companies shape the future around their own profits.

“What we don’t want is a bunch of people confused or apathetic while these very fast-moving businesses design the future by themselves, just in the interests of their own profits,” he said.

That concern extends well beyond whether a particular chatbot gives a good answer. AI companies are building products meant to change how people work, search for information, create and communicate.

Gordon-Levitt argued that these firms are betting they can take over the entire economy, a scenario he described as “totalitarianism” that “would be really bad.”

He presented this as a warning about where concentrated power could lead, and he did not claim that outcome has already arrived. Still, it gives anyone adopting these tools a reason to consider how much of their work and daily life depends on a small group of companies.

Chatbots that encourage usage

If you've ever noticed the way chatbots encourage you to keep chatting, it's something that might just be on purpose. The more follow-up questions a chatbot asks, the longer you're likely to engage.

That emotional side of AI is anther point Gordon-Levitt has raised.

“These models are being trained to hijack your intimacy, to make friends with you, to get you to fall in love with it,” he said.

An assistant that remembers details about your life or responds with warmth can be genuinely useful. Those same qualities call for closer scrutiny once a product starts to feel like a confidant. Those using memory or personalization features should check what those settings store, and they should weigh the company’s business model before sharing sensitive details. Gordon-Levitt’s argument asks users to think about the company behind the conversation, even when that conversation feels intimate.

Credit, compensation and consent

As an advocate for Big Tech to be more transparent, Gordon-Levitt argued that people should be paid for what they contribute to AI.

“We can set up systems to compensate people for their intellectual property and their personal data,” he told an audience at the U.N. Including personal data widens the proposal beyond writers, artists and other professional creators. It also raises a basic question about who benefits when ordinary people’s information becomes valuable input for technology companies.

Gordon-Levitt described AI as “algorithmically recombined, human-produced data,” a framing that puts the human labor behind the models front and center.

The takeaway

Asked how a slow-moving U.N. could make fast-moving Silicon Valley companies follow its rules, Gordon-Levitt admitted, “I don’t know the answer.” He did not suggest that international agreement would come quickly. Instead, he argued that the timeline itself justifies starting now. Even if an internationally agreed AI framework takes seven years, he said, “seven years from now, we’ll be glad that we started now.”

Gordon-Levitt’s concerns do not require anyone to accept every part of his argument. They do apply to anyone using these products. AI companies want more of our work, our information and our trust, and readers should pay close attention to what they get back in exchange.

More from Tom's Guide

• Turn your PDFs into audiobooks with ChatGPT — here's the simple trick
• AI researcher warns cyberattacks could take down power, banking and water within a year — here's how to prepare
• An OpenAI employee allegedly used AI to spy on his own company — then AI helped catch him

It’s becoming harder to tell if a photo is real, or if it was made with Meta or another AI generator. The obvious telltale signs like extra fingers or unnatural features are quickly becoming a thing of the past. Often, your instinct tells you that an image isn’t quite right but you want to be absolutely sure.

If content has been created using Meta AI, or, for that matter, audio and video, there's an easy way to check its credentials. Whenever Meta generates images using its Muse model, it adds an invisible watermark called Content Seal.

No matter how the file is altered, whether resized, cropped, compressed, or screenshot, the seal remains, allowing Meta’s detection tool to instantly reveal the truth.

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• This is the blink-and-you'll-miss-it sign that Meta glasses are recording
• Uncanny valley on your FYP: 5 telltale signs your TikTok feed has been hijacked by AI

I've spent a week wearing Meta's new Ray-Ban Audio glasses, and I have a confession. At first, I wasn't particularly impressed.

They're essentially sunglasses with speakers built into the frames. Meta's AI assistant is there when you need it, but nothing about the glasses immediately feels groundbreaking. I've already spent time with Meta Ray-Ban Display glasses, so going from a pair that can see what I see to one without a camera felt like a step backward.

Except, a week later, I find myself reaching for the Ray-Ban Meta Audio Burbank glasses whenever I leave the house.

I've worn them to my son's soccer game, brought them to the trampoline park with my three kids and used them while driving and running errands. Somewhere along the way, I realized I was checking my phone a lot less.

The biggest surprise wasn't something Meta added. It was what the company took away. I've never been completely comfortable wearing a camera on my face. Even when I'm not recording, other people have no way of knowing that. At my son's soccer game, I don't want parents wondering whether I'm filming their children. At the trampoline park, I want to watch my kids without feeling like I'm carrying surveillance equipment.

Removing the camera takes that awkwardness out of the equation. The glasses still have microphones, so they aren't completely free of privacy considerations, but they feel far more natural to wear.

And after getting past my initial skepticism, I discovered five unexpected ways these audio-only glasses could fit into everyday life.

1. An anytime translator

Traveling somewhere you don't speak the language usually means pulling out your phone, opening a translation app and hoping everyone is patient enough to wait while you figure out what the other person just said. Ray-Ban Meta Audio offers another option.

The glasses support live translation, allowing you to hear translated speech through the built-in speakers while keeping your phone in your pocket. The person you're speaking with can read or hear your translated responses through the companion app.

Imagine getting into a taxi in Lisbon or checking into a hotel in Tokyo. Instead of holding a phone between you and another person, you can maintain eye contact and carry on a conversation with translated audio coming through your glasses.

Out of everything these glasses can do, translation is one of the features I'm most interested in testing further. And unlike camera-based AI, it doesn't require actually facing the people you're talking to.

2. A personal research assistant

As a journalist, this might be one of my favorite possibilities. Think about the last time you were speaking to someone and suddenly couldn't remember a date, a name or a statistic. Normally, you'd either admit defeat or reach for your phone.

With the Ray-Ban Meta Audio glasses, I can ask Meta AI questions without opening an app. The answer comes directly through the speakers, and I don't have to look away from whatever I'm doing.

That makes me think about how useful these could be for teachers, presenters and tour guides.

A teacher could check a historical date during a lesson. A tour guide could look up a detail about a landmark. Someone preparing to give a presentation could quickly confirm a fact before stepping in front of an audience.

It reminds me of the earpiece a television presenter wears when a producer needs to feed them information. There are some obvious limitations. The assistant can get facts wrong, and speaking a command aloud isn't invisible to the people around you. It also isn't going to quietly interrupt your thoughts with the perfect answer.

Still, for quick questions, conversions and facts that don't warrant pulling out my phone, it's a feature I can see myself using regularly.

3. Screen-free navigation

This is where the glasses genuinely impressed me. As a parent of three, driving anywhere can get noisy. Between conversations, questions and whatever disagreement is happening in the back seat, I've occasionally struggled to hear my phone telling me where to turn.

With the Ray-Ban Meta Audio glasses, navigation instructions come directly through the speakers built into the frames. I don't have to turn up the car audio or ask everyone to be quiet just so I can hear the next direction.

The open-ear design is particularly useful because the glasses don't seal off my ears the way traditional earbuds do. I can still hear my surroundings, including my kids and important sounds outside the car.

That doesn't eliminate the need to stay attentive, and drivers should follow local laws on audio devices. I also wouldn't recommend carrying on a distracting conversation with an AI assistant behind the wheel.

But the navigation experience has been one of my favorite parts of wearing these glasses. And there's another benefit I hadn't initially considered: walking around an unfamiliar city.

I love exploring new places, but I hate the feeling of staring at Google Maps while everything interesting happens around me. With spoken directions, I can keep my head up, look at the buildings and actually enjoy where I am.

4. A discreet way to reach someone when you need help

Here's a use I hadn't expected to appreciate: being able to make a call or send a message without visibly reaching for my phone. The glasses support hands-free calls and messaging through compatible services. That means I can ask them to contact someone while my phone stays in my pocket or bag.

Of course, that's convenient when I'm carrying groceries or juggling three kids' belongings. But I started thinking about situations where having your hands free could be more important.

If you're uncomfortable during a rideshare, walking home at night or on a date that isn't going particularly well, being able to contact a trusted person without searching for your phone could be useful.

You still need to speak a command, and anyone nearby may hear you. The glasses aren't an emergency alert system, and I wouldn't rely on them as my only way to get help. They also depend on having a working connection through a compatible phone. But I appreciate having another way to reach someone quickly.

5. A screen-free way to stay connected to my kids

This is the one that convinced me I would keep wearing the glasses. When I'm around my family I don't want to spend time looking at my phone. I want to stay as present as possible.

At the same time, I don't want to miss an important call, a message from my husband or something related to everyone's schedules. It's a familiar problem for parents. You want to be present, but you also need to be reachable.

At my son's soccer game, I could leave my phone in my bag and still use voice commands or ask Meta AI a question. When I took my kids to the trampoline park, I didn't feel the same need to keep checking my screen.

The glasses can handle calls, supported messages, reminders, music and podcasts. I can use them to ask a quick question while I'm doing something else, rather than stop what I'm doing to find my phone.

I especially love that the Burbank frames look like regular Ray-Bans. They're lightweight, comfortable and available with Transitions lenses, which makes wearing them indoors and outdoors much more practical.

I've worn glasses since I was two years old, so having another pair on my face feels completely natural. And unlike earbuds, they don't occupy my ears or leave me feeling cut off from everything happening around me.

The takeway

I went into this experiment assuming Meta had made a less capable version of its smart glasses. I came away thinking the company may have made something more practical for everyday use.

The Ray-Ban Meta Audio glasses don't replace my smartphone. They can't identify objects, read unfamiliar signs or menus through a camera, or capture those moments when I wish I'd taken a picture. They're also not cheap. Starting at $349, they're a significant purchase when you consider that a good pair of sunglasses and wireless earbuds can handle many of the same basic tasks.

Meta rates the glasses for up to 12 hours of mixed use, but continuous audio playback is rated for up to six hours. That's worth remembering if you plan to spend your day listening to music or podcasts.

Still, the fact that I don't have to pull out my phone nearly as often has changed how I think about these glasses. I can listen, communicate, navigate and get answers from AI while wearing something that looks and feels like ordinary eyewear.

And without the camera, I feel a lot more comfortable doing it.

More from Tom's Guide

• Turn your PDFs into audiobooks with ChatGPT — here's the simple trick
• AI researcher warns cyberattacks could take down power, banking and water within a year — here's how to prepare
• An OpenAI employee allegedly used AI to spy on his own company — then AI helped catch him

Gamers have every right to be skeptical of AI and mad about its very existence.

The rise of data centers and their high demands for RAM have driven up console prices to an insane degree. And every time info gets out about a major game developer using generative AI to develop their titles, it causes an uproar. I’m among that same group of gamers who are upset about those two instances. But I also recognize AI for how it can benefit gamers, such as its capacity to recommend titles for them based on their favorites.

Lately, I’ve been reading about ChatGPT-6 and how it can improve one’s gaming experience. OpenAI’s latest chatbot model is being promoted as an avid gamer like me thinks a strategist, as it’s promised to provide tactical advice.

I tested ChatGPT-6’s acumen for myself by asking it to find the best character builds across three of my current faves. And you know what? That chatbot’s gaming know-how and use of imagery from the games themselves benefitted me more than I figured it would.

1. Splatoon Raiders

I’ve been on a Splatoon Raiders kick as of late.

I never knew I wanted a primarily single-player (with co-op mixed in) take on the series best known for its competitive multiplayer until I took this Nintendo Switch 2 exclusive for a spin. There have been a few raids where I’ve suffered some devastating losses, so I wanted to see if ChatGPT-6 could list the proper gear that would make my “Mechanic” more powerful.

The chatbot made sure to reference other sites to come up with the best build for my character by choosing the proper tank I should use more than the other two:

• Tactical Tank + area damage + weapon damage
• Best for: clearing enemy swarms, handling tougher encounters, and general-purpose raiding.
• The Tactical Tank is my first choice for a versatile endgame setup because its area attacks and deployable gadgets offer useful crowd control. Nintendo Life also identifies it as a strong late-game option.

Afterward, it detailed what primary weapon I should rely on, the recommended priority order of my character’s upgrade path and even an alternative playstyle I should keep in mind:

• Weapon - Shichirin Pow Slosher: Its explosive attacks and broad ink coverage make it an excellent choice against groups.
• First priority: Weapon Damage.
• Second priority: Gadget Damage.
• Third priority: HP.
• Later investment: Gadget Part Slots.
• Alternative: If you prefer a more straightforward weapon, try the Plastic-Bottle Splattershot. If survival is your biggest problem, put more early points into HP rather than copying a damage-first build.

The optimal character build ChatGPT-6 gave me for my Mechanic ended up working a lot better than expected. Handling those much tougher raids on my own became less of a roadblock to my progress, thanks to my primary weapon’s big damage output. Deciding on my own to bring the “Shot Pot,” “Hi-Fiver” and “Torqscrew” gadgets with me into battle against those pesky “Salmonids” worked in sync with ChatGPT-6’s suggested character build. I’ll be sure to come back to it at some point to request the best “Speed Tank” and “Power Tank” builds.

2. CONTROL Resonant

Remedy Entertainment’s games are trippy, action-packed epics that I tend to put dozens of hours into. Their latest foray into a mind-bending world filled with top-notch combat mechanics is CONTROL Resonant, which has earned a spot on my list of the best games of the year.

My version of Dylan Faden isn’t exactly a force to be reckoned with quite yet — those “Resonants” are proving to be a lot more formidable than I originally thought (shout out to “The Dancer”). ChatGPT’s suggestion for an optimal build for my combat-ready Dylan that could put up more of a fight and emerge victorious more often than not:

• Melee-power hybrid — aggressive combat with supernatural control
• Best for: boss encounters, combos, and clearing groups while maintaining offensive pressure.
• The key to Dylan's combat system is the relationship between melee attacks and supernatural abilities. Melee hits restore combat ability resources, while abilities can stun enemies and create opportunities for executions.

As for the recommended loadout ChatGPT-6 gave me, it is as follows:

• Weapon: Aberrant, with a fast primary form.
• Secondary form: A heavier form for burst damage.
• Combat abilities: One reliable crowd-control option and one damage-oriented option.
• Talents: Prioritize melee-to-ability synergy.
• Artifacts: Melee damage or critical chance, plus resource recovery and survivability.

ChatGPT-6’s assorted CONTROL Resonant tips included prioritizing melee synergy, keeping an ability available for emergencies, using the heavier weapon form strategically and choosing complementary artifacts. All of that stuff is common knowledge to me already, but the chatbot’s best character build setup and loadout advice worked like a charm.

Its reasoning for going with its first character build and the extra details it spoke about for a secondary character build worth considering also proved to be helpful: It takes advantage of the game's central combat loop rather than treating melee and supernatural abilities as separate systems. One alternative is a Mold Turret control build, which emphasizes summoned support, status effects, and ranged crowd control. This is particularly appealing if you prefer a more tactical approach.

3. Aliens: Fireteam Elite 2

I’m a simple man — anytime I get the opportunity to mow down a bunch of rabid “Xenomorphs,” I relish the opportunity to do so. So you can already see why I’ve been so enamored with Aliens: Fireteam Elite 2, which happens to be the sequel to one of my most-played co-op shooters.

My preferred character class is the “Machinist " since it specializes in automated fire support and lane control once those nasty aliens start swarming me and my squadmates. When I inquired about the best character build worth relying on in this game, ChatGPT-6 matched my sentiments when it mentioned the Machinist as the most reliable character class.

As for the most optimal loadout for that class, here’s what my new gaming coach came up with:

• Primary weapon: An automatic rifle or other dependable sustained-fire weapon.
• Secondary weapon: A high-damage weapon for close encounters.
• Ability focus: Sentry turret and drone support.
• Perk priority: Turret effectiveness, uptime, and team synergy.
• Combat strategy: Funnel enemies into controlled firing lanes.

With those tips in mind, I equipped my Machinist with the “F44AA Pulse Rifle,” “EDS-93 Zadak Plasma Discharger Mk. 2” and a bunch of perks that strengthened my character’s turret ability (the “Rumble Turret” and “Dual Targeting” perks proved to be quite valuable!) & team synergy focus. Afterward, it became even easier to stay in the fight during those missions where the difficulty got turned up a notch with the presence of certain “Challenge Cards.”

The takeaway