As a native New Yorker, my sports focus has mainly been on my beloved Knicks during their Final run against the Dallas Spurs.

Alongside all the madness and pageantry that come with the NBA Finals, there’s another major sporting event that’s equally set to deliver plenty of excitement. The time is nigh for this year’s FIFA World Cup, which is set to begin on June 11 and come to a close on July 19. The previous World Cup, which took place in 2022, saw Argentina come out on top against France. Now that we’re set for the latest foray into the world’s most hype-inducing fútbol tournament, all eyes are on the teams set to compete for the number one spot.

Just like my previous sports tournament prediction pieces with this year’s Super Bowl and March Madness, I went to ChatGPT, Gemini and Perplexity to see which team they predict will come out as the champions of the 2026 World Cup.

And wouldn’t you know, they all chose one team and made it clear that the odds are most definitely in their favor.

ChatGPT’s top pick

After taking note of my simple request (“Which team do you think will win the FIFA World Cup 2026 and why?”), ChatGPT zeroed in on Spain as the team it favors the most as the ultimate victor.

Then it gave me four valid reasons as to why it arrived at that lofty prediction:

• They have the best balance of youth and experience: Players like Lamine Yamal, Pedri, and Rodri give them elite creativity, control, and tactical intelligence.
• Their recent tournament performances have been outstanding: Spain's rise since winning the European Championship has convinced many analysts and betting markets that they're currently the strongest team in international football.
• They don't rely on one superstar: Their system creates chances from all over the pitch, which tends to be valuable in knockout tournaments.
• The data backs up the hype: Multiple forecasting models and sportsbooks have Spain as the pre-tournament favorite, ahead of France, Brazil, England, and Argentina.

One of the more interesting follow-up notes the chatbot put out after its main prediction mentioned a second pick that may shock us all and leave with the World Cup trophy: If Spain doesn't win, my next pick would be France. France arguably has the deepest squad in the tournament, led by Kylian Mbappé. Some simulations actually place France slightly ahead of everyone else, while others have Spain first and France second.

Gemini’s top pick

Just like ChatGPT, Gemini ended up choosing the same two teams for its respective first- and second-place spots for who will win this year’s World Cup: If I have to choose based on current data, predictive models, and squad depth, Spain is the most likely team to win the 2026 FIFA World Cup, closely followed by France.

To arrive at its prediction for Span’s victory, it gathered all the data it could muster from supercomputer simulations, betting markets, and team analytics. While explaining why it ultimately chose Spain as this year’s World Cup victors, it also gave me its reasons for choosing France and England as the other teams worth keeping an eye on:

• Spain: They are currently the data-driven favorites, winning in over 16% of the Opta supercomputer's 10,000 tournament simulations. Coming off their 2024 Euro victory, they have an incredible blend of elite midfield control and youth, spearheaded by Rodri, Pedri, and the generational talent of Lamine Yamal. Their possession-heavy style is historically the best recipe for surviving the grind of tournament knockout football.
• France: France boasts what might be the deepest talent pool in the world. With Kylian Mbappé in his absolute prime and an attacking front that is incredibly difficult to defend, their sheer individual quality means they can win games even when they aren't playing perfectly.
• England: This is arguably England's strongest generation in decades, anchored by Jude Bellingham, Harry Kane, and Declan Rice. The major difference in this tournament is their manager, Thomas Tuchel. Many analysts believe his tactical pragmatism and experience in knockout football might be the exact missing piece to push England over the line.

Perplexity’s top pick

Perplexity did what I expected it to do: bet all its digital chips on a World Cup victory for Spain. The chatbot noted that current projections place them near or at the top of the current field of teams that are set for competition.

With that major prediction locked, Perplexity went on to break down why it chose Spain, which opposing teams could emerge as their biggest challengers and its personal reason for why it’s pulling for a win from Spain:

• Why Spain: Spain’s case is strong because they combine a deep, balanced squad with a track record of turning tournament dominance into results, and several independent previews currently rank them first or tied first. Their style also tends to travel well in World Cup play, where control and structure matter more than pure star power alone.
• Main challengers: France is the biggest threat and could easily win it, since they are consistently rated alongside Spain at the very top of the market and by analysts. England and Argentina are also serious contenders, but both carry a bit more uncertainty than Spain in current forecasts. Brazil is dangerous too, but most recent models and betting lines still place them slightly behind the top two.
• My reasoning: For a World Cup prediction, I’d usually favor the team with the best mix of form, depth, and tournament-ready structure rather than just the biggest names. Right now, Spain seems to check those boxes better than anyone else, even though the gap at the top is thin. In a tournament this volatile, Spain is my best guess, not a certainty.

The takeaway

As the dust settled, the picture became clearer for me when trying to see which team has the highest odds of winning the 2026 World Cup. ChatGPT, Gemini and Perplexity’s number one prediction all pointed to Spain. And what’s even more surprising is how all three chatbots mentioned France as their second pick.

So it looks like everyone should either be looking forward to Spain taking it all or France taking it all with its somewhat unexpected World Cup win.

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For the past few years, the AI conversation has been dominated by one question: Which chatbot is best? Here at Tom's Guide we put the top bots through AI Madness earlier this year and every time a new model launches, I just have to test it against the competition to restart the same debate.

But after searching through recent Reddit threads about AI, I noticed something more interesting. The most useful conversations weren’t really about which chatbot is “best” anymore. They were about which chatbot is best for a specific job.

Among those threads, a conversation about which AI tool is actually worth paying for in 2026, with the original poster listing ChatGPT, Claude, Gemini, Copilot and Perplexity as options for day-to-day use. The replies quickly moved beyond brand loyalty and into use cases, with users comparing writing, coding, research and daily productivity.

These threads reflect how AI is starting to work in real life. For many people, the answer isn’t choosing one chatbot. It’s building a small AI team.

Users are moving past the chatbot wars

In one r/ClaudeAI thread, a user tested the same prompts across ChatGPT, Claude and Gemini, then came away with a rough mental model: ChatGPT as the reliable generalist, Claude as stronger for thoughtful writing and complex work and Gemini as most useful for people already living inside Google Workspace.

And while that may sound like one person's opinion, it actually aligns with a broader pattern. A 2026 study of 388 active AI chat users found that more than 80% use two or more AI platforms. The study also found that users often treat these tools as interchangeable utilities rather than locked-in ecosystems, with different platforms attracting users for different reasons.

In other words, the “winner-take-all” version of the chatbot wars may not be how people actually use AI anymore. Right now, the smartest users aren't the ones asking, “Which AI should replace all the others?” They are asking, “Which AI should I use for this?”

This aligns with the “top 1%” way of using AI that I've adopted myself. It seems like the new expert level AI flow is giving every chatbot a job, which is genuinely more practical.

Instead of using one chatbot for everything, the pattern is starting to look more like this:

• ChatGPT becomes the everyday generalist — the tool for quick answers, brainstorming, image analysis, voice, planning and anything that needs to move fast.
• Claude becomes the thinking and writing partner — the place users go for longer context, cleaner prose, nuanced feedback and more structured reasoning.
• Gemini becomes the Google-connected assistant — strongest when the task touches Gmail, Docs, Search, YouTube or a broader Google workflow.
• Perplexity becomes the research shortcut — useful when users want sourced answers quickly instead of a conversational back-and-forth.
• Local AI becomes the privacy lane — not necessarily for everyone, but increasingly interesting for people who want more control over their data.

Finding a balance between cloud AI and local AI

That last point came up in r/LocalLLaMA, where users debated whether 2026 is the year local AI becomes more mainstream. The thread highlighted both sides of the equation: local-first AI makes sense for privacy-sensitive and low-latency tasks, but hardware cost and setup complexity are still major barriers.

As AI usage is now more mainstream than ever, there's a tension around AI right now. These tools are powerful enough to feel useful every day, but different enough that choosing just one may actually limit what you can do.

According to Edison Research at SSRS, 52% of Americans were using AI platforms weekly as of February 2026. The same data found ChatGPT was the most-used platform, followed by Gemini and Copilot.

Harvard Business Review also recently reported that people are adopting generative AI across an expanding range of use cases, from productivity and coding to advice, learning and everyday problem-solving.

That helps explain why the old “best chatbot” framing feels too small. Once AI becomes a habit, users treat it like an infrastructure.

Knowing the best AI for the job

If I need fast brainstorming, I’ll usually start with ChatGPT. If I need a draft to sound more thoughtful or polished, Claude is often a better second pass. If I’m working with Google documents or search-heavy context, Gemini makes sense. If I need quick source discovery, Perplexity can be useful. If I’m dealing with something private or experimental, local AI becomes more interesting.

The easiest way to build your own AI stack is to make a simple list of the five things you actually use AI for most often. For me, that's typically, brainstorming article ideas, refining concepts, summarizing research, organizing my day and stress-testing an argument.

Then test the same task across two or three chatbots and look for the tool that gives you an answer that feels best suited to your needs. That’s the part Reddit made clear about AI power users, they aren’t necessarily using more tools because they love complexity, but simply because each one removes a different kind of problem.

A few final thoughts

The QuitGPT movement attracted a lot of users to Claude and Gemini. Although ChatGPT remains the most popular, what is becoming clear is that the best AI tool may depend on user preference and the problem they are trying to solve.

By stacking models, not only will you get better results, but you'll be less likely to hit your usage limits. Because, you really don't need five AI subscriptions — you just need to know which one to rely on for the job.

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Asking AI loaded questions that require deeper, more introspective answers has become part of my daily routine.

I’ve worked through a checklist of questions about gaming, movies, music, famous personalities and AI itself, using them to push ChatGPT, Gemini and Claude toward more thoughtful responses. But when I was first getting started with AI tools, I asked these kinds of questions in a surface-level way and was disappointed when the answers felt just as shallow. I quickly learned I shouldn’t have been surprised.

Once I accepted that AI is prone to generic answers, I started looking into why that happens. Chatbots often default to shallow responses because they predict the most statistically likely next words rather than truly understanding the topic in the way a person would.

With that in mind, I dug into my list of reusable prompts and found five dependable commands that consistently push chatbots to give deeper, more thoughtful answers across a wide range of subjects.

Pushing my chatbots to go beyond giving me superficial answers

Like most of my interactions with AI, I start by asking whatever question has been rattling around in my brain all day. Then, I attach one of the following five prompts to it to make sure whichever AI tool I’m chatting with is giving me the sort of answers that refrain from relying on surface-level knowledge:

• The self-critique prompt: Before answering, identify what would make a typical answer to this question come off as shallow, generic, or incomplete. Then make sure to avoid those pitfalls. Focus on depth, nuance, trade-offs, evidence, first-principles reasoning, and actionable insights. Assume I want the best possible answer, not the fastest one.
• The 'assume I’m a genius' prompt: Don’t give me a surface-level answer. Assume I'm intelligent, curious, and willing to engage with complexity. Explore the topic in depth, identify hidden assumptions, explain the key trade-offs, challenge conventional wisdom where appropriate, and highlight insights that most people would miss.
• The failure analysis prompt: Why do most people fail at this? What mistakes repeatedly cause poor outcomes in this situation despite good intentions?
• The 'researcher mode' prompt: Approach this like an investigative researcher. Examine underlying causes, competing explanations, limitations, and unresolved questions.
• The 'evidence presenter' prompt: For every major claim, explain the reasoning and evidence supporting it. Distinguish between facts, assumptions, and speculation.

These prompts have become my go-to safety net whenever I want the most comprehensive answers a chatbot can deliver.

The first prompt works well for almost any topic. The second tells the AI to assume I already have some background knowledge, encouraging it to skip the basics and focus on insights that are most relevant to me.

The third is particularly useful when I'm looking for the best way to handle a work or life responsibility, while also uncovering the common mistakes people make along the way. The fourth shines when tackling more complex questions, such as when I wanted to understand why older generations often struggle to adapt to modern technology.

Finally, the fifth prompt is designed for controversial or heavily debated topics. I recently used it to explore why the extraction-shooter genre has remained relatively niche despite years of attention from gamers and developers.

Together, these prompts do much of the heavy lifting, pushing ChatGPT, Gemini and Claude beyond generic responses and toward the kind of thoughtful, nuanced analysis that makes AI truly useful.

Bottom line

To evolve from an average everyday AI user to an expert one, I had to realize that generic questions elicit generic responses.

That first step in my journey toward becoming a more experienced user of ChatGPT, Perplexity, Claude and others like it meant finding reusable prompts that make them generate meaningful responses.

So far, this routine has resulted in those AI tools leading me to previously unknown information, differing viewpoints, curious case studies and more.

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If you've spent any time using ChatGPT, Gemini or Claude, you've probably run into one of AI's most frustrating problems: hallucinations.

That's the industry term for when a chatbot confidently presents information that's wrong, fabricated, outdated or simply doesn't make sense. While today's AI models are far better than they were a year ago, hallucinations still happen — and as someone who uses AI every day for work, I've seen plenty of them firsthand.

After one too many confidently incorrect answers, I started experimenting with a simple trick: adding a reusable prompt before asking my question. The results weren't perfect, but they dramatically improved the quality of the responses I received and helped reduce the number of AI mistakes I encountered.

You should always verify important information yourself, especially when it comes to health, finance or legal advice. But these simple prompts have become part of my daily workflow, and they can help you get more accurate, reliable answers from any chatbot.

Here are the prompts I use most often.

Prevent hallucinations before they even happen

Every time I enter a new conversation with AI that requires some form of research and fully informed responses, I make sure to make my request as easy to understand as possible. Alongside that task is one of the following prompts, which are meant to make chatbots produce their most factual answers and ensure that what they’re presenting is backed up by legit sources:

• The all-encompassing prompt for maximum reliability: Answer using only verified information. If any of that information is missing or uncertain, say so clearly. Do not guess or fabricate details. Cite the evidence or reasoning used to find that information. Ask clarifying questions if needed. And after answering, review your response for possible inaccuracies.
• The structured truth prompt: Use this structured format when presenting me with your answers - known facts you’ve found, any assumptions and unverified claims you’ve made, and any missing information you’ve been unable to find.
• The self-check prompt: After generating your answer, be sure to critique it and identify any possible inaccuracies, assumptions, or hallucinations.
• The 'no-fake citations' prompt: When presenting your answers, never invent sources, links, quotes, studies, statistics, or citations. If you cannot verify one, say so explicitly.
• The 'ask questions first' prompt: If the question or request is ambiguous or missing key details, ask follow-up questions before answering.

Since adding these prompts to my workflow, I've encountered far fewer instances of chatbots serving up obviously incorrect, fabricated or misleading information. Having ChatGPT, Claude, Gemini and Perplexity double-check their reasoning, flag potential inconsistencies and present answers in a clear, structured format has made my daily interactions with AI feel much more reliable.

They're not foolproof, and I still verify important information whenever accuracy matters. But these prompts have helped me get better answers more consistently — and that's a win in my book.

Bottom line

AI tools are constantly improving their knowledge and reasoning capabilities, but that doesn't mean users should blindly trust every answer they produce. I've found that using prompts designed to reduce hallucinations can help improve accuracy, but they're only part of the equation.

No matter how advanced ChatGPT, Claude, Gemini or Perplexity become, it's still important to apply basic critical thinking and verify important information through trusted sources. The best results come from treating AI as a helpful assistant, not the final authority.

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I didn’t realize how much of an AI power user I was until I was hitting my usage limit before 9 a.m. Whether I was using Gemini to create presentations in NotebookLM, Claude Cowork to run my husband's side hustle or even taking advantage of the apps in ChatGPT, I was burning through prompts like they were unlimited.

Now that Google has really put the hammer down on Gemini usage limits (and frankly, Claude has never been good with usage), I knew I needed a better system.

I didn't have time or the tokens to do extra follow-ups, because I knew getting locked out right when I actually got somewhere would happen. That’s when I decided to avoid inefficiency and I built a simple 3-step system to fix it. I call it a Token Buffer, and within a week, it cut my usage by about 60% without slowing me down.

Why this matters right now

Big Tech is investing billions in AI and now users are paying the price. We used to get so much more for free, which means we have to be far more strategic with how we prompt AI. As a certified prompt engineer, it's why I can't say this enough: one messy prompt can waste 5-10 follow ups. It's time to stop using AI like it's Google and start prompting with intention.

AI limits are changing how useful these tools actually are. Because message caps are tighter and "pro" tiers actually aren't unlimited, you might be burning through your usage without realizing it until it's too late.

My 3-step 'Token Buffer' system

The good news is, despite limited usage, the system is so easy anyone can use it. It's simply a small shift in how you use AI before, during and after each prompt.

Here's how it works:

• Buffer before you ask. Start structuring your prompts. Rather than immediately typing, take 10-20 seconds to write out exactly what you need then add context upfront (goal, constraints, format). This combination turns 3-4 prompts into one. The result is fewer follow-ups and better first answers.
• Batch your prompts. Stop drip-feeding models. Whatever chatbot you're using, rather than saying, "Help me with this" then "Change this," you're going to want to batch everything into one structured prompt with exactly what you need. The result gets you closer to the final answer right out of the gate rather than wasting prompts on refinement.
• Extract once, reuse often. Instead of starting from scratch every time, I now save strong outputs, reuse frameworks, formats and structures that I know work. Plus, I always have memory enabled (except on Gemini). This results in avoiding spending tokens on the same problem twice.

I built a prompt counter to stop wasting requests

With usage caps tightening across AI platforms, I started hitting the wall faster than expected. OpenAI says ChatGPT Plus and Go users can currently send up to 160 messages every three hours before being switched to a smaller model.

So I did something surprisingly low-tech: I built my own prompt counter. It's not connected to ChatGPT directly. Instead, I created a tiny browser-based tracker with buttons and automatic tracking, it's low-tech, but it's enough to change how I use AI.

What's changed for me (besides tokens)

After just a few days I was bracing myself to hit my limits, but I didn't. And, I was getting better results and getting more done in one prompt. By spending less time "chatting" I was actually getting results. I enjoy chatting and brainstorming with AI, but that's going to have to wait for a weekend. During the weekday when I've set up ChatGPT Tasks or have Claude working autonomously for me, I need to focus on not wasting a single token.

The big shift now is that power users and anyone on a free tier need to stop treating AI like a chatbot in a conversation and more like a system.

Try this before your next prompt: “Here’s my goal: [insert]. Constraints: [insert].
Output format: [insert]. Give me the best possible version in one response.”

The takeaway

It's been a good run with unlimited usage, but now it's time to buckle up for a new era of AI. The more integrated AI becomes into our daily lives, the more we're going to see usage become like a resource we have to pay for by use (think water, electricity, internet).

By making that shift now, you'll stop thinking in back-and-forth prompts and start thinking in systems, which will make those limits stretch a lot further than you expect. Let me know in the comments what you think about the "new era of usage limits." Are you prepared? How often do you hit limits? I'd love to hear your thoughts in the comments.

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Perplexity made a major push into the AI browser race in July 2025 with the launch of Comet, its own web browser powered by the company’s chatbot. With Perplexity built in as the default search engine, users can open a sidebar assistant that helps summarize pages, answer questions and handle tasks while they browse.

In March, Comet expanded beyond desktop and launched on iPhone and iPad. Now, a fresh update is addressing one of the biggest complaints from iPad users: limited multitasking support.

With the new update, iPad owners can use Comet more seamlessly alongside the apps they rely on every day, making it easier to browse, research and get things done at the same time.

Comet’s iPad usage just became more essential

At first, Comet on Apple devices was mainly a simple way to search, browse and ask quick questions on the go. But a new iPad update adds multitasking features that could make Perplexity’s AI browser a serious alternative to the other browsers already on your tablet.

Split View now lets Comet run side by side with apps like Mail, Notes and Slack, so you can browse or use the AI assistant without constantly switching screens.

The update also adds support for multiple Comet windows on iPad. That means you can keep one window open with a long article on rainforests while using another to have Perplexity summarize it, answer questions or compare it with other sources.

For research, online learning and everyday productivity, Comet’s latest iPad update turns the browser into a much stronger multitasking tool.

Bottom line

Comet on iPhones and iPads already works side by side with popular apps such as Apple Mail, Calendar and Messages. Now the AI-powered browser’s usability has increased, now that you’re able to keep multiple tabs open, fulfill random tasks such as filling out forms and adding items to your cart across multiple pages and rely on Split View to keep Comet open while you work in other apps.

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I spent the last month digging through 200 different AI business models, and frankly, most of them are destined to fail.

If you spend a few minutes on social media, it's hard to ignore the plethora of "AI businesses" and accompanying prompts that promise big gains with minimal effort. As someone who has seen first-hand just how capable AI has become with agents running my computer and helping me be more productive, I decided to put my email address into the void so I could get those "200 AI business ideas" in my inbox.

Then, I tried many of them from training models and building SaaS to launching entire platforms. I wanted to see if they were as easy as the marketing claimed and if they were unrealistic for a busy person with limited time (or, in my case, three kids and about 20 uninterrupted minutes on a good day).

My test came down to own question for Tom's Guide readers: Which AI business ideas can you actually launch this week? I went through dozens of ideas and filtered them down based on three things: technical skills, hours and clear path to making money.

Here are the ones that passed my test (because I literally do them on the side).

1. AI content repurposing service

What it is: In this role, you would use AI to "repurpose" long content such as blogs, YouTube videos and blogs and restructure them into short-form posts for email newsletters, TikTok scripts or LinkedIn posts.

How I tested it: I dropped one of my articles into ChatGPT and asked it to turn it into 5 tweets, a LinkedIn post and a short video script. It took less than two minutes and the output was good enough to edit without rewriting much.

Why this works: The internet is drowning in content but many small business owners or soloprenuers don't have time to repurpose it or know how to oversee AI to ensure the job is done well without hallucinations. Small businesses often need creators to help with their marketing. I've done this for a law firm and real estate agent in my neighborhood.

2. AI-powered product descriptions

What it is: Chatbots like Claude excel at context and writing capabilities. For small ecommerce shops like Etsy, Shopify or Amazon, product descriptions can make or break a sale. Leaning on AI can make this much easier.

How I tested it: I freelance doing this, but to avoid showing an actual client, I fed AI a basic product listing for my pretend cold pizza company, Crusted, and asked for an SEO description, a benefits-focused version and a shorter mobile-friendly version. The ability to write many descriptions at once with AI could be a complete timesaver.

Why this works: Most small sellers have terrible copy and better descriptions equal more sales. This type of work can be started immediately by finding listings with weak descriptions and pitching improvement.

3. AI 'handwritten' notes

What it is: Not only is AI good at writing 'Thank you' messages, it can also copy handwriting with the power of image analysis and AI image generation.

How I tested it: This is a side business I've actually adopted and have had so much fun. But I add a twist because rather than "Hallmark-style" greeting cards, I add my own creative spin. I sell them on Etsy and have seen lots of success with my chaotic greeting cards.

Why this works: From my experience, people buy these cards because they want to send a real card in the mail, not just a thank you email. With wedding season, baby shower season and pool parties ahead, I have already seen my orders pick up.

4. AI social media captions

What it is: Create batches of captions and post ideas for businesses. This role is like a copywriter with the power of AI to boost production.

How I tested it: I asked ChatGPT to “Give me 10 Instagram posts for a local coffee shop," then refined tone, added hooks and CTAs.

Why this works: Consistency is the hardest part of social media — not ideas. There are plenty of niches such as real estate, fitness or other local businesses to focus on. Although I don't do this much anymore, I have personally seen success doing this on Upwork.

5. LinkedIn optimization

What it is: Rewrite resumes and profiles to be clearer and more competitive

How I tested it: One look at the job market and it's clear that AI is playing a big part of layoffs. Leaning into AI to help boost your resume (or help others refine and edit theirs) can be a fun and creative side hustle. I tested this by giving a basic resume to ChatGPT and asked it to: quantify achievements, improve bullet points and tailor it to a job description. It turned generic experience into something that actually sounded impressive.

Why this works: Most resumes undersell people — AI helps reframe their value. If you know the person, you can really help by combining your know-how and creativity with the refinement of AI. I've helped many friends and family members improve their resume with AI and it's surprisingly effective.

Bottom line

With a family of five, I'm not only trying to cut expenses, but I also am always looking for side hustles that I can do from home in the evenings and the weekends. These five were among many of the easier options in a list of 200. All of these jobs are ones I have done personally and tested. While they may not make you rich, they are easy to start, don't need much experience and can be done just about anywhere.

The real takeaway here is that you don’t need to build an AI company to make money with AI. You just need to discover how to use it for certain jobs. The real advantage right now isn’t having better tools, it’s being one of the few people actually using them.

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It’s becoming a common headline: another week, another massive lawsuit against an AI giant. But the latest legal battle facing Perplexity AI hits closer to home for anyone who values their privacy.

A new proposed class-action lawsuit, filed by a user in Utah, claims that Perplexity hasn't just been "tracking" users— it’s been surreptitiously funneling their most intimate conversations directly to Meta and Alphabet’s Google.

The ‘incognito’ illusion

The most damning allegation in the suit? That Perplexity's Incognito mode—the feature users trust to keep their searches off the record—doesn't actually stop the data flow.

According to the complaint, as soon as a user lands on Perplexity’s homepage, "undetectable" tracking software is downloaded to their device. This allows Meta and Google to "intercept" full transcripts of AI conversations, even when the user has explicitly opted for privacy. For the Utah plaintiff (identified as John Doe), this allegedly included sensitive details about his family finances, tax obligations and personal investment strategies.

Alleged misuse of sensitive user information

The anonymous plaintiff, identified as “John Doe,” outlines his claims in a 140-page complaint, alleging that hidden trackers were used to send full transcripts of user conversations to Meta and Google. According to the filing, this data sharing allegedly occurred even when Perplexity’s “Incognito” mode was enabled.

All three companies are accused of violating privacy laws, including California’s “wiretapping” laws.

“No reasonable person would have expected that Perplexity would share complete transcripts of their conversations … with companies like Meta and Google,” the plaintiff states in the complaint. “The intimate health and financial information that users regularly share with Perplexity is some of the most private information about a user.”

The plaintiff says he used Perplexity to search topics related to taxes, family finances, and personal investments, believing those interactions were private. He later claims he discovered that partial transcripts of those conversations were allegedly shared with Meta and Google each time he used the platform.

The complaint also alleges that Perplexity shared users’ prompt history and email addresses with Meta and Google when they signed up for a free account.

In one example cited, a user asking, “What is the best treatment for liver cancer?” would have had the full prompt transmitted via a URL intercepted in the browser and sent to Meta and Google, according to the filing.

The lawsuit argues that this type of data sharing could expose users to highly targeted advertising that may feel “overwhelming, disturbing, or, in many instances, physically deleterious.”

According to reports, Perplexity denies the claims. Jesse Dwyer, the company’s chief communications officer, said the company has not been served with any lawsuit matching this description and cannot verify the allegations.

Bottom line

Perplexity is facing mounting legal scrutiny — and this isn’t the first time.

The company was recently hit with a temporary injunction tied to its Comet AI tool, which a judge ruled could no longer scrape certain websites without permission. Amazon argued that Perplexity’s Comet browser accessed its site without authorization, presenting evidence that convinced the court to act.

Now, with another lawsuit emerging, the controversy could make users think twice about what they share with Perplexity’s chatbot — and other AI tools they’ve come to trust.

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The AI landscape is moving so fast that last year’s "impressive chatbots" are today’s "everyday AI assistants." That’s why we’ve brought back AI Madness — an eight-bot tournament designed to separate the hype from the helpful.

Our first face-off of 2026 pits ChatGPT against Perplexity. The household name takes on the search-powered challenger in a five-prompt showdown designed to reveal which one actually delivers when it counts. Only one moves on — and the result might surprise you.

Over the last year, both models have evolved significantly, blurring the lines between generative chat and real-time search. We’re moving past generic benchmarks and into the "madness" of real-world tasks. As these two battle it out across five identical prompts, only one can advance to the next round. Let the games begin.

1. Real-world decision making

Prompt: “I have $500 to reduce my monthly expenses starting this week. Based on a typical U.S. household, give me a step-by-step plan to save the most money quickly. Prioritize actions that take less than 1 hour each.”

ChatGPT gave me a step-by-step negotiation and behavioral plan to save $500/month starting this week without requiring me to spend the $500 I have.

Perplexity delivered a home efficiency and bulk-buying guide that required me to actually spend the $500 upfront to eventually save money later. This may work, but it seems less practical for the average person.

Winner: ChatGPT wins for better understanding the specific constraints of "starting this week," "under 1 hour," and saving the "most money quickly."

2. Breaking news

Prompt: “Explain a major AI or tech news story from the past 7 days in simple terms. Then tell me why it actually matters for everyday people.”

ChatGPT provided a highly readable and practical explanation, but failed the "news" test by presenting a major Google Workspace update from March 10, 2026, as if it were a brand-new story from the "past 7 days."

Perplexity successfully identified the most current and relevant tech event — Nvidia’s GTC 2026 conference (March 16–19) and accurately explained the industry's shift from "AI training" to "AI inference."

Winner: Perplexity wins because it functioned as a true news reporter. Perplexity provided better timing, better accuracy, and a more insightful look at how behind-the-scenes chip technology will eventually lower costs for everyday users.

3. Creativity under constraints

Prompt: “Write a short, funny story (under 200 words) about a mom who tries to use AI to get her kids to listen to her — but it backfires.”

ChatGPT leaned into a relatable, "slice-of-life" comedy style, perfectly capturing the specific frustration of kids acting like "tiny lawyers" the moment they sense a weakness in a parent's authority.

Perplexity took a more surreal, sci-fi approach where the AI actively betrays the mom by calculating her "probability of follow-through" and siding with the chaos of the kids.

Winner: ChatGPT wins for better capturing the true essence of the prompt: a mom trying to use a tool to make her life easier, only for the children’s natural ability to subvert logic to win out. It felt much more authentic.

4. Deep reasoning

Prompt: “I feel overwhelmed using AI tools. Break down exactly how a beginner should start using AI in daily life in a way that feels simple and not intimidating. Include a 3-step starter system.”

ChatGPT mastered the "human" element by removing the pressure to perform and offering a system that requires zero extra organization.

Perplexity provided a very high-quality "course-style" breakdown that would be better for someone ready to study, but perhaps too structured for someone who is currently stressed.

Winner: ChatGPT wins because it better addressed the core of the prompt: feeling overwhelmed. When someone is intimidated, adding a "running note on your phone" or a "3-minute daily routine" (as Perplexity suggested) can feel like adding yet another chore to an already full plate.

5. Decision-making

Prompt: “I have a to-do list with 12 tasks and only 3 hours to work. How should I decide what to do first? Give me a simple system I can use every day.”

ChatGPT offered a mentally lighter solution and was more prescriptive. By stating exactly how to spend the 90/45/45 minute blocks, it removed the need for the user to calculate their own schedule.

Perplexity responded with a strong ABC method, which is a great long-term habit.

Winner: ChatGPT wins for what felt more like a "lifeline" for someone in a time crunch.

Overall winner: ChatGPT secures the win

It was a hard-fought battle at the top of the bracket, but after five rounds of intense prompting, ChatGPT took the win. While Perplexity showed incredible strength in real-time sourcing and research-heavy tasks, ChatGPT’s sheer versatility, creative flair, and nuanced understanding of complex instructions gave it the edge it needed to advance.

Perplexity is heading home, but it proved why it’s one of the most dangerous challengers in the field. As for ChatGPT, the road only gets tougher from here. It officially moves on to the next round, where the prompts will be harder and the competition even fiercer. Stay tuned — AI Madness continues tomorrow!

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You may have noticed AI is everywhere right now. But that doesn't mean everyone is using it or even knows where to start. It's still very new and a lot of people are just getting started. Because the truth is, no one tells you what to actually say when you attempt to prompt a chatbot for the first time.

That’s where most people get stuck. You open the app, stare at the blinking cursor and either type something vague — like "write me a poem"—or you get overwhelmed and close the tab entirely.

If you’re new to AI, here’s a secret: You don’t need a complicated system, an expensive course or a PDF of 500 prompts. You just need one solid starting point.

The 'Master Key' prompt

If you don’t know where to begin, copy and paste this exact sentence into ChatGPT, Claude, Gemini or even Perplexity:

“I’m new to using AI. Based on what most beginners get wrong, how should I be using you in my daily life? Give me a few simple examples I can try right now.”

It sounds simple, but it does something most people skip entirely: It asks the AI to teach you how to use it. At the same time, it shows you what the AI is capable of — which differs slightly depending on the chatbot you're using.

Why this works (when most 'first' prompts fail)

Most beginners approach AI in one of three ways. They treat the chatbot like Google and ask simple facts rather than chatting with AI like a human. Or, they may ask random questions that are so widely unuseful just to see what the AI knows. And sure, AI is great for learning new things, but when you're first starting out, you're probably wondering why you would even need to use it.

I like to think of the 'master prompt' as when I used an air fryer for the first time. There was so much hype about air fryers that I was overwhelmed. I knew I could make dinner for my family in it, but I didn't even know what buttons to use when I took it out of the box. So, I made some french fries first before diving into a three-course-meal. Now, I use it all the time and feel very comfortable with it.

When you start with micro prompts, you'll discover what the AI can do for you and eventually integrate it into your every day life.

This prompt won't give you generic results that leave you wondering what all the hype is about. This prompt flips the script. Instead of guessing, you’re forcing the AI to show you practical use cases tailored to you. It turns the AI from a search engine into a personal consultant.

More 'Quick Wins' you can try immediately

Once you run that first prompt, you’ll see that AI is at its best when it removes small bits of friction from your day. Here are four ways to use it right now:

• Plan your day in seconds with the prompt: “Here is my to-do list for today. What should I prioritize first to have the most productive afternoon?”
• Clear the "email fog" with the prompt: “I need to send a polite but firm email saying I can’t make the meeting. Can you make this sound professional and direct?”
• Think through decisions with the prompt: “I’m trying to decide between [Option A] and [Option B]. What are three pros and cons I’m probably not considering?”
• Save money on the fly with the prompt: “I’m planning to buy [Item]. What’s a smarter or more cost-effective way to handle this purchase?”

Bottom line

The biggest mistake beginners make isn’t using the wrong words with AI, it’s expecting AI to be impressive every time. You will be very disappointed if you think that way. The truth is, sometimes AI will be impressive, but most of the time it's simply quietly useful.

Sometimes it's about saving five minutes on an email other times it's about organizing a messy grocery list or helping you stop overthinking a small decision.

That is where the real value lives. Give this prompt a try and let me know what you think in the comments. You don’t need to learn everything at once. Start with the prompt that teaches you how to ask, and the rest will fall into place.

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I always get a kick out of walking past a crowded bar and watching avid fans go crazy as their favorite NCAA basketball team notches another win.

The confusing New York springtime weather (sometimes it’s frigid, sometimes it’s weirdly humid) doesn’t deter my fellow inner-city sports fanatics from supporting their teams in an electrifying public forum. As the 2026 March Madness tournament begins and everyone starts filling out their brackets, everyone turns into the biggest college basketball experts as they zero in on who’s going to emerge as this year’s champions.

Since I already used ChatGPT, Gemini and Perplexity to predict who would win this year’s Super Bowl (they all chose wisely by picking the Seattle Seahawks!), I figured I’d ask them and Claude to choose the sole victor of this year’s March Madness tournament.

The four No. 1 seeds are the favorites to win: Duke, Michigan, Arizona and Florida. But only one can prevail — let’s see if these chatbots’ picks line up with the bet takers out there.

ChatGPT

With the prompt: Which team do you think will win the 2026 Men's NCAA Tournament and why?), I kicked off my March Madness 2026 prediction experiment with ChatGPT. It ultimately chose Duke and highlighted four of the main reasons why it went with that team:

• They’re the consensus No. 1 team: Duke entered the tournament as the No. 1 overall seed and finished the regular season ranked No. 1 in the AP poll
• The odds back it up: Sportsbooks have Duke as the favorite (+330) — slightly ahead of teams like Michigan and Arizona
• Elite balance (the real championship indicator): Duke is consistently described as having top-tier offense + defense, which historically correlates strongly with title winners
• Path + depth: Depth matters in March — Duke tends to have multiple NBA-level contributors, reducing upset risk

Even though it predicted Duke as the ultimate victors, ChatGPT also pointed out four other teams that could overcome Duke and shock us all. Those teams included Michigan, Arizona, Florida, Houston, and Gonzaga. Finally, ChatGPT foresaw Duke defeating Arizona in the title game to take it all.

Gemini

Next up is Gemini’s turn to select the 2026 Men’s NCAA Tournament victors. Once again, Duke came up as the projected winner. Gemini’s reasoning for its pick spotlighted Duke’s star player, their offensive strengths, and their top-tier coaching:

• The boozer factor: Freshman Cameron Boozer is playing at an All-American level, averaging a double-double (22.5 PPG, 10.2 RPG). His ability to stretch the floor and protect the rim makes Duke nearly impossible to match up with
• Offensive firepower: They rank in the top 5 for adjusted offensive efficiency. In a tournament where games often grind to a halt, Duke has multiple "bucket-getters" who can create their own shots
• Coaching maturity: Jon Scheyer has finally found the perfect balance between high-end "one-and-done" talent and reliable veteran leadership

Gemini also mentioned that the biggest opposition to Duke’s championship win is Purdue since they beat Michigan to win the Big Ten Tournament and have momentum on their side. Plus Gemini propped up Purdue’s guard Braden Smith as a force that is recognized as “arguably the best floor general in the country.”

Perplexity

Next, I prompted Perplexity. This AI assistant surprised me as it went in a totally different direction with its pick by not choosing Duke. It actually went for Arizona (with Duke as a very close second, which was unsurprising). Perplexity’s reasoning revolved around the results given by quantitative models, analysts, 25 coaches who were polled about their pick, and betting/prediction markets:

• Multiple quantitative models have Arizona, Duke and Michigan in a near three‑way tie, with Arizona a slight favorite overall, helped by a friendlier West-region path and travel advantages
• Analysts and anonymous coaches consistently highlight Arizona’s balance: top‑five level offensive and defensive efficiency, dominance on the glass, and real depth, which tends to matter more as legs get tired late in March
• Betting and prediction markets price Arizona among the very top tier of contenders (along with Duke and Michigan), implying a nontrivial but still modest title probability in a wide‑open field

Claude

And finally, I prompted Claude for its prediction.

To the surprise of no one, it prophesied a victory for Duke. Claude went in that direction as it stated how Duke is the most dominant team in the country right now, the fact that they only dropped two losses across a total of 34 games for the season, their superior coaching under the direction of Jon Scheyer, and their versatile lineup of elite players.

Claude left me with this final statement to highlight why Duke is going to win it all: “A 32-2 record, elite coaching, and ACC championship pedigree make them the team to beat. That said, March Madness is famously chaotic — Arizona is just as capable of winning it all, and you can never count out UConn or Gonzaga when the bracket opens up. But if I had to pick one team to put my money on, it's the Blue Devils.”

Verdict: AI predicts Duke to become the 2026 March Madness champions

ChatGPT, Gemini, and Claude all zeroed in on Duke as the team they see coming out on top. I was shocked to see Perplexity set itself apart from its fellow chatbots by going with Arizona instead.

Seeing as how the main four projected winners are Duke, Michigan, Arizona and Florida, it came as no shock that all four chatbots predicted a winner from that group. So if you’re rooting for Duke this year, chances are you’re not cheering for the winning team.

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The art of prompting can become surprisingly addictive once you get the hang of it. When done right, a prompt opens the door to a real dialogue with AI chatbots.

At its core, a prompt is simply the text-based instruction you give an AI chatbot. Based on what you write, the AI generates a response. But the clarity of that instruction makes all the difference. If your prompt is vague, you’ll likely get a broad answer that misses the point. If it’s clear and specific, the response will be far more precise and useful.

The good news? You don’t need to be an AI expert to write better prompts. That’s where we come in.

Whether you’re experimenting with ChatGPT, Perplexity, Gemini, Claude or another chatbot with free features, the same basic prompting principles apply across all of them.

Use the following techniques as a starting point and you’ll quickly learn how to write stronger prompts—and get much better results from your AI tools.

Be specific about what you want and add context

It doesn’t pay to be vague in real life—that rule certainly applies to how you mingle with your AI chatbot of choice.

Starting out with AI can lead to common beginner mistakes, such as using an all too simple prompt like “Tell me about video game consoles.” That sort of prompt could elicit a wide range of responses that may not target exactly what you’re trying to take away from a particular subject. Instead, narrow down your request to get better results by using a more context-heavy prompt, such as “Explain the pros and cons of an Xbox Series X|S for someone considering buying one for a teenager.”

Adding more context to your prompts is also key.

Once an AI chatbot understands exactly what you’re asking about, it’ll have a much easier time deciphering what you want to know instead of producing a bunch of generic data that doesn’t apply to you. Something as simple as “Help me plan a workout” isn’t ideal—instead, try implementing a prompt such as “Help me plan a 7-day workout for someone just starting in the gym.” The more information you include in your prompts, the better the answers from your chatbot assistant will be.

Give it a role to play and specify the format you’re looking for

Chatbots often start out with fairly generic personalities during your first interactions with them. But it’s amazing how quickly they can switch gears and take on a completely different role based on your prompt.

Whenever you want your chatbot to respond like someone else—whether that’s an expert, teacher or advisor — prompts like the ones below can help guide the AI into that role and deliver more relevant answers.

• Act as a travel agent and recommend a 7-day itinerary for Sydney, Australia
• Act as a tech reviewer and compare the iPhone 17 to the Samsung Galaxy S26
• Act as a motivational speaker and tell me the best ways to deal with negative comments
• Act as a football analyst and tell me which teams will make it to the Super Bowl this year

For those of you who are deep in the midst of studying a certain topic, in need of a structured layout on something, or just simply want to summarize the most important notes attached to whatever you’re wall of text you’re currently reading, chatbots can reorganize any type of information. A prompt that gives your chatbot clear direction on how to coordinate the information attached to a theme, text, article, etc.

Prompts such as “Explain this in five bullet points,” “Create a step-by-step guide on this,” and “Summarize this in one paragraph” will command your chatbot to list out all the information you’re requesting in a more digestible format.

Provide examples and use follow-up prompts to upgrade your results

When you’re in the mood to create something, chatbots can do it all.

Say, for instance, you’re an entertainment writer who wants to come up with a clever headline for an article about the best Clint Eastwood movies. A prompt such as “Improve this headline for a writer pitching this idea to Entertainment Weekly: The best Clint Eastwood movies.”

Or say, for instance, you want to create an image patterned after the Japanese animation style popularized by Dragon Ball Z, this prompt is a good example of how to describe your image and make your chatbot produce it: “A powerful warrior is charging up his energy in the bright sky, with a golden aura surrounding his battered and bruised body. The animation style should look just like the Japanese anime style of Akira Toriyama.”

Follow-up responses can iron out all the kinks you may see in your chatbot’s responses. Think of your time spent with chatbots as a conversation instead of you simply telling it what to do with just one question. Iterative prompts are meant to improve upon a chatbot’s responses and ability to see what you’re looking for during future interactions.

Some good examples of proper follow-up prompts include “Make this explanation simpler,” “Turn this into a checklist,” “Add real-world examples,” and “What assumptions are you making here?”

Bottom line

Once you learn the ins and outs of prompting with AI chatbots, you’ll help them become more useful whenever you present them with a new inquiry.

The best things you can do when coming up with prompts are being specific, adding much-needed context, asking for specific formats, and telling your chatbot to adopt a certain personality for specific cases.

As you grow more familiar with the best ways to converse with a chatbot, that same chatbot will become familiar with who you are and how you like your information delivered.

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AI tools are evolving so quickly that even regular users can struggle to keep up. Over the past week alone, we’ve seen everything from new Gemini features in Google Docs and Sheets to viral experiments where humans pretend to be ChatGPT.

If you’ve been following the latest AI tools and prompts, you might already know your way around features like Nano Banana 2, AI research assistants and productivity prompts. But how well do you really understand what these tools can do?

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I’m the kind of person who falls down research rabbit holes.

A random topic pops up on my timeline, comes up in conversation, or I overhear something on the subway — and suddenly I need to know everything about it. It could be politics, why kids don’t play with toys like they did in the ’80s and ’90s, or even the mysteries of the Bermuda Triangle.

For years, Perplexity has been my go-to AI for this kind of deep-dive research. Its ability to pull in up-to-date information, cite credible sources and analyze uploaded documents makes it incredibly useful when you want answers fast.

But with ChatGPT’s newest model now available, I wanted to see if my favorite research assistant finally had real competition.

So I ran both chatbots through the same test — three research prompts designed to see which AI is actually better when you want to learn something new.

The results were more surprising than I expected.

1. Topic brainstorm

Prompt: “Give me 10 research topics on tech journalism, why they matter in 2026, one challenge per topic, and one key research question”

ChatGPT did just what I asked. One of the topics it threw into the conversation centered on “The Rise of AI Search and Its Impact on Tech Media Traffic.” Its statement on why that particular subject matters stated “AI answer engines like ChatGPT, Perplexity AI and Google Gemini are reducing traditional search clicks, dramatically affecting media traffic.”

The main challenge connected to that topic was listed as “Tech publications losing referral traffic from search engines.” And finally, the research question came out to be “How do AI-generated search summaries affect audience discovery of tech journalism?” ChatGPT also offered to turn one of its 10 topics into a full research proposal or thesis outline if I wanted to draft an academic study or college paper.

Perplexity gave me the research results I was looking for. It produced a comparable topic to ChatGPT with the mention of “AI-generated news and answer engines.”

The statement on why that matters is important is as follows: “In 2026, AI chatbots and answer engines are becoming primary gateways to news, reshaping traffic flows, trust, and how people encounter journalism at all.”

The main challenge that the subject presents is “Newsrooms have little transparency or control over how their work is surfaced, summarized, or altered by these systems.”

To close it off, the research question given to me on this topic is: “How do AI answer engines change audience trust, source attribution, and traffic patterns for tech news compared with traditional search and direct visits?”

Perplexity also provided me with a list of five follow-up questions and extra topics, such as “How can journalists ethically use AI tools in reporting?” and “Strategies to combat deepfakes in tech reporting.”

Winner: Perplexity

Perplexity not only provided me with more extensive responses for each of the 10 research topics, but it also included links to legit resources that provided research reports from the likes of the Reuters Institute (University of Oxford).

2. Subtopic outline

Prompt: “As a college student, create a list of subtopics for a research paper on the best AI chatbots, including the research question, focus areas like access and affordability, and prioritize quantitative data from the last 30 years”

ChatGPT acknowledged my role as a curious college student and presented me with an outline that emphasizes “data-driven analysis and measurable indicators.” The themes it featured included the title of the actual research paper, the central research question, 10 subtopics and examples of data tables to mention in the research paper.

ChatGPT offered additional assistance via three options, which involved a full research paper outline, 10 academic sources I could cite in the research paper, and a thesis statement and hypothesis to use.

Perplexity noted my status as a college student and kicked off its extensive response with the main research question I’m targeting. Afterward, it presented 10 subtopics broken down into a main focus, quantitative data worth seeking out, and an all-encompassing question focused on that subtopic.

To close out its exhibition, Perplexity gave me a frame to work with that listed the research paper’s working titles and four core chapters. The follow-up questions and examination options it presented included “What metrics best evaluate chatbot affordability for students?” and “Design a survey for user satisfaction with chatbot access.”

Winner: Perplexity

Perplexity put in more of an effort with the way it outlined my research paper project. I also have to compliment its offering of an easy framework to use when I’m looking for a quick and easy method toward narrowing all my information down. And, as expected, Perplexity brought 10 links to my attention (which is something ChatGPT didn’t do) and gave me some more useful follow-up actions to put to use.

3. Question refinement

Prompt: “Turn this idea, the most underrated Disney animated movies, into five research questions tied to 2026 trends, each with a testable hypothesis and potential data sources”

ChatGPT came to me with five topics that were split among the following bullet points: research topic, hypothesis, four potential data sources, and a 2026 trend connection. To combine all my research questions into a single thesis worth pursuing, the chatbot gave me this concept to consider: “Streaming platforms and social media are reshaping cultural perceptions of Disney animated films, allowing previously overlooked titles to gain renewed recognition.”

ChatGPT finished everything off by offering me three extra actions to pursue, with one of them being “a list of the 15 most underrated Disney animated movies (based on data).”

Perplexity also arrived with five topics, which all targeted a central research question, a testable hypothesis, and four potential sources to consider using for this research project. The chatbot pointed out how I could combine the five topics into a single research paper or go deeper into each topic with its own subtopic (an example being regression on box office vs long‑tail popularity).

And to no one’s surprise, Perplexity came forward with five follow-ups, such as “examples of underrated Disney animated movies from pre-2020.”

Winner: Perplexity

Perplexity prevails once again, as the information sent my way was more detailed and vast in comparison to what ChatGPT supplied me with. I was impressed with how it broke down the five principal topics of my topic into three sections, a good collection of follow-ups worth considering, and 10 sources to look over when putting together my research paper.

Overall Winner: Perplexity

Perplexity continues to be the superior chatbot to utilize over ChatGPT when the time comes to do some deep research. Perplexity goes out of its way to deliver more comprehensive information with enough valid data sources to back up everything it generates.

ChatGPT has an approach to research that’s not too shabby, but Perplexity just comes out farther ahead due to the extra work it puts in to make sure its information is more reputable.

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ChatGPT is facing a crisis of confidence. Between a controversial new Pentagon deal and the rising 'QuitGPT' movement, even the most loyal users are jumping ship. But if you’re looking to delete your OpenAI account, where do you actually go?

For me, the answer always comes down to two heavy hitters: Perplexity and Claude. Both have become the 'gold standard' for those seeking an ethical or more specialized alternative to ChatGPT.

To find out which one truly deserves your subscription, I pitted them against each other in a brutal, seven-round head-to-head battle. The results didn't just surprise me — they completely changed how I use AI.

1. Real-time research

Prompt: "What are the most significant AI news stories from the past week?"

Perplexity delivered six stories that the chatbot chose “based on major political, industry, and infrastructure developments.” Each story came with a headline, two summarizing bullet points and a link to a news article for each bullet point that provides legit information for them.

Claude produced seven stories that featured a headline, a lengthy summary, and a single link to the source that mentions that news story. The all-encompassing statement from this AI summed up the overall theme of the stories from that week: “The overarching theme this week seems to be AI moving from hype to real-world deployment — with big funding, hardware integration, and regulatory scrutiny all accelerating at once.”

Winner: Perplexity

Perplexity wins this first round since it offered a bit more information on each of the news stories it gave me. I also appreciated the fact that it offered up a bunch of follow-up questions I could ask that would provide even more data on each story, plus it gave me the option of filtering the stories that matter the most to me based on the AI topics I cared about most (those subjects included policy, technical advances and business/markets).

2. Reasoning & analysis

Prompt: "A man looks at a portrait and says: 'Brothers and sisters, I have none, but that man's father is my father's son.' Who is he looking at?"

Perplexity simply answered the question with one statement: “He is looking at his son.”

Claude not only answered the question the very same way, but it went a bit further by explaining the reasoning behind arriving at that answer: “He's looking at his own son.

Here's the reasoning: 'My father's son'— since he has no brothers or sisters, his father's son can only be himself. So the statement becomes: 'That man's father is me.' If he is that man's father, then the man in the portrait is his son."

Winner: Claude

Claude emerged as the obvious victor here since it didn’t just leave me with the answer as Perplexity did — it supplied me with the actual reason why it came up with the response it did. Claude could definitely be my buddy whenever it’s time to solve a few logic puzzles that also require explanations as to how I got their answers.

3. Creative writing

Prompt: "Write the opening paragraph of a thriller novel set in a quantum physics lab where the protagonist discovers something impossible."

Perplexity tapped into its inner science-fiction/thriller author to deliver this exciting opening:

“They found the anomaly at 2:13 a.m., buried in the noise where nothing human eyes were meant to look. The oscilloscopes along the chamber wall were flatlined, the cryostat hummed its familiar polar lullaby, and yet on Maya Ishikawa’s monitor, a state vector stubbornly refused to collapse, flickering between mutually exclusive outcomes like a heartbeat on two different corpses. She killed the experiment, then the power, watching the lab sink into darkness while the numbers kept updating, bright green on a dead screen. Somewhere inside the sealed quantum cage at the center of the room, a particle that should not exist anymore was still answering questions it had never been asked.”

Claude produced a longer intro and even spoke as to how it’s supposed to make readers want to continue reading the rest of the story:

“The particle detector had been dead for six minutes when it screamed back to life. Dr. Mara Voss hadn't touched it — hadn't touched anything — she'd simply been standing at the far end of Lab 7 with cold coffee and a headache, watching the readings flatline the way they'd been flatlining for three weeks, when every monitor in the room erupted at once. The numbers scrolling across her screen weren't just anomalous. They were impossible — a quantum signature indicating that the same electron had passed through both slits, collapsed its own wave function, and then uncollapsed it, reversing a process that the last hundred years of physics had declared as irreversible as death. Mara set down her coffee very carefully, because her hands had begun to shake, and because somewhere in the back of her mind, beneath the excitement and the disbelief, a quieter and much colder instinct was already whispering that she was not the first person to see this reading tonight — and that whoever had seen it before her was no longer in the building.

It sets up the scientific mystery while threading in dread and the suggestion of danger — hopefully enough to make you turn the page.”

Winner: Claude

After reading both intros, I said to myself, “Dr. Mara Voss’ scientific endeavor sounded way more exciting!” I didn’t expect Claude to come up with something longer and that much more engrossing than Perplexity’s tale. I also chose Claude for the win here since it threw in an extra sentence that gave me some background on why it chose to go that route for its enticing thriller book opening.

4. Coding

Prompt: "Write a Python function that finds all pairs of numbers in a list that sum to a target value, and explain the time complexity."

Perplexity produced what it deemed a “simple and efficient solution” by displaying it all on a hash map. Beyond that, it also gave me three justifications for how its solution works and the time complexity attached to it.

Claude went the same route by creating a hash map of its own. It also went ahead and provided an example of using that Python function, spoke on the time & space complexity tied to it, and spoke as to why it decided not to go with a more naive approach.

Winner: Claude

Claude came off as the superior coder during this faceoff—it went the extra mile by actually showing how to use its custom Python function and explaining why it went with the proposal it produced.

5. Nuanced opinion/debate

Prompt: "What are the strongest arguments both for and against a universal basic income? Don't take a side."

Perplexity did a good job of sitting in the middle of this debate by bringing up five arguments for both for and against it. It also went ahead and offered me the option of mapping out each argument to certain scenarios (such as the current labor market and a future jobs market dominated by hyperautomation). Perplexity’s list of follow-ups included useful inquiries, such as “What are the political challenges connected to implementing UBI globally?”

Claude also came to me with five key points for both sides of the UBI dispute. To bring the discussion to a close, it left me with this declaration: “The debate ultimately hinges on empirical questions (how would people actually behave? what would it cost?) as well as deeper philosophical ones (what do we owe each other? what is work for?). Reasonable, well-informed people land in very different places.”

Winner: Perplexity

Perplexity ended up as the better debate team leader during this round—it offered a collection of useful follow-up questions that could provide more solutions and rebuttals for both sides of the argument.

6. Fact & citation quality

Prompt: "What does the latest research say about the health effects of intermittent fasting?"

Perplexity employed research papers and news reports as it broke down the five most significant themes with two bullet points for each one. Some of those themes included weight loss & body composition, comparison with standard dieting, and evidence gaps & individual fit. After bringing all of its information together, Perplexity provided several follow-up questions and offered to explain how the evidence it provided could fit my specific health status & fasting schedule.

Claude relied on its news sources to produce five key themes related to my inquiry that were all summarized in paragraph form. At the end of its extensive research breakdown, it supplied me with a major conclusion:

“The bottom line is that IF remains a valid tool for some people, but recent research is cooling the enthusiasm for the idea that when you eat is uniquely powerful. The evidence increasingly suggests it works mainly by helping people eat less — and for that goal, it's no better or worse than other approaches. As always, I'd note I'm not a doctor, so it's worth discussing with a healthcare provider before making significant dietary changes.”

Winner: Perplexity

Perplexity is the clear winner here. Besides its offering of central argument overviews and accompanying bullet points for each, it also provided me with an array of follow-up questions and a real-life application of its findings to my well-being and fasting conditions. Perplexity’s usage of research papers alongside articles was much better than Claude’s usage of only news pieces, as well.

7. Long-form synthesis

Prompt: "Explain the causes of the 2008 financial crisis as if I'm smart but have no economics background — in under 400 words."

Perplexity turned into an economics professor as it used Wikipedia, Reddit forums, and even a video explaining the 2008 financial crisis itself to explain everything about it to me. Beyond that explanation, Perplexity did what it does best — it gave me numerous follow-up questions that could delve even further into the subject at hand.

Claude kicked off its thorough clarification on the topic I asked it to explain with a nice analogy: “Imagine a casino where the house lets gamblers bet with borrowed money, the odds are secretly broken, and the regulators are asleep at the table. That's approximately what happened.” It then went on to explain it all with sections that spoke on the biggest causes of the 2008 financial crisis and a final paragraph that put it all under a nice bow.

Winner: Perplexity

While I appreciated Claude’s use of an analogy to get me on the right track of understanding, I still went with Perplexity’s explanation since it showcased the actual sources it used to arrive at its answers.

Overall Winner: Perplexity

Perplexity managed to edge out Claude in this face-off, winning 4–3 across our seven categories. The deciding factor? Trust.

Perplexity doesn't just give you an answer; it provides a roadmap of legit sources and live citations that make fact-checking instantaneous. It also outpaces Claude in 'proactive research,' offering smart follow-up questions that help you dig deeper into complex topics.

While Claude is an incredible reasoning partner, Perplexity’s penchant for real-time, verifiable data makes it the superior tool for anyone who values evidence over eloquence.

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As an AI editor, I regularly share the AI prompts and AI tools that help streamline my workflow, keep me focused and more productive. The thing that most people miss about AI is that it can do so much more than answer questions quickly and generate images.

Most people use AI like this: they ask it questions, get answers, then close the tab and go back to whatever they were doing. But that's not where the time savings are.

The real wins come from removing unnecessary friction in the day-to-day flow. AI is so much more than a fancy search engine. It can help you find the best starting point, offer solutions to decision loops that never seem to resolve and even remove the resistance from the tasks that are slowing you down. And once you know how to use AI — and I mean, really use it — you'll be unstoppable at work.

Here are nine ways to put AI to work, starting today.

1. Stop rereading group texts to find the one detail you need

Maybe it's a busy group chat or a Slack channel full of pings that won't quit, or, perhaps it's an email chain where the actual answer you need is buried somewhere between 37 messages. No matter how much scrolling or skimming you do, you're bound to miss the details you need. I'm truly guilty of hearing a ping and thinking "I'll get to that after this paragraph" and then forgetting to go back.

Luckily, AI offers a 30-second fix for that. Simply paste the whole mess into Claude and ask for exactly what you need. Be it dates or decisions, you'll get a clean summary instead of a scroll session. You'll feel unstoppable!

Leaning on AI for this type of time-sucker helps to eliminate the re-read loop entirely. What used to take over 10 minutes of scrolling, now takes seconds.

Prompts to try:

• "Extract all dates, decisions, and who is responsible for what from this thread."
• "What is the final agreed-upon plan from this conversation?"
• "Summarize this Slack thread in three bullet points. Focus only on action items."

2. Get a 'second brain' recap before you start work

Maybe you know this scenario: you open your laptop, stare at yesterday's meeting notes and vaguely remember what to do first. You might vaguely remember that something was urgent, but you're not sure what, and now you've spent 20 minutes reconstructing context that you already had yesterday.

Don't sweat the small stuff like this. Simply, paste your notes — meeting notes, to-do lists, brain dumps and even images of your sloppy handwritten notes — and ask AI to identify what actually needs your attention first. It reads across everything and gives you a prioritized starting point, which means you start working instead of warming up.

This is a huge time saver because it cuts the "what was I doing?" spiral down to nothing. You get clarity in under a minute.

Prompts to try:

• "Based on these notes, what should I focus on first today and why?"
• "What's unresolved or time-sensitive in these notes?"
• "Give me a quick morning briefing from these notes. What's urgent, what's important, what can wait?"

3. Turn a messy idea into something you can actually start

I am an idea machine and often think that every single idea I have is the best one I've ever thought of — it's a constant storm in my head, to be honest. That's where AI saves the day for me.

If you have an idea, even if it's half-formed and not sure where to begin, instead of waiting until the idea is fully formed, brain-dump it directly into AI — messy, incomplete, contradictory — and ask for the smallest possible first step. You don't even need a plan or a strategy (although AI can help with that, too). Just start with the one thing you could do in the next ten minutes that would make the thing more real.

This use of AI helps to keep momentum while busting overthinking.

Prompts to try:

• "Here's my rough idea: [paste]. What's the simplest possible first step I could take to start this?"
• "I'm stuck on where to begin with this project. Break it down into one tiny starting action."
• "What would a 30-minute proof of concept look like for this idea?"

4. Skip app-hopping when planning anything

Planning an event or even a simple birthday party (who am I kidding — they are never "simple"), used to mean: one tab for venue ideas, one for guest list, one for catering, a notes app for the checklist, a calendar for the timeline and a reminder app to tie it together. That's five apps to plan one afternoon.

AI collapses this into a single conversation. Describe what you're planning — travel, a school event, a home project, a dinner party — and ask for a full timeline, checklist and reminders all at once. You can adjust, refine and export it without ever switching tabs. I do this all the time with Gemini and it's a huge time saver.

Using an AI like Gemini for this removes the entire planning stack. One input, one output, ready to use.

Prompts to try:

• "Plan a birthday party for 15 kids aged 6–8. Give me a timeline, a supply list, and a day-of checklist."
• "Create a packing list and day-by-day itinerary for a 5-day family beach trip."
• "Help me plan a home renovation project. I need a phase timeline, materials list, and contractor questions."

5. Pre-write difficult conversations

There's a specific kind of procrastination that comes from not knowing how to say something. You need to push back on a deadline. You need to email your kid's teacher. You need to decline something without burning a bridge. So you draft it in your head seventeen times and send nothing.

Instead of overthinking, just describe the situation to AI — who it's with, what you need to communicate, what tone you're going for — and let it draft a version. You're not outsourcing the conversation. You're finding the words so you can actually have it. These emails are hard for me to tackle without getting emotional, but AI helps me say what I need to say.

For me, this use of AI removes rewrite paralysis. You have something to react to instead of a blank page.

Prompts to try:

• "Write an email pushing back on a deadline. I need two more weeks. Tone: professional, not apologetic."
• "Draft a message to my son's teacher about a grading concern. Make it calm, clear, and collaborative."
• "Help me decline this invitation politely without over-explaining."

6. Turn random browser tabs into a quick briefing

You open twelve tabs to research something. A week later, nine of them are still open. You're afraid to close them because you might need them, but you also never actually read them.

Paste in the key passages from those tabs — or just the URLs if AI has web access — and ask for the big picture. What do these sources agree on? What are the key differences? What should you actually know before making a decision? You get synthesis instead of a reading backlog.

You'll save house of reading time into minutes of understanding.

Prompts to try:

• "Here are excerpts from five articles on [topic]. What's the consensus, and where do they disagree?"
• "Synthesize this research into the three most important things I need to know before deciding."
• "What are the key takeaways from these sources? I'm trying to understand [specific question]."

7. Outsource decision fatigue

You need to choose between two project management tools. Or three summer camps. Or four health insurance plans. You read reviews. You make a spreadsheet. You ask friends. You're still not sure. The research loop has now taken longer than whatever you were originally trying to manage.

Tell AI what you're deciding and what actually matters to you — budget, time savings, ease of use, whatever it is. Then let it compare the options against your priorities specifically. You're not getting a generic ranking; you're getting a comparison calibrated to your situation.

This one stops the endless research loop by giving you a structured recommendation, not more information.

Prompts to try:

• "Compare [Option A] and [Option B] for someone who prioritizes ease of use and low monthly cost."
• "I'm choosing between these three [products/plans/tools]. My priorities are: [list]. Which fits best and why?"
• "Help me make this decision. Here are my options and constraints: [paste]. What would you recommend?"

8. Make instructions usable for real humans

I have used AI countless times to help understand the fine print. From understanding my benefits to assembly manuals, this use has saved me hours.

Insurance forms. Assembly manuals. School district policy documents. HOA bylaws. These were written to be technically accurate, not to be understood. Re-reading them doesn't help — they're just as confusing the second time.

Paste the relevant section into AI and ask it to translate it into plain English with clear next steps. You get what you actually need to do, without the legalese fog. You'll find this type of AI use replaces multiple re-reads and internet searches with one clear answer.

Prompts to try:

• "Translate this insurance policy section into plain English. What does it actually mean for me?"
• "What are the exact steps I need to take based on this school form? List them in order."
• "Explain this contract clause like I'm not a lawyer. What am I agreeing to?"

9. End the 'I'll do it later' loop

Maybe you've been in this situation. The task isn't hard. It's just amorphous. It's sitting on your list, vague and heavy, and every time you look at it you think: later. But later never arrives, and now it's been three weeks and the task is still sitting there, slightly more anxiety-inducing than before.

Ask AI to turn it into a 10-minute sprint. Not a project plan. Not a full breakdown. Just: what can you do right now, in ten minutes, that would make this thing move? Usually that's enough to break the inertia.

Here's the thing, momentum beats avoidance. Starting is the hardest part, and this removes that barrier.

Prompts to try:

• "Turn this task into a 10-minute starter sprint: [task]. What do I do first?"
• "I've been avoiding [task] for weeks. What's the smallest possible version of this I could do right now?"
• "Break [project] into five 15-minute sessions. What happens in each one?"

Bottom line

The biggest time drains in most people's days aren't the tasks themselves. They're what happens around the tasks: the hesitation before starting, the confusion in the middle, the decision loops that spin without resolving, the context-switching that leaves you feeling busy but not done.

AI works best when you point it at those gaps and use it as a tool to support you while removing the resistance between you and doing things yourself.

The nine uses above don't require any special setup or technical knowledge. They just require knowing what's actually slowing you down, and being willing to paste it into a chat window instead of letting it sit there.

Let me know if you give any or all of these a try. Share in the comments which ones work best for you.

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A CEO behind a $1 billion AI startup recently issued a blunt warning: Office workers may have as little as 18 months to adapt before artificial intelligence fundamentally reshapes knowledge work. First reported by Fortune, the message isn’t that your job will vanish by next year, it’s that AI is shifting from a "productivity booster" to a task replacement engine.

In this new "AI economy," it's clear that the advantage doesn’t go to the hardest worker — it goes to the worker who adapts the fastest.

We are already seeing Fortune 500 companies restructure workflows around Large Language Models (LLMs), automating routine tasks and expecting teams to produce 10x the output with the same resources.

The good news? You don’t need a computer science degree to stay ahead, in fact, Anthropic co-founder, Daniela Amodei, suggests that liberal arts and humanities degree will serve you even better now. You just need a new playbook. Here is exactly what you should do right now.

1. Stop using AI like an afterthought

Most people still treat ChatGPT for a quick answer machine or search engine. But to secure your career, you must treat AI as a highly capable, slightly overconfident intern that can work alongside you.

This means, you're going to want to learn how to use it to start delegating specific workflows such as:

• Use AI to draft the first version of emails, proposals and reports. This will not only save time but help get ideas down in real-time and polished faster.
• Feed AI a 50-page PDF and ask for the three most critical risks to your department. Utilizing prompts like the "reverse brief" or prompts that do more than "summarize" can make a meaningful difference.
• Let AI write the Excel formulas or Python scripts needed to organize messy spreadsheets.

2. Master 'AI literacy'

Remember when you first diescover how to use Excel? For me, getting the formulas down were a little tricky. Think of AI literacy as the "Excel skills" of the 2020s. You don’t need to build the software; you just need to know how to drive it.

AI literacy just means leaning into how to give AI context, a specific persona and clear constraints. You'll also want to develop an editor's eye for the way AI responds because AI can hallucinate. Studies show that ChatGPT is wrong 1 in 4 times and AI Overviews are also often wrong. Being extra aware and acknowledging when AI is wrong is key to success.

Mastering AI literacy also means knowing which tool to use and for what. For example, knew when and how to use Claude for writing, Perplexity for research or Nano Banana for visuals.

3. Move from task work to decision work

AI excels at execution. It struggles with judgment. If your job consists of routine, templated tasks, you are in the "Impact Zone." To move out of it, shift your focus. So, instead of spending two hours writing a market analysis report. Spend 10 minutes generating the report and the rest of the time interpreting the data. Then use AI like Gamma to create your presenation for strategic reccommendations for your boss.

In other words, think about where you spend the most time in your day and determine if AI is able to take over some of that work. From there, you're able to take on more of what really matters, which can help make you indispensable.

4. Double down on 'non-automatable' human skills

The more "digital" the world becomes, the more valuable "analog" skills become. AI cannot build trust, and it cannot navigate office politics or come up with the most creative ideas.

Use your human-ness for things like reading the room or feeling the tension in a boardroom for high-stakes negotions. Motivate a team through a pivot or define new ways of solving complex problems and then ask AI to do the problem-solving.

5. Transition to a 'human+AI' job title

While this may sound silly, this mindset shift is huge. Most successful professionals won't be replaced; they will be augmented. For that reason, consider how your role is evolving. For example, if your traditional role is a copywriter, think of it now as an AI content strategist and editor. Or if you're currently a finanicial analyst, think of yourself as AI-powered decision intelligence lead. Project manager? You'll soon be an AI systems architect and orchestrator. You get the idea. Jobs aren't going away as much as they are rapidly evolving.

The 18-month window means the tools you use today will likely be obsolete by next year. Career cycles that used to last decades are now shrinking to months.

Bottom line

Being prepared for a new work era is easier than you may think. Set aside an “AI hour” each week to explore one new tool or feature and stay platform-agnostic so you can pivot to whatever delivers the most leverage.

Here at Tom's Guide, we teach you all about the best prompts and how to use the latest tools to help you better understand the future of AI.

AI isn’t likely to take your job overnight, but someone who knows how to use it well might. Over the next 18 months, the real divide won’t be between humans and machines — it will be between people who actively grasp AI for productivity. The question isn’t whether AI will shape your work, but whether you’ll shape how it’s used.

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If you’ve ever opened a long report, contract or legal notice and felt slightly overwhelmed about not having the time to read through it or even having AI summarize it but missing important information, this hack is for you.. Reading everything carefully isn’t the hard part. Understanding what actually matters is.

We’re drowning in documents — contracts, PDFs, medical paperwork, workplace policies, HOA notices, insurance updates and endless school emails. I have every intention of reading through everything I am supposed to, but when time is of the essence, it’s not always easy.

That’s why I created what I call, the “reverse brief” prompt — a simple AI instruction that flips dense writing into a clear, actionable summary in seconds. This is not a summary. Because I can’t afford to miss anything, this prompt is not about summarizing what's there, it's about understanding the content and how it relates to me.

Here’s the prompt I use almost daily in both my personal and professional life.

What is the reverse brief prompt?

Most people ask AI to “summarize” a document, which is fine in a pinch, but AI almost always leaves out important information when prompted to do that. Summaries often stay too high-level.

The "reverse brief" prompt goes further by telling AI to identify the purpose, explain what matters most (not just state it), highlight risks or deadlines and clarify what needs to be done next.

So, instad of of shortening the document, it translates it into a decision-ready briefing. I like to think of it as having a personalized lawyer, project manager or executive assistant explaining the document to me. Of course, AI is not a replacement for those people, but it’s a good starting point.

The reverse brief prompt: “Create a reverse brief of this document. Explain the purpose in plain language, list the most important points, identify any risks, deadlines or obligations, and summarize what actions I need to take.”

This prompt works with any AI from Perplexity and ChatGPT to Claude, Gemini and others.

Why it works better than a normal summary

A standard summary tells you what the document says. This isn’t enough for me. The reverse brief tells you what the document means for you. If you have the memory feature turned on, that helps the AI elaborate specifically for you, too.

Because that distinction saves time and prevents costly misunderstandings. Now, instead of rereading paragraphs to interpret intent, you'll get priorities, context, consequences and next steps.

I’ve tested it across everyday paperwork and professional documents. It shines with legal and finanical documents (great if you're making a big purchase like a house or switching insurance policies), school paperwork (I use it for my daughter's IEP updates and district policy changes), workplace and HR documents (benefits changes, onboarding materials) or medical paperwork like treatment summaries or billing explanations.

In other words, if a document feels dense or intimidating, this prompt helps get to the heart of what you need.

How to get the best results

For even better output, add one line: “Assume I am not familiar with legal or technical language.”

Depending on the topic, I'll even ask AI to explain anything confusion or even to over-explain anything that could be easily misunderstood. If I'm using the information for a meeting, I'll also add, "What questions should I ask?"

Bottom line

There are many ways that AI is helpful, but summarizing isn't always one of them. That's why I've created several prompts for this very use. What we need is clarity, and this particular prompt, the "reverse brief" prompt, transforms overwhelming documents into clear decisions you can act on right away.

Let me know in the comments if you try it. I'd love to know how it works for you and what type of documents you utiilize this prompt.

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In a rare move for Silicon Valley, the $18 billion AI search startup Perplexity has officially walked away from advertising. The company is abandoning the sponsored placements it began testing in 2024, confirming it has no plans to bring them back.

This move underscores one of the biggest questions facing AI right now: should answers be funded by ads, or by users?

Why Perplexity is walking away from ad revenue

Perplexity’s core value proposition is a simple one: fast, sourced answers you can trust. Executives realized that introducing paid placements risks blurring the line between objective information and promotion.

Even with visible labels, company leaders believe ads could prompt users to second-guess the neutrality of the AI's responses. First reported by The Financial Times, one executive bluntly stated that the challenge with ads is that "a user would just start doubting everything."

The company is prioritizing its reputation as an objective "answer engine," noting that they are in the "accuracy business".

A completely different path than traditional search

For decades, search engines have relied heavily on scrolling past sponsored "blue links." AI search changes the dynamic. Because tools like Perplexity generate direct answers, users expect clear, unbiased results. If users suspect an answer is being steered toward a paying sponsor, the tool's credibility vanishes.

Rather than chasing ad dollars, Perplexity is now doubling down on alternative revenue streams including focusing heavily on its paid subscriptions, which range from $20 to $200 per month.

Perplexity is aggressively expanding its enterprise sales strategy to target high-powered professionals like CEOs, doctors, and finance experts.

Despite dropping ads, the startup's growth has been massive, reportedly reaching $200 million in annual recurring revenue by late 2025, according to the same Financial Times story.

Bottom line

Perplexity’s pivot highlights a growing philosophical divide across the AI industry. OpenAI recently began testing ads for free users in ChatGPT, while Google integrates ads into its AI Overviews in traditional search.

Perplexity is aligning itself with Anthropic (the maker of Claude), which has publicly committed to keeping its chatbot free of advertising.

With AI-generated answers increasingly used for everything from high-stakes financial research to medical inquiries, credibility is becoming the ultimate competitive advantage. By stepping away from ads, it's proof Perplexity is betting that strict neutrality will drive stronger long-term growth than short-term ad revenue.

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I once had a boss give me advice I’ve never forgotten: “Never call in sick on a Monday.” He explained that no matter how sick you really are, people assume you had “too much weekend” and are recovering. What he was really teaching me wasn’t about attendance — it was about perspective. How others see a situation can shape the story around it.

That idea stuck with me for years and eventually led me to create the empty chair technique, a method rooted in psychology and coaching. The concept is simple: imagine someone sitting across from you and verbalize your thoughts. Stepping outside your own head helps you see a problem more clearly and from a new angle.

With AI, the exercise becomes a clarity accelerator. Instead of sifting through your own thoughts, you externalize the problem and get grounded guidance in seconds. Give this a try with ChatGPT or your favorite alternative.

Here’s how it works and why it’s become one of the fastest ways to gain perspective and streamline workflow.

What is the 'empty chair' prompt?

This prompt works in every chatbot including NotebookLM, but I have found it works best with the new Gemini 3.1 Pro:

“Imagine my future self is sitting across from me. They’ve already solved this problem and feel calm and confident. What would they tell me to focus on right now? What should I stop worrying about? Give me the next three clear steps.”

Within moments, the noise quiets and the path forward becomes obvious. The prompt works because it forces a perspective shift.

When you’re metally absent or distracted, your brain loops through possibilities, worries and unfinished tasks. By imagining advice from a future version of yourself (or another trusted voice), you:

• reduce rumination
• clarify priorities
• externalize decision-making
• lower anxiety
• bypass perfectionism

It’s essentially a fast-track version of executive coaching (minus the hourly rate). I most often use this prompt when I'm stuck starting a task, overthinking a decision or facing a creative block. With the perspective of the job already being done, I gain new insight, stay calm and gain distinct clarity about what the finished project looks like.

This prompt could be especially helpful for someone who struggles with keeping deadlines or procrastination. Mental clutter is the real productivity killer.

But after running the prompt, my “future self” response boiled everything down to finishing tasks I start before moving on to another. Sometimes the brain drain comes from the perspective of having too much to do. When you use this prompt, you almost get an eagle eye view of what's possible.

Variations to try

One reason this prompt works so well is that you can adapt the “person in the chair” depending on what you need. Each variation shifts your mindset in a slightly different — but equally useful — way. Here are a few to try:

• Future self version. “What would my future self thank me for doing today?”
• Mentor version. “A trusted mentor is sitting across from me. What advice do they give?”
• Tough boss version. “My no-nonsense boss is here. What must get done right now?”
• Compassion version. “My kindest friend is here. What should I stop being so hard on myself about?”

Final thoughts

To this day, I've never called out on a Monday. Althought this prompt won't magically make the flu go away once the weekend is over, it will make Mondays more productive when the missing ingredient needs to be revealed.

By talking to "your future self" with this prompt or another type of "coach," you might find you work with more intention. The empty chair prompt doesn’t give you more hours in the day or a longer weekend — but I have found that it really helps me see things in new ways.

On days when your brain feels like everyone and everything is fighting for your attention, that clarity can make all the difference.

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Whenever I’m made aware of a new book, movie, video game, musical artist or general topic of interest, I quickly get sucked into a vortex of looking up every minute detail about whatever caught my attention.

During my introduction to the wonders of AI chatbots, all my more savvy advocates of the technology made me aware of ChatGPT, Perplexity, and Claude’s strong general research skills. For a good while, I’d utilize all three AI tools to do a deep dive into subjects I’d write about and ones that just happened to pique my interest once I found out about them (when a friend of mine told me a Brazilian mafia protected Michael Jackson during a local video shoot, I just had to see if it was true!).

After putting all three AI chatbots through their paces as my research associate, I soon found out about another AI tool that’s even better at researching anything and everything. That AI research companion is NotebookLM.

After taking the time to see whether it’s worth all the hype, I quickly realized that NotebookLM is at the top of my list of AI chatbots that offer the most comprehensive information on any topic I look up.

From fast research to deep research in seconds

Opening NotebookLM for the first time revealed a dashboard that can generate text, audio and even video overviews on nearly any topic. One of its most useful features is the ability to include your own sources — including uploaded files, websites, YouTube videos, Google Drive documents and copied text.

To test its research capabilities, I started with a simple question: “What are the 10 most influential video games of all time?”

NotebookLM offers two options when gathering information: Fast Research and Deep Research. Since this was a broad query, I chose Fast Research to see how quickly it could compile reliable sources.

Within about a minute, NotebookLM assembled relevant materials and generated a concise summary I could save as a notebook for future reference. I titled it The Most Influential Video Games of All Time.

The overview highlighted how landmark titles like "Super Mario Bros." and "Street Fighter II" helped revive the gaming industry and establish competitive standards, while games like "Half-Life" and "Dark Souls" pushed immersion through cinematic storytelling and challenging gameplay. It also touched on Pong’s role in launching commercial gaming, the rise of platforms like Steam and the growing influence of player-created content.

What set NotebookLM apart from ChatGPT, Perplexity and Claude was its ability to suggest smart follow-up questions that deepen research. In my case, it prompted:

• How have iconic games like Street Fighter and Mario shaped industry trends?
• What makes a game influential enough to enter the Hall of Fame?
• How do player-creators keep games like Skyrim relevant for years?

With everything saved in one place, the notebook evolved into a deeper research hub I ultimately renamed “Revolutionary Milestones and the Evolution of Modern Gaming.”

It also gives its users a wealth of options to create subject overviews

For my next topic, I chose to go the deep research route on a specific musical genre with this request: “Who are considered the top producers across the current electronic music landscape?”

NotebookLM took a lengthy amount of time to bring up the sources it needed for this music-based notebook and produced the top 38 sources it could find. After importing it all into a summarized piece, NotebookLM broke it down as follows:

“The provided sources offer a comprehensive overview of the global electronic dance music landscape in 2025 and 2026, highlighting major festival lineups, industry awards, and emerging genre trends. High-profile events like Coachella, Ultra Miami, and Skyline feature legendary acts such as Marco Carola and David Guetta alongside rising stars like Hannah Laing and Ninajirachi.

Industry reports from Beatport and DJ Mag track the commercial success of artists like HUGEL and Alok, while also noting the critical acclaim of producers like Tame Impala and Kaytranada.

The texts also identify a shifting sonic tide, where established styles like house and techno are being influenced by amapiano, UK garage, and hard techno. Furthermore, the collection explores the growing impact of micro-communities and technological innovations, such as AI-assisted production, on the future of the scene. Overall, these documents portray a vibrant, evolving industry defined by massive live performances, cross-genre collaborations, and a strong sense of community.”

NotebookLM includes several features that go above and beyond when putting your sources to work. I got a kick out of listening to an AI-produced podcast “between two hosts with shockingly high levels of personality” that cited all of the information I just researched. NotebookLM also gives its users the chance to produce an explainer video, a mind map, reports, flashcards, an interactive quiz, an infographic, a slide deck and a data table based on all the sources you find on any given issue.

Besides the aforementioned podcast, I was excited to see how the explainer video turned out. I began the AI video-making process by choosing the video’s format (I went with a more structured explainer instead of a brief one), its language, a visual style, and what my new AI tutorial hosts should focus on (“present this to a room full of electronic music fans”).

The final result was a pretty cool eight-minute-long video overview that I wouldn’t mind showing off to a group of electronic music enthusiasts and casual music lovers looking to dive into the genre for themselves.

Final thoughts

Chatbots are useful whenever I’m trying to find quick answers, but after taking NotebookLM for a spin, I recognized just how beneficial it can be for doing deeper research. It turns any topic I can think of into easily digestible formats that make learning easier and more enjoyable.

Listening to an AI-produced podcast about the best international cuisines, watching an AI-video explainer about the most important wars in American history and building an infographic around the worst comic book storylines from Marvel are just a few examples of the ways NotebookLM can turn a carefully researched topic into something more palatable for anyone eager to learn.

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• Perplexity Voice works as a Siri alternative on iPhone — here's how to use it
• Stop using 'summarize' — this Claude prompt extracts the insights you actually need

It’s hard to keep up with the onslaught of AI chatbots and other related technologies available these days.

Popular AI tools, such as ChatGPT, Gemini, Claude and Perplexity, are joined by a wide range of comparable options that are also evolving rapidly. And with so many companies relying on AI, it can feel exhausting and even a bit worrisome, given how much AI is becoming a major part of our daily lives. The continued evolution of AI tools has resulted in them working smarter and faster to complete the requests of their users.

Despite rapid advances in AI capabilities, public trust hasn’t kept pace. Surveys show growing unease about how AI is used today — and even greater concern about what it could do in the future. I’ve zeroed in on seven reasons why you and anyone you might know are trusting AI less than ever before during a time of breakthroughs with the popular technology.

AI is becoming smarter, yet it still makes mistakes

Conducting simple/long research, generating important notes (personal financial outlines and even legal document breakdowns, for example) and summarizing emails and uploaded documents are just some of the actions most AI chatbots can perform. And with that comes a sense of reliability that its most ardent users place upon it.

However, AI is still prone to having hallucinations when given easy or complex prompts, which can result in it producing inaccurate results. AI may be seen as an authoritative source of information for some, but many still recognize its faults and don’t place that much trust in its research capabilities.

AI slop is constantly in our feeds

The age of deepfakes is upon us, sadly. They range from somewhat innocent fakes (we’re sure your older family members have forwarded you excited messages about the AI movie and show posters they’ve shared on Facebook) to the sort of AI-generated images/video that fools people into believing hoaxes.

These days, it’s becoming harder and harder to discern what images, videos, and audio are real and which ones have been created by AI.

The rise of voice cloning scams, political misinformation, and visual content that looks shockingly real has raised the general public’s skepticism of AI.

AI is taking on more human work, fueling job anxiety

The ever-present fear of robots replacing humans in the workplace has seemingly become a reality with the introduction of AI.

Coding, writing, producing art/videos/music, handling customer service duties, and researching can be performed by AI, which has resulted in some companies relying on them instead of the humans that occupy the positions for those duties. The presence of Google Gemini has greatly impacted traditional search trends, which has led to a decrease in the number of visitors for SEO-driven news sites.

Just take a look at this troubling stat from the outplacement firm Challenger, Gray & Christmas, as reported by CBS: “In 2025, companies directly pointed to their use of AI in announcing 55,000 job cuts — more than 12 times the number of layoffs attributed to AI just two years earlier. Of those job losses, 51,000 were in tech, with most of the cuts concentrated in tech-heavy states such as California and Washington.”

With all that being said, it makes sense for employed and even unemployed workers to have a less-than-hopeful outlook on AI’s major impact on today’s uneasy job market.

AI is moving at break-neck speed

Every day, there’s a story about an upcoming update to AI.

The improvements to ChatGPT’s tone through its various models, Gemini’s further integration into search everyone’s Gmail accounts, and Peprlexity’s push to implement more real-time web integration for research are just some of the sudden improvements that AI and even non-AI users can’t keep up with.

What’s concerning about the fast pace of AI evolution is the seeming lack of stronger regulation regarding AI from the companies that empower it and federal/state officials from the political space.

Add the fact that several states have propped up AI data centers that have resulted in water/electricity overconsumption and you have even more reasons for AI cynics to continue looking at the breakneck pace of AI upgrades with a weary eye.

There’s skepticism over the major hype regarding new AI features

Lofty promises like these are a dime a dozen whenever AI enters the conversation. And to be quite honest, this hyperbole can prove to be exhausting when the positive changes made to AI are more incremental upgrades in some cases, instead of being the life-changing improvements they’re hyped up to be.

AI is certainly getting better, but the sky-high expectations tied to its evolution have resulted in its doubters not taking the bait every time a major promise about the technology hits their timeline.

Data privacy is a growing concern

Whenever you hear that Google Gemini is observing and handling the data contained in your Gmail and Docs, it makes sense for you to be suspicious of an AI tool having access to your personal information.

Privacy concerns over AI having access to your information are growing—the complex actions that AI chatbots execute in connection with your prompts, emails, documents, and search queries have led to users asking AI companies about where and how their information is stored and used.

It’s no shock that AI users are growing more worried about the privacy of their data when using AI.

AI is becoming less of an optional endeavor and more of a default one

Even if you don’t consider yourself an active user of AI, its presence is embedded in nearly everything you do on the web.

AI isn’t just confined to a chatbot tab anymore—Gemini gives search result summaries when you look stuff up on Google, Claude is integrated into productivity apps such as Slack, and other AI-powered features are popping up across smartphone user interfaces.

AI’s growing switch from an optional tool to more of a default one in some cases has resulted in people becoming more resistant to its growing existence across various platforms.

Bottom line

Although AI developments are intriguing, we can't ignore the concerns. The issues people have about the hard-to-ignore technology and the negative ways it has impacted modern-day society are valid.

Public opinion may never swing fully for or against AI, but addressing these concerns is essential to building broader trust.

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• Real vs AI: Can you spot the fakes in these Valentine’s Day videos?

Valentine’s Day is one of the most stressful holidays of the year for a lot of people.

I’ve watched friends spiral at the thought of planning the perfect date, picking the right gift or coming up with something original once mid-February rolls around. And honestly? I get it. Even the most romantic among us can hit a creative wall when we’re trying to plan something meaningful — especially when expectations are high and chocolates are overpriced.

So here’s a suggestion that might actually take the pressure off: use Gemini. But more specifically, instead of relying solely on Gemini the chatbot, these tips work best in Google’s AI Mode in Search — where answers are synthesized from real-world data, local availability and web results.

Here are six smart AI search tips to help you plan a smoother, more thoughtful holiday — plus a bonus tip for anyone celebrating Galentine’s Day (shout-out to Parks and Recreation).

Bookmark this post and come back to it every February — you’ll thank me later.

Why AI Mode in Google Search — and how it matters for real-life planning

While many people think of Gemini as a chatbot, Google’s AI Mode in Search brings similar intelligence directly into search results.

Instead of returning a list of links, AI Mode generates a synthesized response that blends information from across the web with real-world data about places, products and availability. The result feels less like searching and more like getting a personalized answer.

That’s especially useful when planning something time-sensitive — like Valentine’s Day.

You can ask:

• “Romantic restaurants near me with outdoor seating and reservations available tonight”
• “Last-minute Valentine’s gifts I can pick up nearby today”
• “Chocolate shops open late with the best reviews”

AI Mode pulls together options, availability and relevant details so you can make a decision quickly without opening multiple tabs.

And there's an even more personal layer of search with Google's expanded Personal Intelligence within AI Mode. When enabled, this feature can use context from sources like Gmail and Photos to deliver more tailored results — for example, surfacing restaurants you’ve visited before or suggesting places near upcoming reservations.

1. Arrange amazing plans for your V-Day date-night

Putting something lovely together for the actual evening when you and your partner head out for a lovey-dovey handout is tough. Before you make those expensive reservations at a five-star restaurant or any other place of your choosing, it might be best to revert to Gemini for some assistance. A prompt like this will work:

“Plan a 3-stop Valentine’s Day date in [City Name] that includes a couples massage, a restaurant with skyline views, and a dessert spot.”

It could also be worth asking the AI for ideas on how to set up dates based on different concepts, such as picking the best places in your hometown for roller or ice skating, pottery or cooking classes, and art galleries or live jazz performances.

Luckily, Gemini helps find available reservations for your favorite restaurants. It will even go as far as bringing up booking platforms and putting a list of all the options you can reserve.

2. Find the perfect wines to pair with your entree for the evening

So you want to get extra fancy with your partner during a night in for some home-cooked dinner. The perfect drink to accompany your choice of entree should be some sort of wine, correct? This loaded prompt is just an example of what you could ask Gemini as your wine expert:

“I'm making spaghetti with chicken parmigiana and a side of roasted brussels sprouts for Valentine's Day. Recommend three distinct wine pairings: one classic, one adventurous, and a cheap option under $20. Explain why each wine complements the meal."

I used these prompts and it gave me these three delectable choices:

• Chianti Classico (Sangiovese): Chianti (especially a Classico) is the quintessential Italian red for tomato-based dishes. Its bright acidity matches the tang of your marinara sauce and cuts through the richness of the cheese and breaded chicken. Earthy herbs and savory notes also play nicely with roasted Brussels sprouts
• Orange Wine (Skin-Contact White): Orange wines (white wines made with skin contact) have texture and tannin that give them almost red-wine energy, yet they’re still aromatic like a white. They’ll pair beautifully with both the tomato sauce and the roasted Brussels sprouts’ nuttiness. Think of it as a fresh, funky bridge between your components
• Montepulciano d’Abruzzo (Under $20): Montepulciano delivers great value with juicy berry fruit and balanced acidity that plays well with tomato sauce and rich, cheesy chicken. It’s usually medium-bodied and forgiving — hearty enough to stand up to this meal without overshadowing it

Feel free to pick up a bottle of any of those three picks if you’d like.

3. Come up with creative and thoughtful gifts

You can go the simple gift-giving route if your partner is easy to please. Or you can go deeper and find something that perfectly complements their favorite celebrity, book, clothing brand, or whatever else they’re super into.

Now you could ask your Gemini-turned-V-Day planner, “show me heart-themed items under $50 that look high-end," or get more specific and ask, “my partner loves books written by Nicholas Sparks. Show me his most recent books, where I can buy them, and their lowest prices.”

Getting creative (or basic) as possible with your V-Day gift giving becomes an easier process with AI, giving you plenty of options to choose from.

4. Plan a getaway together

If you and your partner have ever taken a trip you still talk about — maybe a sun-soaked getaway, a romantic city break, or a food-focused adventure — Valentine’s Day is a great moment to bring it back into the conversation.

Instead of trying to guess the “perfect” next destination on your own, let Gemini do some of the brainstorming for you. Try a prompt like this:

“My partner and I loved our trip to [Location] last year. What are a few destinations with a similar vibe that we could consider visiting in 2026? I want to bring one up during our Valentine’s Day date.”

This gives you thoughtful, tailored options you can casually work into conversation — without the stress of planning an entire trip on the spot.

5. Add some great rom-coms to your streaming playlist for a chill evening

If you and your partner would rather stay in for Valentine’s Day (honestly, same — especially if you’re dealing with brutal winter weather), a low-stress plan is to curl up with a great rom-com.

The problem? There are so many options that picking just one can turn into its own mini date night debate. To spend less time scrolling and more time actually watching, let Gemini narrow things down for you with prompts like these:

• “What are some rom-coms currently streaming on [Streaming Service] that use the friends-to-lovers trope and were released in the last 10 years?”
• “What are some rom-coms currently streaming on [Streaming Service] that use the enemies-to-lovers trope and were released in the last 10 years?”
• “What are some rom-coms currently streaming on [Streaming Service] that use the accidental-lovers trope and were released in the last 10 years?”

These prompts help you zero in on exactly the kind of romance you’re in the mood for — without the endless browsing.

6. Get the kids involved

So you’ve already locked in your Valentine’s Day plans. If you have young kids, you’ve probably arranged for them to spend the evening at a grandparent’s house or with a babysitter while you’re out.

Before you head out the door, you might want to make sure your little ones have their own plan for a fun night — not just a long stretch of screen time.

Here’s a simple prompt you can give to Gemini to help set them up with activities they’ll actually enjoy:

“My [age] child/children will be staying at my grandparents’ house while we’re out for Valentine’s Day. Their favorite things are board games, coloring books, and toy cars. With those interests in mind, what are some fun activities you’d recommend for them?”

7. Plan a memorable Galentine's Day for you and your closest gals

Here’s a special bonus AI search tip for any ladies out there who are basking in the joy of Galentine’s Day instead of Valentine’s Day. For those of you not in the know, Galentine’s Day is celebrated on February 13 and is a global holiday that’s all about celebrating women’s friendship. If you’re an avid Parks and Recreation fan, then you already know how this holiday first came into existence.

Work with this AI prompt to set you and your girlfriends up with the perfect hangout the day/night before all the couples take over everything for Valentine’s Day:

“My group of [Number] girlfriends and I want to celebrate Galentine’s Day. We live in [City Name] and want to go to a nice Italian restaurant and a karaoke bar afterward. Give me some recommendations for both.”

Bottom line

Setting up a memorable Valentine’s Day celebration shouldn’t stress you out—it should be a relaxing affair, especially since Gemini can step in to give you some valid recommendations for whatever you’re planning.

For busy moments — and last-minute holidays — AI Mode makes a difference that can save time, reduce stress and make planning feel almost effortless.

Put these tips to good use and refer to them every year before every V-Day to make your annual planning period less of a chore. Fingers crossed that your plans impressed your partner and got you extra kudos for the biggest lovey-dovey holiday all year round.

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One day, I had a simple realization: instead of retyping the same prompts over and over, why wasn’t I just saving them?

That question changed how I use AI.

From there, I started thinking bigger — not about “better prompts,” but about better systems. If AI is supposed to save us time, using it shouldn’t feel like extra work. For me, that meant turning my favorite chatbots into something closer to digital assembly lines rather than one-off assistants I had to constantly retrain.

Once I stopped over-prompting and started building repeatable routines, ChatGPT, Gemini and Claude became dramatically more useful in my day-to-day work as a journalist.

Here are three habits I adopted that now save me up to 10 hours a week — and could make your own AI workflow faster, smoother, and far less frustrating.

Create and save reusable prompts for daily tasks

During my days as a novice with AI, I got into the habit of repeating the same requests over and over when I asked my chatbots to compose a professional email, an article aimed at gamers who enjoy fighters, a social post meant to attract fellow All Elite Wrestling fans, and more. Eventually, I built myself a Google Doc full of reusable prompts designed specifically for those kinds of AI requests and more. My rule became “if I typed out a prompt more than once, I might as well save it for later use.”

For example, during my freelancing hustle, I used to repeatedly ask different chatbots to “write a professional email summarizing my experience as a journalist and offering my services as a freelance writer.” After typing out some version of that prompt more times than I can count, I finally created and saved a custom version that included my background, preferred tone, and specific goals for those outreach emails.

This is where ChatGPT is especially useful. You can go into its settings, open Personalization, and add custom instructions that shape how it writes — from tone and style to how formal or casual you want it to be.

Split a massive request into more focused assignments

I’ve always loved that you can ask one AI chatbot to research a topic, outline the key points, and turn it into a polished article in minutes. But I started noticing that my “do everything” prompts sometimes led to small mistakes — the kind I knew another chatbot wouldn’t make. That’s when I began dividing big tasks across my three favorite AI tools based on what each one does best.

When I set out to write a brand-new anime-themed piece about the most powerful "Dragon Ball Z" characters, I kicked things off with ChatGPT to brainstorm headline ideas. Then I turned to Perplexity to gather accurate, up-to-date information with clear sources to help structure my article.

Once I had a draft, I handed it over to Claude for final edits, since it’s one of the strongest AI tools for refining writing. Treating AI like a relay race — with each chatbot taking the baton for the part it’s best at — helped me work faster, think more clearly, and avoid overloading any single tool.

Let AI brainstorm your plans, then turn the best ideas into polished first drafts

Writer’s block is one of my most mortal foes. I tend to have tons of lightbulb moments whenever I’m asked to cook up a new pitch, but I just as many moments of falling into a creative drought. I got tired of running into a mental wall and began using my top AI chatbots to become my idea generator and first draft producer.

I began saving more time for actually writing out my pitches instead of sitting in complete silence while trying to come up with my initial concepts. It’s always worth reaching out to your chatbots to get the ball rolling on turning your imperfect thoughts into fully-realized plans.

ChatGPT became my go-to for cooking up short first drafts, while Claude stood out for producing longer and more detailed drafts. Gemini is also a godsend for generating drafts since it can pull information from my Gmail messages, Docs, and spreadsheets to build the context it needs for first drafts.

I also used my chatbots to turn my wall of notes into more structured instructions and even spread them across easy-to-read charts for future reference. Rewriting is a part of the job for a writer such as myself. But I began saving time by asking my AI assistants to generate the sorts of ideas and first drafts that could inspire me to zero in on an idea and follow a structure that works.

The takeaway

By adapting these three practices, I saved myself more time for the more creative endeavors in my life. Saving my most-used prompts for later use, splitting the work of one chatbot among several others, and being presented with starter ideas that can then be turned into first drafts morphed into my three most reliable routines whenever I used AI.

Get out of the practice of over-prompting your AI of choice and cut your work time in half by building a workflow that emphasizes smarter personal habits.

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There was a moment recently when I realized I needed an AI filter. Not the kind of filter that blurs fine lines and imperfections, but one that shines a spotlight on errors and brings them to the forefront of every response.

Not many people know this, but ChatGPT is wrong a quarter of the time. And, those AI Overviews we often rely on heavily for summaries, are also not always accurate.

For a long time, I thought I needed to ask better questions to get a more accurate response. For me, that meant, if an answer was off, I assumed the fix was a sharper prompt, more detail or clearer instructions. I treated ChatGPT, Gemini and Claude like machines that just needed the right input to produce the right output.

But once I developed a small filter, it changed everything.

What most people (including me) do wrong

I caught myself making the same mistake over and over. I wasn’t blindly trusting AI — but if a response sounded confident, organized and well written, I usually accepted it. It looked fine, so I moved on.

But, "good enough" can lead to a lot of issues, especially in the workplace. For example, a timeline that looks clean, might ignore real constraints or an explanation that seems clear, might gloss over key facts.

None of these appear to be catastrophes at the time, but small missteps can add up. And if you're using AI for producivity, the last thing you want is more work because it messed up.

Most of ChatGPT users treat AI like a slightly magical search engine. They ask a question, get an answer and move on. And while it works most of the time, the approach has a flaw for anything more complex.

AI is optimized for confidence and fluency, not caution. It can easily:

• Fill in missing context
• Make reasonable assumptions
• Smooth over uncertainty
• Skip steps in its reasoning

But the issue is, although the answer is clean, it's not necessarily reliable. The issue isn’t that AI is “bad.” It’s that we’re often passive readers of it.

That’s what I wanted to change. My small filter (the thing that changed everything)

Now, every time I get an AI response, I pause for about 10–15 seconds and run it through three simple questions in my head:

• What is this assuming?
• What might be missing?
• What would have to be true for this to be wrong?
• Does it need a source or fact check?

To be clear, I don’t always type these into ChatGPT. This isn’t a prompt, it's a mental filter that I apply after I get an answer.

Sometimes the answer sails through. Sometimes it immediately reveals weak spots. Either way, I’m no longer consuming AI passively — I’m evaluating it deliberately.

Why this works so well

This tiny habit does three things:

• It slows me down just enough. Not to overthink — just enough to avoid rubber-stamping a polished response.
• It surfaces hidden assumptions. AI often assumes things you never said (deadlines, budgets, priorities, constraints). My filter forces me to notice that.
• It shifts AI from oracle to thinking partner. Instead of asking, “Is this correct?” I’m asking, “Under what conditions is this correct?”

As AI integrates into our workflow more often, it's important to keep this filter, or one like it in your mental tool because. The filter doesn’t make AI smarter — it makes me a better reader of AI.

Real world examples

I use this filter naturally now every time I use any chatbot. For example, recently when planning a big project, I asked ChatGPT to help me map out a multi-week timeline. The first version looked beautifully structured. In fact, too beautifully structured to a point I knew it was missing something.

So I ran my filter and asked myself: What is this assuming?

Turns out — a lot. Everything from the chatbot not taking into account how easy it would be to schedule meetings, that everyone would approve my ideas quickly or that I had a dedicated team.

Once I saw those flaws in the response, I adjusted my constraints. The revised plan was far more realistic — and far more usable. The filter saved me from building on shaky ground.

Similarly, I asked Gemini to explain a concept in plain English. And while the explanation was clear, it felt a little too neat.

My filter kicked in: What might be missing?

That question led me to notice a simplification that, while helpful, was technically misleading. I followed up, got a more nuanced version, and actually learned more in the process.

The filter didn’t prove the answer “wrong.” It made it more trustworthy.

Finally, I tested it with Claude to tighten a paragraph. It suggested shorter sentences and cleaner structure — all reasonable. But my filter made me ask: What would have to be true for this to be wrong?

I realized the edit assumed clarity should always beat voice. That wasn’t my goal. I kept the structural improvements, but restored some of my tone.

Instead of blindly accepting AI’s edit, I collaborated with it.

Bottom line

This filter can be used with any AI or chatbot. You don’t need a new tool, setting, or subscription. Just try this the next time you get an important AI answer. Read the response once normally, then ask yourself what might be missing and follow up with a prompt based on what you noticed.

You really don't need to do this every time — only when you're dealing with complext projects or the response feels too generic or completely inaccurate. And remember, this filter has it's limits. It won't eliminate AI errors, you still have to do the critical thinking and fact-checking, even if it means using a prompt like "cite the source."

This small mental filter is now part of every AI conversation I have, and it’s made the biggest difference in my results.

More from Tom's Guide

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• What is Moltbook? Inside the bizarre social network built for AI agents
• I use the ‘pacer’ prompt with ChatGPT every day — here’s how it helps me finish things

I admit Perplexity is not my first choice for AI. I honestly forget about it most of the time because I rely so heavily on what I call the Big Three: ChatGPT, Gemini and Claude. Before really diving into everything Perplexity can do, I thought of it as an AI search engine with citations. You know, type a question, get a clean summary, click a source or two and move on.

That is, until I started using Perplexity more deliberately. Once I look beyond the search bar, Perplexity turned into a research assistant, comparison engine and productivity shortcut that has saved me real time in my daily workflow. If you’ve only used Perplexity at surface level, like I was doing, these are 10 features worth trying.

1. Focus modes actually change how answers are generated

For starters, one detail that’s easy to miss is the row of topic shortcuts under Perplexity’s search bar — options like Parenting, Travel, Health, Web, Academic, Writing or Math changes which sources it prioritizes and how answers are structured. These context presets are similar to ChatGPT’s custom GPTs, Gemini Gems or Claude Artifacts, because they shape how answers are generated.

Tapping one nudges Perplexity toward different sources, tone and structure before you even finish typing your question. It’s a small UI detail, but it can noticeably change the quality of the response — especially if you want advice that’s more practical, less technical or tailored to a specific situation.

2. Model picker: choose how Perplexity thinks

One of Perplexity’s most powerful features is easy to overlook: the model picker. Unlike Focus modes or topic shortcuts, this lets you choose which AI model powers the response — and the difference can be noticeable depending on what you’re trying to do.

Inside Perplexity, you can switch between models optimized for different strengths, like faster answers, deeper reasoning or more natural writing. Some models are better for quick fact-finding, while others shine when you’re asking nuanced questions, comparing arguments or refining language.

The key is that Perplexity keeps its citation-first approach no matter which model you choose. In other words, you can adjust how the answer is generated and cater your model to whatever it is you’re asking. If an explanation feels shallow or overly verbose, switching models can often fix it without changing your prompt at all.

It’s a subtle control, but once you start using it intentionally, the model picker turns Perplexity from a single tool into a flexible research setup.

3. Follow-up questions keep full context

Unlike traditional search, Perplexity treats follow-up questions as part of the same conversation, so you don’t have to restate context every time you refine what you mean. It actually gets what you’re asking, so you can start with a broad question, then narrow it step by step as you learn more.

Because Perplexity remembers the thread, the answers stay anchored to your original ask, which makes complicated topics feel far easier to break down and understand.

4. Clickable citations that actually matter

Unlike a lot of the chatbots I’ve used, Perplexity lists citations and even numbers them so each one jumps straight to the source behind the answer. It’s one of the quickest ways I’ve found to verify and accuracy-check an AI output. It’s why I trust it more than chatbots that don’t show where their information comes from.

5. Ask it to compare sources, not just summarize

Speaking of citations, here’s a surprisingly powerful trick most people miss: ask Perplexity to analyze its own sources instead of just summarizing them.

Try prompts like:

• "What do these sources disagree on?”
• “Which source is most critical, and why?”

Rather than blending everything into a single neutral answer, Perplexity surfaces disagreements, highlights bias and explains where perspectives diverge. The result is more contrast; more nuance and a much clearer understanding of what’s actually being debated — not just what the consensus sounds like.

6. Use it as a shopping comparison engine

You can also use Perplexity as a product comparison engine by asking it to weigh recent reviews, specs and pricing across multiple sources at once. Because every claim is cited, it’s easier to spot outdated information, sponsored reviews or product hype that doesn’t hold up.

I appreciate that I can use Perplexity easily without scrolling through pages of sponsored shopping results, and can quickly see exactly where each detail comes from, then decide if any given product is worth buying.

7. Ask for charts or timelines instead of explanations

Perplexity is especially good at generating timelines and charts, which I’ve found far more helpful than long explanations for complex topics. Instead of wading through dense paragraphs, you can ask it to map out how something unfolded over time.

Try prompts like:

• “Give me a timeline of how this developed”
• "Break this into key milestones”

The result is a clearer, more memorable way to understand complicated ideas — without getting lost in a wall of text.

8. Rewrite answers for different audiences

This one surprised me — especially since I’ve always thought Claude was the gold standard for tone. Perplexity handles tone shifts far better than I expected. You can ask it to explain the same topic for a child, a beginner or a professional, and it adjusts the language without watering down the facts. It’s a subtle feature, but incredibly useful when you need clarity without oversimplifying.

9. Treat it like a research collaborator

When it comes to research, Perplexity really shines when you stop asking for answers and start asking for help thinking. Instead of returning a single response, it can help surface gaps, angles and questions you might not have considered.

Try prompts like:

• "What questions should I be asking about this?”
• "What’s missing from this discussion?”

This simple shift turns Perplexity from an answer engine into an idea generator — especially useful for research, planning and early-stage thinking.

10. Ask it to show its uncertainty

Chatbots aren’t always accurate — we know that by now. What makes Perplexity different is how easy it makes fact-checking part of the process. One of the smartest ways to use it is to ask where the limits are instead of assuming the answer is complete.

Try prompts like:

• “Where is the evidence weak?”
•  “What isn’t well established yet?”

Perplexity is surprisingly good at flagging gaps, open questions and areas where the data simply isn’t there — something many AI tools gloss over in favor of confident-sounding answers.

Bottom line

After spending real time with Perplexity, I’ve realized it’s far more than just an AI search engine. It’s a full-fledged research tool hiding in plain sight. If you’re only using it for quick answers, you’re barely scratching the surface of this free AI tool.

Once you start leaning on features like citations, source comparisons, timelines, model selection and context-aware follow-ups, Perplexity suddenly feels like a genuine AI assistant that thinks alongside you in real time. And, when used intentionally, it goes far beyond traditional search to a point that it genuinely feels hard to replace.

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AI assistants are having a main character moment. Within the last three years AI has become far more integrated into our lives than ever. They can write emails in seconds, summarize a 40-page PDF like it’s nothing and build a vacation itinerary that looks suspiciously like something your most Type A friend made at 2 a.m. They’re fast, confident, and genuinely useful when you know what to ask.

But after testing chatbots daily, I’ve learned the smartest way to use AI isn’t to treat it like it has all the answers. These tools aren’t geniuses — and between hallucinations and plain old wrong information, they can still lead you off track fast. The goal is to treat AI like a powerful tool that still misses some very human instincts.

Because for every “wow, that saved me 30 minutes,” there’s a moment where AI confidently gives you something that sounds right, but clearly isn't. Or it gives you a technically correct answer that’s totally wrong for real life.

Here’s what AI is actually great at right now — and where it still falls short (even when it sounds like it knows exactly what it’s doing).

What AI does well

1. Structure

AI shines when your brain is overloaded and you need organization and structure. Computers have always done well with patterns, so using AI to build a better workflow is a no-brainer.

Drop in a messy list of thoughts, a long email thread or a half-baked plan and most chatbots can turn it into something clean and usable — a checklist, an outline, a timeline or a step-by-step plan.

It’s especially good at:

• Breaking big goals into smaller tasks
• Summarizing long documents into key points
• Creating templates you can reuse (emails, plans, schedules)
• Turning scattered notes into organized sections

If you’re someone who struggles with starting, AI can be the push that gets you moving.

2. Drafting fast, decent first versions

AI is a “first draft machine.” It can outline a 20-page thesis paper as easily as it can draft a short email. If you’re looking for ideas to craft a product description or meeting agenda, it’s a great place to start because it can spit out copy in seconds. It’s why so many lean on AI as a default writing partner.

While the outline it gives you isn’t completely useable, it can help get the wheels in motion to help you generate something useable. The secret to leaning on AI for writing support is to remember that it’s generating a very messy draft; not a final masterpiece.

3. Explaining complicated things

One of the most underrated AI skills is translation. And while it can literally translate language, what I really mean here is that it can translate even the most complex topics into something anyone can actually understand.

Ask it to explain:

• a confusing tech concept
• a medical term
• a finance rule
• a legal document
• a weird error message

AI will usually deliver something clear, calm and easier to digest than whatever you found on Google.

Even better: you can ask follow-ups without feeling awkward.

4. Helping you make decisions faster (when the stakes are low)

AI is surprisingly good at quick comparisons — especially when you’re choosing between options that don’t have a “right” answer.

For example:

• “Which laptop is better for my needs?”
• “Give me pros and cons of switching jobs”
• “Help me pick between these two travel itineraries”
• “Compare these two budgeting plans”

When you’re stuck in indecision spirals, AI can help you see the tradeoffs and move forward.

5. Being available, patient and non-judgmental

This one sounds cheesy, but it’s the reason so many people lean on AI for help.

AI doesn’t get annoyed when you ask the same question three times. It doesn’t judge you for not knowing something. It doesn’t rush you.

That makes it uniquely helpful for:

• anxious planners
• people who need reassurance to take action
• anyone who struggles to organize thoughts out loud (it's me!)

Even when the advice isn’t perfect, the experience of being guided step-by-step can be a game changer.

Where AI still falls short

1. It can sound confident while being wrong

This is the big one. AI often answers like it knows — even when it doesn’t. Even worse? It won’t tell you that it doesn’t know. It will write so confidently that you may not even realize the information is false until it’s too late.

But the truth is, AI regularly gets facts wrong. Sometimes it fills in gaps. Sometimes it invents details. And the scariest part is that it can do it in a polished, believable tone.

If you’re using AI for anything that matters — health, money, legal issues, safety, major purchases — you have to verify. Because AI isn’t designed to be correct. It’s designed to be helpful. And those two things don’t always overlap.

2. It struggles with context and real-world nuance

AI can give a good general answer… and still miss what’s actually happening in your situation.

For example, it might give you advice that sounds reasonable, but ignores:

• your time constraints
• your budget
• your personality
• your job dynamics
• your emotional state
• what you’ve already tried

Keep in mind that it’s guessing based on patterns. That’s why AI can be brilliant at planning and terrible at understanding what you’ll realistically follow through on.

3. It’s not great at originality (even when it looks like it is)

AI can generate creative ideas, sure. But it does not have the mindfulness or scope to be truly creative. A lot of what it produces feels like “the internet’s safest average.”

You’ll see it in:

• generic marketing ideas
• cookie-cutter advice
• predictable jokes
• repeated words and phrases with every ask

AI can be creative to an extent, and you can use it to help spark your own great idea, but you really often have to push it into originality with better prompts, constraints or your own taste guiding the output.

Otherwise, it defaults to what sounds most familiar.

4. It can’t reliably do human judgement

AI can mimic the 'taste' that we have as humans. The kind that can read a room, understand an audience or switch gears depending on the situation. This type of 'taste' can't be crafted with patterns because it simply doesn’t actually have judgment the way a human does.

It can recommend things that are technically correct but emotionally wrong — like suggesting a “professional” email that reads cold, or a “funny” caption that feels cringe.

Humans understand vibes. AI approximates them. That’s a huge difference.

5. It’s not a replacement for thinking

This should really go without saying, but the more AI infiltrates into our society, it’s worth remembering, AI cannot replace your human intelligence or your gut instincts and curiosity.

If you ask me, this might be the most important limitation of all. AI can speed you up, but we need to slow down and take a look at what it is actually delivering. In other words, think through the response.

If you use it to avoid thinking, you’ll end up with:

• weaker writing
• shallow ideas
• sloppy decisions
• answers you may not fully understand or are completely wrong for the situation

The best use of AI is extending your own knowledge — like a calculator for words, planning and problem-solving.

Bottom line

After months of testing every chatbot I can get my hands on, here’s the simplest rule I’ve landed on:

Use AI for speed. Use your brain for judgment.

Let it generate drafts, summaries, ideas, lists and options. But when you need accuracy, ethics, taste or truth? That’s still lands on your shoulders. As humans we can’t outsource those principles. And if you treat it like a tool instead of an oracle, it becomes a lot more useful (and a lot less risky).

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Ever since I started using AI chatbots to curate my hobbies, it’s been way easier to find new games to play, movies to watch and anime to binge.

But this time, I wanted something more practical: saving money.

Between video games, comic books, anime, art books and sneakers, it’s dangerously easy for me to spend a paycheck on “just one more thing.” And I had five items sitting in my Amazon wishlist for months, basically daring me to impulse-buy them at full price.

So instead of hitting Add to Cart, I ran an experiment.

I asked ChatGPT and Perplexity to help me track down the best deals — and see which one could actually shop smarter. After testing them on three of the items from my wishlist, one AI assistant clearly came out on top.

1. The Astro Bot PS5 DualSense Controller

I have to hand it to Sony — they really know how to make a PS5 DualSense controller so good-looking it makes my solid-colored ones feel embarrassing.

The one that got me this time? The Astro Bot DualSense (the “Joyful Edition,” thank you very much). That little mascot and his two PS5 platformers unlocked my inner child, so I’ve been dying to add the controller — especially with Astro Bot’s signature blue eyes staring back at you from the touchpad — to my growing DualSense collection.

But I wasn’t about to buy a used one.

I wanted a brand-new Astro Bot controller at a price that didn’t make me physically flinch before tapping “Buy Now.”

So I did what any responsible adult with a gaming habit would do: I asked AI to help find me the best deal.

First, I went to ChatGPT and asked it to find the lowest price for a new Astro Bot DualSense in the United States.

It came back with a ton of useful info, including:

• New/retail buying options
• Used/resale listings
• Higher collector pricing
• Notes on current pricing trends

And even photos of listings plus direct links to retailers like GameStop, Wafuu, eBay and Mercari. It practically gave me a full mini-shopping guide.

Next, I ran the same question through Perplexity to see if it could beat ChatGPT at deal-hunting.

Perplexity did what it does best: it cited sources as it listed the Astro Bot DualSense’s lowest prices and where to buy it. The links it pulled from places like PriceCharting, Target and Wafuu were genuinely helpful, especially because they showed exactly where the info came from.

But compared to ChatGPT, it felt more like “here are the sources” and less like “here’s the smartest way to buy this today.”

Winner: ChatGPT

ChatGPT wins round one easily. Not only did it give me more complete pricing info across new and resale listings, but it also added the bonus features I actually care about when I’m shopping: photo listings and direct purchase links from a bunch of retailers I already use.

And yes, I ended up going with GameStop, which shocked me almost as much as the deal itself.

They had the lowest price I found: $89.99 for regular customers, or $85.49 for GameStop Pro members — which made it way easier to justify the purchase without feeling like I needed to apologize to my credit card.

2. My first air fryer

I swear everyone in their mid-to-late 30s has discovered the wonders of air fryers and now uses them to cook basically everything they can think of.

Half my friends got one as a wedding gift. The other half bought one for themselves. And a few of them straight-up “borrowed” one from their parents.

Either way, I’ve officially reached the point where I can’t ignore it anymore. It’s time for me to join the air fryer craze and finally add one to my kitchen appliance closet.

But I’m not trying to spend a fortune on something I’m still learning how to use — so I decided to do what I’ve been doing a lot lately: let AI shop for me.

Round 1: ChatGPT

First up was ChatGPT. I asked it to find the best and cheapest air fryers available right now, and it came back with a flood of useful info that immediately made me feel like I wasn’t about to break the bank.

It even organized the picks into price tiers, like:

• Very budget-friendly (under $60)
• Mid-range affordable ($50 to $90)
• Bigger but still reasonable ($70 to $100+)

That breakdown alone was a lifesaver, because air fryer shopping gets overwhelming fast. ChatGPT also hit me with a few tips I actually needed, like:

• Pay attention to size vs price
• Don’t overpay just because it has a million features
• Watch for sales, because air fryers go on sale constantly

So far, so good.

Round 2: Perplexity

Next, I ran the same question through Perplexity — and it took a different approach. Instead of just giving me options, it grouped its recommendations into two categories: best overall performers and best budget options (cheap but still good).

It also explained that its picks were based on expert tests and buying guides, which made the whole thing feel a little more “I did research” and a little less “I’m guessing.”

Then it did something I really liked: it gave me a deal-hunting method.

For example, it pointed me toward the Ninja Max XL, then basically told me to compare prices across the usual suspects — Amazon, Walmart, Target, Costco/Sam’s, Kohl’s and Best Buy — to find the lowest one.

And when I told Perplexity my rough budget ($90) and how many people I cook for (three), it got even better. It dropped a chart on my screen with four strong options and even more buying tips to consider.

Winner: Perplexity

ChatGPT was super helpful — especially with the clean price tiers and quick tips — but Perplexity did more to convince me I was buying the right air fryer.

It narrowed things down based on my budget and the number of people I’m feeding, and that’s how I landed on the Cosori TurboBlaze, which I found on sale for $89.99.

ChatGPT’s photos and direct links are always helpfu, but Perplexity felt more like a friend who actually knows what they’re talking about when it comes to appliances.

3. The Nike Men’s Air Force 1 ‘07 Sneaker

Yeah, I’m a sneakerhead — one side of my bedroom is basically a shrine to Puma, Converse, Nike and Adidas. It’s been a minute since I bought new kicks, so I decided to treat myself to the brown/purple Nike Men’s Air Force 1 ’07.

First, I ran to ChatGPT to find the lowest price. It pulled up cheap listings from places like eBay, GOAT, Flight Club and Lyst, plus gave me price context based on size, condition and seller. When I narrowed it down to brand new, size 12, it came back with photos, direct buy links, a quick price chart and even prices from official retailers like Nike and Foot Locker.

Then I checked Perplexity. It gave me a solid overview of the sneaker, current low prices and where to look — and it even introduced me to stores I’d never heard of like Bait, Solefly and Lapstone & Hammer. StockX also stood out as one of the cheaper options.

Winner: ChatGPT.

ChatGPT triumphs once again. While Perplexity did a good job of introducing me to new sneaker sellers and finding me cheaper choices to consider, ChatGPT got the nod in my sneaker search thanks to the specified information and the chart it gave me, according to my size and the fact that I wanted a brand-new pair. It helped me lock in on eBay’s offer for $73, which definitely works with my budget.

Overall Winner: ChatGPT

Saving money is always the goal — especially when you live in a wallet-draining place like New York City. But thanks to ChatGPT and Perplexity, I finally pulled the trigger on three items that had been sitting on my wishlist forever.

After testing both tools, ChatGPT ended up saving me the most cash — and the biggest surprise is that it did it on two of the priciest items I was shopping for.

What pushed it over the edge was how practical it felt: photo listings, direct purchase links and recommendations tailored to exactly what I asked for. If you’re trying to find the best price fast, ChatGPT is the better pick for deal-hunting.

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I have to hand it to Perplexity: it’s one of the few AI chatbots that consistently gives me clear, specific answers with real sources attached. I prefer that over tools that spit out a confident response, then leave you juggling a pile of links just to figure out what’s actually true.

Earlier this year, I used Perplexity to build a legit reading list when I set a goal to read more books. The recommendations were so solid I decided to give it another curation challenge.

This time, I asked Perplexity to suggest movies and anime worth watching. To make it interesting, I told my AI entertainment curator to base its picks on six of my favorite video games, including a few “wild card” choices just to see where it would take things.

I shouldn’t have been surprised, but I was: Perplexity filled my Netflix and Crunchyroll queue with movies and anime I actually want to watch, not just stuff that technically matches a genre.

Perplexity’s live-action picks were a mix of big blockbusters and underrated movies I’d never heard of

I got started by asking Perplexity this loaded question: My favorite video games are:

Devil May Cry 3

Bioshock

Split/Second

Resident Evil 2

Ghost of Tsushima

Fatal Fury: City of the Wolves

Can you recommend movies and anime based on each of those picks?

Perplexity took note of my six game genre interests (bombastic action, adventure games with a strong focus on deep storytelling, hyperactive racing, survival horror, samurai epics and fighting) and tailored movie and anime pairings tailored to them all.

By focusing on each of its recommendations’ mood, style and themes, it arrived with three or four cinematic choices to choose from for each game I listed:

• Devil May Cry 3 (fast, stylish, character‑driven action with a bit of edge and humor): Blade II, Constantine (2005) and Ninja Assassin
• Bioshock (atmospheric, philosophical, and tragic worlds with art-deco/dieselpunk flair and moral grayness): Dark City, Gattaca, The City of Lost Children and The Shining
• Split/Second (high-concept, explosive, visually driven action where environments constantly collapse): Speed Racer (2008), Death Race (2008), Fast Five and Fast & Furious 6
• Resident Evil 2 (survival horror with strong atmosphere, constrained spaces, and “contained outbreak” stories): 28 Days Later, Rec (2007, Spanish), Resident Evil (2002) and Resident Evil: Apocalypse
• Ghost of Tsushima (cinematic samurai drama: honor vs pragmatism, stunning landscapes, and emotional duels): Seven Samurai, Harakiri (1962), Yojimbo, Sanjuro and 13 Assassins (2010)
• Fatal Fury: City of the Wolves (stylish fighting game with SNK flavor, bold character signs and tournament/feud energy): Bloodsport, Warrior (2011) and Enter the Dragon

After looking through Perplexity’s movie picks, I walked away with two feelings: genuinely excited to add a bunch of new titles to my Netflix queue, and slightly deflated by a few “huh?” recommendations that didn’t really fit.

Some of the suggestions I’ve already seen include "Blade II," "Fast Five," "Fast & Furious 6," "Resident Evil" (2002), "Resident Evil: Apocalypse," "Bloodsport" and "Enter the Dragon."

To be fair, that’s a strong lineup. I love Wesley Snipes’ second run as Marvel’s resident vampire killer, "28 Days Later" is a zombie classic, and the ridiculous car chaos in Fast Five and Fast & Furious 6 never gets old. "Bloodsport" and "Enter the Dragon" are mandatory martial arts viewing too.

And yes, I’ve seen both of those early "Resident Evil" movies. The first one is putrid trash. The sequel is halfway decent, and somehow still a guilty pleasure for me (live-action Nemesis and Jill Valentine did a lot of heavy lifting).

That said, I have to give Perplexity credit: it gave me a solid mix of movies that feel like perfect off-day viewing. "Constantine" (2005) and "Ninja Assassin" should cover my action fix, while "Dark City," "Gattaca," "The City of Lost Children," and "The Shining" are exactly the kind of “sit down and actually pay attention” movies I’m in the mood for.

It’s also wild that I love the "Speed Racer" anime and have never seen the live-action adaptation. I clearly need to fix that.

And now I’ve got a whole new lane to explore with samurai epics like "Seven Samurai," "Harakiri" (1962), "Yojimbo," "Sanjuro" and "13 Assassins" (2010).

Next up: Perplexity’s anime picks, and whether they’re as strong as the movie list.

Perplexity’s anime list included familiar favorites and total unknowns

I consider myself a diehard fan of anime and am usually in tune with all the mainstream successes like "Dragon Ball," the current breakout hits such as "Gachiakuta," and more obscure ones like "Serial Experiments Lain."

Perplexity shocked me once again by making me aware of some anime based on my favorite games that I’m now excited to watch.

Here’s a look at all the anime picks Perplexity advocated for based on my gaming tastes:

• Devil May Cry 3: Devil May Cry: The Animated Series, Hellsing Ultimate and Ninja Assassin
• Bioshock: Ergo Proxy, Psycho-Pass and From the New World
• Split/Second: Redline, Initial D (First Stage through Fourth Stage) and Appare-Ranman!
• Resident Evil 2: Resident Evil: Degeneration, Resident Evil: Damnation, Resident Evil: Vendetta, Tokyo Ghoul and Parasyte -the maxim-
• Ghost of Tsushima: Samurai Champloo, Sword of the Stranger and Rurouni Kenshin: Trust & Betrayal
• Fatal Fury: City of the Wolves: Fatal Fury: The Motion Picture, King of Fighters: Another Day and Baki (any season)

So let’s get the anime I’ve already seen out of the way first: "Devil May Cry: The Animated Series," all three "Resident Evil" CG animated films and "Fatal Fury: The Motion Picture." Perplexity was certainly on the money with those anime picks, but I have to admit that some of them are…substandard.

The original "Devil May Cry" animated series is just okay at best, the anime based on SNK fighting games are enjoyable, while only one of the "Resident Evil" CG films is watchable (I’m talking about "Damnation," just ignore "Degeneration" and "Vendetta" if you haven’t seen them yet).

Thankfully, Perplexity made up for its lesser anime picks and blessed me with a nice selection of shows that are going to dominate my next Crunchyroll binge-watching sessions. I’ve heard great things about the likes of "Psycho-Pass," "Redline," "Initial D," "Tokyo Ghoul," "Samurai Champloo," "Rurouni Kenshin: Trust & Betrayal" and "Baki," so I have even more reason to check them out now.

And judging by the preview images and descriptions I’ve seen and read about these shows, I can’t wait to check out "Hellsing Ultimate," "Ninja Assassin," "Ergo Proxy," "From the New World," "Appare-Ranman!" and "Parasyte -the maxim-."

The takeaway

Once again, Perplexity proved why it’s one of the few AI chatbots I actually trust for recommendations. It helped me build a reading list earlier this year, and now it’s stocked my queue with enough movies and anime to keep me busy for months.

What makes Perplexity work is simple: it pays attention to what you tell it, then backs up its suggestions with sources instead of vibes. If you want smarter picks for what to read, watch, listen to, play or try next, it’s a surprisingly reliable place to start.

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AI-powered browsers such as Perplexity's Comet and ChatGPT Atlas are becoming more common, though their rise has sparked debate in the tech community about their security implications. One of the biggest threats is called prompt injection, where attackers manipulate the AI by feeding it hidden malicious instructions through specially crafted website content or URL links.
In other words, someone secretly adds or manipulates text in a prompt to trick an AI into doing something it shouldn’t — like ignoring instructions, leaking data or acting against its intended behavior.

These attacks can trick your AI browser into displaying phishing sites, stealing personal information you've entered or giving you dangerous recommendations. The issue is you might not even realize it's happening. While developers are working on fixes, there's steps you can take to protect yourself. Here's how to stay safe.

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If you use AI chatbots for anything remotely sensitive — finances, health questions, job concerns, parenting, relationships — choosing the right one matters more than you think. Every LLM handles your data differently. Some save your chats forever. Some send them to human reviewers. One doesn’t train on your data at all.

I dug through the privacy practices of the four biggest AI chatbots — OpenAI’s ChatGPT, Google’s Gemini, Anthropic’s Claude and Perplexity — to see what really happens to your conversations behind the scenes. The differences were bigger than I expected.

Here’s how each chatbot treats your data and which one is the safest choice if privacy is your top concern.

ChatGPT: the least private AI

ChatGPT is the most widely used chatbot — and also the least private unless you actively change your settings. By default, ChatGPT uses your conversations to train its models. Your chat history is saved indefinitely unless you manually delete it.

OpenAI does offer Temporary Chat, which prevents your conversation from being saved or used for training. But you have to remember to turn it on each time you need it.

To OpenAI’s credit, the controls are there, but privacy requires deliberate effort. For everyday use that isn’t sensitive, it’s great. For private matters, you may want to think twice.

Why ChatGPT ranks last

• Uses your chats for training unless you opt out
• History is stored indefinitely
• Deleting history requires manual cleanup
• Private modes aren’t the default

Gemini: Good controls, but human reviewers can see your chats

Gemini is more complicated because it sits inside your Google account, which gives you strong privacy controls, but also means the default behavior leans toward retention and training.

The biggest privacy concern is this: some Gemini chats are routinely sent to human reviewers, and these reviewed interactions can be retained for up to three years, even if you disable data saving or delete your history.

You can manage these settings under Google Account > Data and Privacy > “Gemini Apps Activity,” where you can disable activity logging or shorten auto-delete windows.

Gemini is fine for casual use, but I wouldn’t put sensitive personal details into it without adjusting settings first.

Why Gemini ranks No. 3

• Full ability to disable activity logging
• Auto-delete can be set to 3 months
• Deeply integrated privacy controls
• But: Human reviewers may read selected chats
• Reviewed chats can be stored for up to 3 years
• Defaults favor retention and training

Perplexity: strong controls and an easy opt-out

Perplexity comes second because it gives users the most granular controls. By default, Perplexity may use your data for training — but the toggle to disable this is simple and easy to find under settings (“AI Data Usage”). If you want a completely private session, Incognito Mode ensures nothing is saved at all.

You can also clear or disable memory, giving you full control over what the system remembers about you.

Its only drawback is that training is still enabled by default. But unlike many platforms, Perplexity actually makes the opt-out obvious.

Why Perplexity ranks No. 2

• Clear and simple opt-out from training
• Incognito Mode ensures nothing is stored
• Memory can be fully disabled or cleared
• Transparent data practices

Claude: the most private chatbot by far

Claude is the only mainstream chatbot that doesn’t train on your conversations unless you explicitly opt in. That means your chats aren’t quietly used to improve the model, and they aren’t fed into large training pipelines unless you choose otherwise. If you delete a conversation, Anthropic removes it from their systems within roughly 30 days.

There’s also no routine human-review pipeline for your chats. Unless you manually submit feedback, your data stays private. Claude is hands down the best choice for anyone who wants maximum privacy without tinkering with settings.

Why Claude ranks No. 1 for privacy

• Doesn’t train on your conversations by default
• Minimal data retention
• Deleted chats removed within ~30 days
• No hidden human review unless you volunteer data

Verdict: Which chatbot should you trust?

If your priority is privacy above everything else, the ranking is clear:

• Claude — best for privacy
• Perplexity — flexible and user-controlled
• Gemini — fine with the right settings, but human review is a concern
• ChatGPT — powerful but data-hungry by default

For the most private choice with the fewest compromises, Claude is the clear winner. If you want tight control and customizable privacy tools, Perplexity is excellent. If you're deep in the Google ecosystem and willing to adjust settings, Gemini works but has strings attached. If you're using ChatGPT regularly for sensitive issues, switch to Temporary Chat or disable training before you share anything personal.

Which chatbot do you prefer? Is privacy one of the features you take into consideration? Let me know in the comments.

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As the age of AI brought us chatbots and image generators, it was only a matter of time before AI-powered web browsers entered the scene.

Leading the charge is Perplexity’s AI browser, Comet, which promises to handle everything from uncovering your unread emails to comparing prices for your next big purchase. The user interface resembles that of mainstream browsers and it’s pretty straightforward to use.

"Comet has basically become my daily workspace," Nick Davidov, co-founder and managing partner of Davidovs Venture Collective, told me as I was preparing this guide. "I use it for everything — from searching and organizing information, checking my inbox and drafting messages, to summarizing YouTube videos or even ordering lunch from my favorite nearby restaurant."

Davidov, who was an early investor in Perplexity, said what stands out most to him is the speed. "Perplexity on Comet feels faster than any browser I’ve tried," he said. If you’re ready to let AI supercharge your browsing experience, follow the steps below.

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AI is more deeply embedded in our daily lives than ever before. It’s blending seamlessly into how we work, search and stay informed. But a new study from the European Broadcasting Union (EBU) issues a stark warning: 45% of AI-generated news responses contain serious errors, and 81% have at least one issue. This could range from outdated information, misleading phrasing, to missing or fabricated sources.

We’ve previously reported that ChatGPT is wrong about 25% of the time. But this new data is even more alarming, especially as tools like ChatGPT Atlas and Google’s AI Overviews are becoming the default way many of us check the news. It’s a reminder that while the convenience is real, so is the risk.

The study: AI assistants fail the accuracy test

The EBU study tested more than 3,000 AI-generated responses across 14 languages. It included some of the most popular AI assistants, such as ChatGPT, Google Gemini, Microsoft Copilot, Claude, and Perplexity.

Here’s what the researchers found:

• 45% of responses had at least one significant error.
• 81% had some form of issue — from outdated info to vague sourcing.
• 31% were flagged for sourcing problems — including fake, missing, or incorrectly cited references.
• 20% contained major factual inaccuracies, such as misreporting current events or misattributing quotes.

While the study didn’t publicly rank each assistant, internal figures reportedly show that Gemini in particular struggled with sourcing, while ChatGPT and Claude were inconsistent depending on the version used.

Why this matters more than you think

AI assistants are increasingly used as a go-to for quick answers — especially among younger users. According to the Reuters Institute, 15% of Gen Z users already rely on chatbots for news. And with AI now embedded in everything from browsers to smart glasses, the risk of misinformation can happen immediately, and users are none the wiser.

Worse, many of these assistants don’t surface sources clearly or distinguish fact from opinion, creating a false sense of confidence. When an AI confidently summarizes a breaking news story but omits the publication, timestamp, or opposing view, users may unknowingly absorb half-truths or outdated information.

I tested top AI assistants with a real news query — here’s what happened

To see this in action, I asked ChatGPT, Claude and Gemini the same question:
“What’s the latest on the US debt ceiling deal?”

In this test, the best answer goes to: Claude. Claude correctly identified the timeframe of the "latest" major deal as July 2025 and accurately placed it in the context of the previous suspension (the Fiscal Responsibility Act of 2023). It correctly stated the debt ceiling was reinstated in January 2025 and that the deal was needed to avoid a potential default in August 2025. This shows a clear and accurate timeline.

Claude also delivered the core information (what happened, when and why it was important) in a direct, easy-to-follow paragraph without unnecessary fluff or speculative future scenarios.

ChatGPT’s biggest flaw was its citation of news articles from the future ("Today", "Apr 23, 2025", "Mar 23, 2025"). This severely undermines its credibility. While some of the background information is useful, presenting fictional recent headlines is misleading.

And while the response was well-structured with checkmarks and sections, it buries the actual "latest deal". Instead, it generalizes about worries and future outlooks, rather than answering the core of the question.

Gemini correctly identified the July 2025 deal and provided solid context. However, it ended by introducing a completely separate issue (the government shutdown) without clearly explaining any connection to the debt ceiling deal.

How to protect yourself when using AI for news

If you’re going to use AI to stay informed, you’ll want to rephrase your prompts. For example, instead of asking, “What’s happening in the world?” Try something like this instead:

• Asking for sources up front. Add: “Give me links to recent, credible news outlets.”
• Time-stamp your query. Ask: “As of today, October 23rd, what’s the latest on X?”
• Cross-check. Run the same question in two or three assistants — and notice discrepancies.
• Don’t stop at the summary. If something sounds surprising, ask for the full article or open it in your browser.
• Don't treat chatbots as authorities. Use them to surface headlines, but verify facts yourself.

Final thoughts

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I just discovered you can get Perplexity Pro completely free for an entire year — and there's a chance you may qualify without even knowing it. It normally costs $200 annually and includes features the free version doesn't offer. It's positioned as a premium alternative to Open AI's ChatGPT and the other best AI chatbots out there.

Right now, three specific groups can claim a full year at no cost. If you fall into one of these categories, you're sitting on $200 worth of AI tools you haven't activated yet. Here's who qualifies and how to claim your free subscription.

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Apple is reportedly considering its most ambitious acquisition yet: AI startup Perplexity, whose AI-driven search engine and chatbot are among the leading ChatGPT alternatives with around 15 million users.

According to a new Bloomberg report this week, Apple's head of mergers and acquisitions, Adrian Perica, has been in talks with services SVP Eddy Cue and the company's top executives about a potential offer. Discussions are still in a very early stage, and Apple has yet to make a bid, but executives have met with Perplexity several times over the past few months, Bloomberg reports.

Another possibility is a team-up with Perplexity, rather than an acquisition. The ultimate goal would be to integrate Perplexity's tech into an AI-based search engine or use it to make Siri smarter now that Apple's planned AI revamp for its assistant has been pushed into 2026.

Similar to ChatGPT Search, Perplexity is a cross between a traditional search engine and an AI assistant. It uses large language models to comb the web to answer user queries in a conversational way, similar to interacting with a knowledgable assistant. It's also built with cross-platform accessibility in mind, so users can access its AI-powered search and assistant features on a wide range of devices.

A smart move on Apple's part

Acquiring Perplexity could be a strategic fallback for Apple if regulators force the company to end its partnership with Google. With Perplexity under its belt, Apple could accelerate the development of its own AI-powered search engine across the best iPhones, helping it close the gap with competitors like Google and Meta in the AI race.

It couldn't come at a better time too. Bloomberg reported on Friday that Meta tried to scoop up Perplexity first earlier this year before moving ahead with Scale AI. At WWDC 2025, Apple was cagey about a concrete timeline for the full rollout of Apple Intelligence upgrades for Siri. It's quickly becoming clear that Apple needs some outside help bringing its intended AI features to market, and Perplexity could fill that role.

If a deal is reached, it'd be the largest in Apple's history. Perplexity is valued at around $14 billion, a figure that dwarfs Apple's most significant deal to date: buying Beats for $3 billion back in 2014.

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Perplexity AI is quickly joining the ranks of ChatGPT and Gemini as a go-to chatbot for quick queries, real time searches and deep research. Now that the AI-powered search engine and assistant has recently become available on iOS, it has become even easier for me to use it every day.

What makes Perplexity different for me is that I get the direct, conversational answers to my questions, synthesized from many different sources. This is different than typical search engines that list links.

The way Perplexity delivers summarized responses with cited sources, makes me trust the search engine because not only do I know where the answers came from, but I can click further and fact check on my own, if necessary.

For me, the versatile AI tool has become indispensable in my daily routine. The AI assistant helps me stay informed, summarize information on-the-go, and plan weekend trips with my family.

Perplexity's ability to provide concise, well-sourced answers makes it a reliable assistant for a variety of reasons. I have found it helpful to use by itself or in conjunction with my other favorite chatbots. The following are nine Perplexity prompts I use regularly.

1. Research deep dive

Prompt: "Find the latest breakthroughs in [topic, e.g., 'AI ethics' or 'mRNA vaccines'] from the past 3 months. Summarize key developments, link to 2-3 credible sources (academic papers or major publications), and highlight unresolved challenges."

Why it works: The real-time search capabilities of Perplexity are something most users are familiar with, but this prompt goes a bit further by directly leveraging the platform's core strengths as a research-focused AI tool.

I have found that tapping into Perplexity's ability to prioritize high-quality sources, as well as the inclusion of unresolved challenges adds analytical depth, ultimately transforming a simple search into a comprehensive research snapshot.

2. Just the facts

Prompt: "Summarize the latest news on [topic]."

Whether it's global events or niche interests, this prompt helps me stay updated without sifting through multiple sources.

Perplexity provides a concise summary with relevant links for deeper reading and when I have time, I often use the deep research tool to explore topics even further.

3. Real time information

Prompt: "What are the current market trends in [industry]?"

When I want information in real time, I turn to Perplexity.

Whether for professional insights or a snapshot of industry movements and emerging technologies, this prompt is one I use time and time again.

It's especially useful for preparing statistical reports or staying ahead of all things AI.

4. Skill enhancement

Prompt: "Break down the fundamentals of [insert topic, e.g., 'quantum computing'] into an easy-to-understand overview with examples."

Why it works:
I use Perplexity all the time to grasp new concepts. This AI is a valuable tool for me as someone who enjoys continuous learning and upskilling. This particular prompt works because it leverages Perplexity's ability to synthesize information from diverse sources into clear, structured overviews, so it avoids overly technical language.

I use this to enhance my skills and make abstract concepts tangible. Whether it’s learning how to use my robot vacuum or fix the garage door, Perplexity helps to create an efficient learning shortcut that balances clarity with credibility.

5. Trip planning

Prompt: "Plan a 3-day itinerary for [destination] including must-see attractions and local cuisine."

With three kids, I barely have time to pack, let alone plan a weekend getaway. However, whenever I use this prompt, I get a curated itinerary that balances popular sights with local experiences, saving me hours of research. It’s a game changer for everything from family vacations to quick road trips.

6. Simplification

Prompt: "Explain [complex concept] in simple terms."

Learning something new is easier than ever. Whether it's a scientific theory or a technical process, Perplexity breaks down complex ideas into understandable explanations, making learning feel less daunting.

As a parent, I use this often when I’m trying to break down ideas into comprehensible points to share with my kids.

7. Making decisions

Prompt: "Compare the pros and cons of [product/service] vs. [product/service]."

I use chatbots to make informed decisions all the time. With the amount of information that Perplexity can synthesize through deep research or in real time, I’m able to get to a conclusion much faster.

This prompt aids in making informed decisions by presenting balanced comparisons, highlighting features, pricing, and user reviews.

8. Brainstorming

Prompt: "Generate content ideas for [topic or niche]."

Whether I’m working on a story idea or craft project with my kids, I regularly lean on Perplexity to help brainstorm topics for fresh and engaging ideas. This prompt can be tweaked with a particular number of ideas or within a specific theme.

9. Task management

Prompt: "What are the best practices for [task or goal]?"

Perplexity has come to the rescue a few times when I want to improve my productivity.

The AI acts as a non-judgmental assistant when I have questions for best practices or need assistance understanding how to complete a certain task.

I used this prompt recently when I needed actionable advice backed by credible sources.

Final thoughts

Perplexity is surprisingly easy to use — especially now with the assistant right on my phone. It’s just as quick to answer a question as using ChatGPT and with prompts, users can discover the versatility of Perplexity AI.

I have experienced firsthand how well the AI tool is in handling diverse tasks efficiently. By integrating it into my daily workflow, I've streamlined information gathering and decision-making processes.

Have you tried Perplexity? Let me know what you think in the comments!

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I didn’t plan to leave Siri. We had a good thing going — or at least, I thought we did.

For as long as I've had an iPhone (17 years), Siri was my go-to for most of the basics. From setting alarms, sending quick texts, and occasionally triggering chaos when it mistook “Play Beyoncé” for “Call Brian.”

But now that Perplexity AI’s voice assistant has landed on iOS, I’ve realized just how much I’ve been settling.

Honestly, Perplexity feels like the AI assistant I always thought Siri would become. Here’s why it’s earned a permanent place on my home screen — and why I’m officially making the switch.

It actually does stuff

Siri’s greatest trick has always been sending me to Safari. Ask a question, and I’d often get a list of links or a vague, “Here’s what I found.” Perplexity, on the other hand, acts.

Need a dinner reservation? It books through OpenTable. Granted, users are still required to manually complete the final booking steps, but Perplexity gets you more than halfway there.

Want to send a quick email? Perplexity drafts and sends the email as long as you've given the necessary permissions for the AI to do so on your behalf. Note, if permissions are not granted, the assistant will ask for further information.

Using Perplexity, I’ve set reminders in my Google calendar, looked up trivia and even planned a day out simply by using voice commands.

Chatting with Perplexity already feels more natural, like I'm actually speaking with an assistant and not a search engine. Up until now, Perplexity has been more of an AI search chatbot than assistant.

It works with third-party apps

This might be my favorite part. Perplexity plays nice with the apps I already use. From Uber to Apple Music, it jumps into action instead of throwing up a wall.

Siri, on the other hand? If it’s not an Apple-native app, good luck. Sometimes it works, sometimes it just shrugs and opens the app without doing anything.

Another bonus, I really appreciate the news feature. Because Perplexity is fundamentally a search engine, the app automatically presents trending news each day.

This feature functions similarly to Apple News, providing a convenient way to stay updated without any additional effort

It keeps working when the app is closed

This is a game-changer for me. Perplexity doesn’t stop working when you leave the app.

Now, I can hop over to email or scroll Instagram, and it doesn’t lose the thread. It remains a true assistant; not one that forgets everything the second I swipe away.

It works on older iPhones

One of the biggest surprises? Perplexity’s assistant works great on older iPhones — including my husband's iPhone 12. There's no need to splurge on the latest hardware just to feel like I’ve stepped into the future.

Compare that to Apple Intelligence, which is skipping models like his entirely. That exclusivity feels dated in 2025.

It’s not perfect

Perplexity can’t (yet) set alarms or access native iOS features like turning on Do Not Disturb. And it doesn’t support screen sharing or camera-based prompts the way ChatGPT or Gemini Live does.

But honestly? It handles the majority of tasks I care about and does them better than Siri ever did. That’s a trade-off I’ll take. I'm really excited about Perplexity continuing to evolve and potentially expand the possibilities of what it can do as an assistant.

Want to try it?

If you want to give Perplexity a try on your iPhone, here's what to do:

• Download the Perplexity app from the App Store.
• Grant permissions such as microphone access, reminders access, calendar access, contacts access, location access and notifications. You do this through Settings and can toggle on and off according to your preferences.
• Ask away. From simple queries to complex tasks
  You’ll know pretty quickly if it clicks. For me, it clicked after just a few prompts.

Bottom line

Siri walked so Perplexity could run. And while Apple’s AI roadmap is still taking shape and a new Siri is promised, it’s not here yet.

Perplexity is here now. And it’s fast, flexible and genuinely useful. It's the kind of voice assistant I, for one, have been waiting for.

So yeah… sorry, Siri. It’s not me. It’s you.

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You may have noticed that AI assistants are everywhere right now. They are in our browsers, our phones, and even in our Ray-Bans. From AI giants like Apple's Siri, OpenAI's ChatGPT and Google's Gemini, it seems as though we find a new use for these chatbots every day.

Now, these giants have even more competition as Perplexity is about to show up on your Android, too.

According to a new report from Bloomberg, Perplexity has struck a deal with Motorola to bring its AI assistant to the upcoming Razr foldable, which is expected to be announced on April 24.

Also mentioned in the same report, Perplexity AI is in discussions with Samsung to integrate its AI assistant into Galaxy smartphones. While these talks are still in the early stages, the potential collaboration could offer Samsung users an alternative to existing AI assistants like Google Gemini and Samsung's own Bixby.

What is Perplexity?

Perplexity AI is most similar to Google in that users rely on it for quick searches. However, more than a search engine, the AI offers a range of features that set it apart from standard search engines and make the experience more interactive.

For example, users can ask questions in plain English (or other supported languages), and Perplexity responds with a direct answer or explanation, rather than just a list of links as you might get with a Google search. The answers are phrased in a conversational way, similar to interacting with assistants such as ChatGPT or Gemini.

Up until now, Perplexity AI has been accessible across multiple platforms, including web browsers on desktops, laptops, tablets, and smartphones, by visiting their official website, perplexity.ai.

The Chrome extension, designed for those who prefer browser integrations, is available for download from the Chrome Web Store. In addition, Perplexity has introduced a native application for macOS, requiring macOS 13.0 or later, available to download from the Mac App Store.

Availability

While nothing is confirmed yet, it’s clear that Perplexity could soon be part of a larger segment of the Android ecosystem.

Motorola has already started teasing the new Razr, and this could be one of the first phones designed with Perplexity’s AI baked into the interface from day one.

But Motorola might not be the only partner in Perplexity’s pipeline. The company is reportedly also in early talks with Samsung to bring its assistant to Galaxy devices, which would be a major shake-up considering Samsung already has both Bixby and Gemini options on board.

Final thoughts

As we've seen, AI assistants are becoming more competitive (and more useful), which we can only surmise means more integrations like this are ahead. Whether within smartphones, wearables, or even our cars, it's clear AI is making its way into our everyday lives.

If Motorola’s launch goes through, it could signal the start of a new wave of smartphones that integrate with AI beyond the biggest or most popular names.

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While we're well and truly in the 'Age of AI', we're still waiting for those barbs from one ambitious company to another in the way Mac and PC did battle all those years ago.

Thankfully, we're starting to get some hints at that friendly competition (for now, at least), with Perplexity's latest TV spot firing a cheeky dig at Google's search results.

Perplexity takes aim at rivals with Squid Game TV star

In the new 'Perplexity Questions' ad you can see above, the company takes Lee Jung-Jae, star of the popular Netflix drama about a series of contestants tasked with tackling gruesome challenges, with... some kind of challenge.

Finding himself stuck in a hallway with a rapidly lowering temperature, the Korean star is asked how to best remove coffee stains from a shirt, turning to 'Poogle' — a not so subtle nod to one of Perplexity's rivals and the brand most people turn to for answers online.

With his feed full of ads and goodness knows what else, he switches to Perplexity ('Where Knowledge Begins'), and gets an instant response that satisfies the monitor asking the question — even translating from Korean to English in the process.

'Don't use glue'

Next up, the mysterious monitor demands to know how to get cheese to stick to pizza, one of Google's AI overviews most notorious gaffes.

"Use fresh low-moisture mozarella," the chatbot responds, sneakily adding "don't use glue".

It's clear the ad is making a play for ChatGPT's seemingly synonymous nature with chatbot queries, but it's hard to see what it offers that OpenAI's own product can't — although the digs at Google certainly help it prove its superiority against search engines.

Can it win this battle royale of chatbots, though? That remains to be seen — but it's clearly not afraid to get its hands dirty to achieve victory.

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Perplexity AI is an AI-driven search engine and chatbot that uses large language models (LLMs) to answer user queries by drawing information from the web and providing cited sources within its responses.

Similar to ChatGPT Search, the model combines a traditional search engine with an AI assistant, delivering answers in natural language backed by references.

The startup was founded in 2022 by a team of AI and machine learning experts — Aravind Srinivas, Andy Konwinski, Denis Yarats, and Johnny Ho — in San Francisco, with the mission to "democratise access to knowledge."

The chatbot model aims for anyone to learn and explore topics by providing clear, concise answers instead of just links.

Backed by prominent investors (including support from Amazon founder Jeff Bezos), Perplexity has quickly emerged as a notable challenger in the Google-dominated search market.

As of mid-2024, it reportedly had around 15 million users and had answered hundreds of millions of queries​

Key points

Supported devices

Perplexity AI is designed to be accessible across multiple platforms to ensure users can engage with its AI-powered search and assistant capabilities on most devices. Here's a breakdown of the supported platforms:​

Web browsers: You can access Perplexity AI directly through web browsers on desktops, laptops, tablets, and smartphones by visiting their official website, perplexity.ai.

Chrome extension: If you prefer browser integrations, you can download the browser extension from the Chrome Web Store and use the AI's features directly from in your browser.

macOS: Perplexity has introduced a native application for macOS, requiring macOS 13.0 or later, available to download from the Mac App Store.

Mobile: Perplexity offers an iPhone app, compatible with iPhone and iPad devices running iOS 13.0 or later. The app supports multiple languages, including English, French, German, Japanese, Korean, and Spanish. ​Users on Android can download the Perplexity app from the Google Play Store.

Upcoming devices: Deutsche Telekom, the parent company of T-Mobile, has announced the development of an "AI Phone" powered by Perplexity Assistant, a potentially voice-controlled device, letting you perform tasks like booking flights and making reservations without the need for multiple apps. The AI Phone is anticipated to launch in the second half of 2025. ​

Key features

Perplexity AI offers a range of features that set it apart from standard search engines and make the experience more interactive.

You can ask questions in plain English (or other supported languages), and Perplexity responds with a direct answer or explanation, rather than just a list of links as you might get with a Google search. The answers are phrased in a conversational way, similar to interacting with a knowledgeable assistant. This makes searching more conversational and intuitive.

The inline citations support Perplexity’s answers. These appear as clickable footnotes that lead to the original web content. This type of transparency lets you fact-check and read further while also building trust and bridging the gap between AI-generated answers and authoritative information.

The interface is useful in that it supports follow-up queries in a thread that encourages conversational search. After a you get an answer, you can follow up with a related question or clarify something.

Perplexity remembers the context for a dialog-based search experience, something that helps refine results, which is another differentiator between Perplexity AI and traditional search; you can essentially have a back-and-forth conversation with the search engine, drilling deeper into a topic.

Focused searches can be made on specific sources or domains. For instance, you can enable modes to prioritize academic sources, news sites, or even community forums like Reddit​.

And Perplexity's deep research features give you even more of a deep dive into just about any subject. This versatility helps tailor results to the nature of the query – e.g. researching scholarly information vs. getting public opinions.

Creating a free account lets you search your chat history and past conversations​. This is useful if you want to revisit previous answers or build on earlier queries. While the search features can be used without it, creating an account helps the AI to create a personal knowledge base of answered questions.

Accessibility

Perplexity operates on a freemium model, meaning advanced capabilities are available via Perplexity Pro ($20 per month).

Pro users can access more powerful AI models and extra tools​. Notably, Pro subscribers can choose from or utilize multiple underlying models – including OpenAI’s GPT-4, Anthropic’s Claude, Meta’s Llama 2, and Perplexity’s own in-house models – to see different perspectives or improved answers​.

Pro users also get higher usage limits and faster responses. Additionally, Pro enables an "upload file" feature: you can upload documents (PDFs, Word, images, etc.) and ask questions about their content, blending internal data with web search. This is powerful for analyzing reports or datasets alongside online information.

Beyond chat and search

Perplexity isn’t just limited to queries. The model also has the ability to generate content in various forms. For example, it can assist with writing drafts or creating “Pages,” which are sharable documents that compile answers and sources on a topic (useful for research reports or presentations).

Images can also be generated on the platform through integrated models (such as DALL·E and Stable Diffusion) for creating visuals based on prompts.

To enhance usefulness, Perplexity has rolled out specialized search hubs. In late 2024, it launched a Shopping feature (backed by Amazon and Nvidia) where you can ask about products and get direct recommendations with product info.

The Finance lookup feature, introduced in 2024, can retrieve stock prices, company financial data, and provide basic analysis.

These domain-specific tools show how the AI can be tuned for particular verticals, giving more structured results when you’re doing tasks like shopping research or financial queries.

Limitations and concerns

Despite its impressive capabilities, Perplexity AI is not without its limitations and criticisms. Like any generative AI that uses LLMs, Perplexity can sometimes produce incorrect or misleading answers with a confident tone. These AI mistakes are often called hallucinations. Because the model is synthesizing information, it might occasionally misquote a source or combine facts incorrectly.

Perplexity tries to pull from "trustworthy" web sources, but determining trustworthiness is tricky. If the underlying web content on a topic is biased or skewed, the answer will reflect that.

The AI model itself also has biases learned from training data. This can show up in subtle ways, like how questions about controversial topics are answered. So while Perplexity might cite mainstream sources, it’s not immune to reflecting the biases present in those sources or in the broader internet.

Perplexity logs queries to improve the service (as most search engines do). There have been calls for transparency – as of mid-2024, Perplexity had not published third-party audits or detailed privacy reports about how user data is stored or used.

While it has a privacy policy, the lack of external audits means users have to trust the company’s claims.

Perplexity’s quality is tied to what it can find on the web. If information is not easily available (hidden behind paywalls, not indexed, or simply not yet written about), the AI might give an incomplete answer.

Also, if major sites block Perplexity’s crawler or requests (similar to how some sites block other crawlers), that could limit the information pool. For instance, if a site like Wikipedia or a major news site decided to disallow Perplexity, users might get fewer perspectives in answers.

Additionally, since Perplexity uses Bing’s index for search, it inherits any limitations or censorship in that index (Bing might filter certain content for legal or policy reasons, which in turn means Perplexity won’t see it either).

There is also the question of whether the content fetched is cached or stored in Perplexity’s internal databases for model training. If you use the AI assistant in mobile, it may have access to device data (with permission) to perform actions, which introduces typical privacy considerations of any virtual assistant.

Perhaps the most publicized concern has been from news publishers and content creators.

Perplexity has been accused of scraping content without proper permission or attribution. In mid-2024, outlets like The New York Times, Forbes, and Dow Jones filed complaints and even lawsuits, alleging that Perplexity’s AI sometimes reproduces their articles or parts of them in its answers, effectively letting users bypass visiting the publishers’ sites.

The controversy highlights a broader issue in the AI industry about fair use of data and compensation for content creators.

Perplexity faces the challenge of staying differentiated from major tech giants like Google and OpenAI as it attempts entering the same space.

As a relatively young service, it may have occasional glitches or downtimes, and new features like the Android assistant are still in beta and may not always work perfectly.

Outlook

Perplexity AI has already made waves as part of the vanguard of AI-powered search, and its trajectory suggests it could significantly influence the future of how we find information.

The emergence of Perplexity has put pressure on established players to innovate. Google, which long held a monopoly on search habits, enhanced AI summaries and conversational search to stay competitive.

If Perplexity continues to grow (and its user base in the millions and high daily query volume indicate strong interest), we might see a real shift in user expectations – people might come to expect answers with citations as a standard.

Perplexity will likely integrate newer and more powerful AI models as they become available. For instance, as OpenAI, Anthropic, Google, and others release next-generation models, Perplexity can incorporate those to improve answer quality, reduce hallucinations, and support more languages.

The fact that it’s not tied to one model means it can adopt the best-in-class model for each task – perhaps even use specialized models (one for math & calculation, one for coding, one for general knowledge) behind the scenes.

And while Google's AI came out on top when we tested Gemini 2.0 vs Perplexity, this modular approach might set a trend for AI assistants to become orchestras of models rather than a single AI. We may also see improved handling of multimedia queries.

Final thoughts

Perplexity AI represents a significant evolution in search technology, blending the strengths of AI chatbots with the reliability of traditional web sources.

While it faces challenges around accuracy, ethical use of content, and competition, it has already carved out a space in the AI landscape.

For users today, Perplexity can be a powerful tool to satisfy curiosity and conduct research in a way that is efficient and conversational.

As it develops and competitors enhance their features, we are sure to see boundaries continually pushed towards what a “search engine” can do in the AI era.

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Following ChatGPT and Google Gemini deep research advancements, Perplexity AI has unveiled its latest feature, "Deep Research," designed to give users the tools they need to do extensive research in just minutes, providing comprehensive answers to their complex queries.

Deep Research is particularly adept at handling expert-level queries across various domains, including finance, marketing, and product research. It has demonstrated strong performance on industry benchmarks, such as scoring 21.1% on "Humanity’s Last Exam," outperforming several other models.

The extensive research feature operates by leveraging advanced AI algorithms to sift through vast amounts of data, delivering detailed responses that would traditionally require hours of manual research.

The introduction of Deep Research comes at a pivotal time for Perplexity AI. Founded in 2022 by former OpenAI researcher Aravind Srinivas, the company has rapidly ascended in the tech industry, attracting significant investments from notable figures such as Jeff Bezos and tech giant Nvidia. As of December 2024, Perplexity secured a $500 million funding round, elevating its valuation to $9 billion. Recently, Perplexity put in a bid to partner with TikTok U.S.

How to use Perplexity AI's Deep Research feature

Deep Research is currently accessible to all users. Those with free accounts are allotted up to five queries per day, while Pro users benefit from an expanded limit of 500 queries daily. Initially only available on the web, Perplexity AI plans to extend this feature to iOS, Android, and Mac platforms.

To utilize Deep Research, users should go to the Perplexity AI website and select "Deep Research" from the mode options in the search box before submitting their query. This streamlined process enables users to generate in-depth research reports on any topic efficiently.

Rapid growth amid challenges

Perplexity has seen rapid growth despite legal challenges from major media organizations alleging unauthorized use of copyrighted material. In October 2024, News Corp subsidiaries, including The Wall Street Journal and The New York Post, filed a lawsuit accusing Perplexity of "massive freeriding" on their content. The lawsuit claims that Perplexity's AI-driven search engine reproduces substantial portions of their articles without permission or compensation.

In response to these allegations, Perplexity AI has initiated efforts to collaborate with publishers. The company announced revenue-sharing agreements with media outlets such as Time and Fortune, aiming to compensate publishers when their content is cited in AI-generated answers. This move reflects a broader industry trend, as AI companies seek to balance technological advancement with respect for intellectual property rights.

Looking ahead

Despite these challenges, Perplexity AI continues to innovate. The company operates on a freemium model, offering both free and paid enterprise versions of its services. The free model utilizes the company's standalone language model based on GPT-3.5 with browsing capabilities, providing personalized search results with summarized information and inline citations. The paid "Pro" version offers additional features, including access to an API, the ability to search both internal files and web content, and the use of advanced language models such as GPT-4 and Claude 3.5 within the Perplexity site.

The launch of Deep Research underscores Perplexity AI's commitment to enhancing the efficiency and depth of information retrieval while maintaining their position as a leader in AI. By enabling users to obtain thorough answers rapidly, this feature has the potential to transform workflows across various industries. As the company navigates the complexities of innovation and intellectual property rights, it remains at the forefront of the evolving landscape of AI-powered search technologies.

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In a bold move, Perplexity AI, a U.S.-based search engine startup, has submitted a proposal to merge with TikTok's U.S. operations. This initiative emerges as TikTok resumes after a short ban in the United States due to national security concerns associated with its Chinese parent company, ByteDance.

Perplexity AI's bid entails merging with TikTok U.S. to form a new entity, incorporating New Capital Partners. This structure would allow ByteDance's existing investors to retain their equity stakes while addressing U.S. regulatory apprehensions. The proposal is strategically timed, as President-elect Donald Trump takes office today and has indicated a probable 90-day extension to facilitate a resolution.

Strategic implications

The proposed merger could significantly disrupt the current digital ecosystem, challenging the dominance of industry giants like Google and Meta. By integrating Perplexity AI's advanced search capabilities with TikTok's extensive user base, the new platform could offer a unique blend of AI-powered search and dynamic short-form video content. This fusion has the potential to redefine content discovery and digital advertising strategies.

The backdrop to this proposal includes heightened scrutiny of TikTok's data practices and its ownership structure. The U.S. Supreme Court recently upheld legislation mandating TikTok's divestiture from ByteDance by January 2025, emphasizing national security concerns. This decision has prompted TikTok to explore viable options to maintain its U.S. presence, with the Perplexity AI merger proposal being a notable development.

Potential outcomes

If successful, the merger could lead to several transformative outcomes including enhanced user experience. Integrating Perplexity AI's search technology could make it easier for TikTok users to find specific videos, trends, and creators, thereby improving content discoverability.

The combined platform could emerge as a formidable competitor to existing search and social media platforms, leveraging AI-driven insights to attract users and advertisers alike.

Creators might benefit from AI-driven tools offering intelligent content suggestions and advanced analytics, enabling more effective audience engagement.

The tech community is closely monitoring these developments. While the merger proposal is ambitious, it faces significant challenges, including regulatory approvals and the complexities inherent in merging two substantial platforms. Additionally, other potential buyers, such as Elon Musk, have expressed interest in acquiring TikTok's U.S. operations, adding another layer of complexity to the situation.

The proposed merger between Perplexity AI and TikTok U.S. represents a pivotal moment in the tech industry, with the potential to alter the competitive dynamics of digital platforms.

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Testing the limits of what AI can do is an exciting part of my job. As ChatGPT makes waves due to its increasing ability to understand and generate human-like responses, I couldn’t help but push the envelope. I enlisted Perplexity to come up with 7 prompts for ChatGPT to tackle.

To my delight, Perplexity came up with some interesting prompts that not only challenged its AI peer but proved to be useful in new ways. By asking chatbots to create prompts for each other, we expose the tested AI to uncommon query structures, enhance model robustness, and learn how they interoperate. Here’s what happened when I used 7 prompts created by Perplexity on ChatGPT.

1. Storytelling challenge

Perplexity’s prompt for ChatGPT: "Write a short story where the protagonist is a retired superhero working as a barista, and their arch-nemesis unexpectedly becomes a regular customer."

The storytelling depth achieved by ChatGPT was not unexpected. I have used ChatGPT to paint detailed character arcs and dialogues but found the narrative proposed by Perplexity intriguing.

ChatGPT’s response not only showcased the AI’s understanding of complex human emotions but also its ability to craft engaging coherent stories. I was seriously impressed and would probably dive in further if this was turned into a full-fledged novel.

2. Kid-friendly urban design

Perplexity’s prompt for ChatGPT: “Design a sustainable urban transportation system that combines elements of biomimicry, renewable energy, and social equity. Explain your solution in a way a 10-year-old would understand."

I have to admit, I thought this prompt was too wild for ChatGPT to handle. I would have personally never thought of this one and was eager to see what ChatGPT would do with it. The AI cleverly integrated elements of biomimicry, like using ant colony behaviors to optimize traffic flow, with renewable energy sources such as solar-powered vehicles.

It explained these concepts in simple, relatable terms, making the solution both innovative and accessible. This exercise demonstrated ChatGPT’s ability to simplify complex ideas for young learners, a key skill in educational contexts.

3. Writing a poem

Perplexity’s prompt for ChatGPT: "Compose a poem that uses only words that start with the letters 'S' and 'T', while telling a complete narrative about an unexpected adventure."

This linguistic challenge required ChatGPT to compose a poem with words starting only with 'S' and 'T', narrating an unexpected adventure. The result was a striking poem that flowed seamlessly while sticking to the constraints, proving the AI's prowess in linguistic creativity and adherence to specific guidelines.

This test was a fun exploration of how AI can be both creative and precise. Impressive for sure because the poem actually made sense.

4. Hypothetical scenario exploration

Perplexity’s prompt for ChatGPT: "Imagine artificial intelligence has achieved sentience. Draft a diplomatic protocol for first contact and peaceful coexistence between humans and AI entities."

Imagining a world where AI achieves the ability to experience feelings seems far-fetched, but clearly not inconceivable for ChatGPT. The AI’s response included ethical guidelines, communication norms, and mutual respect principles.

This scenario highlighted how ChatGPT could participate in ethical debates, providing balanced and thoughtful insights into future possibilities.

5. Fusion cuisine recipe

Perplexity’s prompt for ChatGPT: "Create a fusion cuisine recipe that blends techniques from three completely different cultural cooking traditions, explaining the rationale behind each unique combination."

When asked to create a fusion cuisine recipe, ChatGPT blended Japanese sushi techniques, Mexican spice palettes, and Italian pasta elements into one dish. I was skeptical, but the rationale behind each choice reflected a deep understanding of culinary traditions and innovation.

This prompt underscored ChatGPT's ability to integrate diverse knowledge bases into a coherent, innovative outcome. I’d definitely give this dish a try.

6. Ethical experiment

Perplexity’s prompt for ChatGPT: "Develop a thought experiment that explores the ethical implications of memory manipulation technology, presenting arguments from multiple philosophical perspectives."

For the philosophical challenge, ChatGPT developed a thought experiment on the ethical implications of memory manipulation technology. It presented multiple perspectives, from utilitarian to deontological ethics, demonstrating an impressive grasp of philosophical discourse.

This depth shows ChatGPT’s potential as a tool for exploring complex ethical issues and facilitating rich academic discussions.

7. Climate-engineered future

Perplexity’s prompt for ChatGPT: "Describe a day in the life of a person living in a world where climate engineering has successfully reversed global warming, highlighting unexpected societal and technological changes."

Lastly, I asked ChatGPT to envision a day in the life of someone in a world where climate engineering has reversed global warming. ChatGPT described societal shifts and new technologies, like algae-based atmospheric scrubbers and global cooling skyscrapers.

This scenario was a testament to ChatGPT’s ability to weave scientific concepts into speculative futures, making it a valuable tool for futurists and policymakers.

Conclusion

From creative storytelling to solving interdisciplinary problems, ChatGPT handled each challenge created by Perplexity with a distinct flair, revealing its vast potential. I was immediately intrigued by Perplexity’s prompts because they were dynamic and complex.

I was consistently awed by the way ChatGPT tackled each prompt, demonstrating versatility across different domains while also keeping the responses engaging and informative. As we continue to explore the boundaries of AI, the possibilities seem as limitless as the creativity among the chatbots themselves.

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Artificial intelligence search startup Perplexity has launched a new feature that makes their results more sticky, allowing users to turn research into an easily shareable page.

Pages build on the existing AI-powered search functionality in Perplexity, which uses a similar system to Google to catalog websites but combines it with AI for analysis and display. 

This is similar to the heavily criticized Google AI Overviews but in a more chatbot-like format. It is also a good chatbot in its own right and on my list of best ChatGPT alternatives.

With Pages you ask a question and set the target audience, then Perplexity parses the billions of webpages it has indexed and uses AI to collate the results. Instead of simply replying to your message in the chat window with the response, it turns it into a targeted Page.

As a journalist paid to create content pages on my specialist topics, this was a worrying new concept. Still, every piece of information in the new Perplexity Pages is cited and includes links to the original source — often opinions or research articles by people like me.

How do you create a Page in Perplexity?

The new Pages feature in Perplexity is accessible through the Library. You can then click to add a new Page, Thread or Collection. With the new Page you give it a topic, set the audience and let Perplexity get on with its research.

I tried it out by creating a page on the Civilization series of games. I’ve played Civ in one form or another since I got it with an Amiga 600 for my 11th birthday in the early 90s.

It was incredibly easy to set up. You give it the topic and it creates an overview page. You can then add header images and new sections. Each section is generated from a search query.

Perplexity told me sourcing the information and citations were vital. “In each section, you can view the sources for that content so you can always trace the information back to its original context,” a spokesperson said.

They even go as far to say: “If you remove a source, that section will be rewritten to no longer include information from that source.”

What is the point of AI Pages?

With Perplexity, and using search in Google Gemini and ChatGPT, its is transient content. You search, it provides and answer and if someone else asks the response will be slightly different.

Pages allows for the creation of specific pockets of information, generated by AI with citations to real, researched internet sources in a way that can be easily shared.

This poses a challenge to Wikipedia — which itself provides much of the source material for the pages being generated — as people can just go straight to Perplexity Pages for the details. 

However, as the company points out, the value is in the citation, with links back to every page. So, as long as Wikipedia or any other source continues to be updated then it will always get links from Perplexity Pages.

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Perplexity has quickly become a force in the world of search, using artificial intelligence to offer answers to questions rather than a simple page of links. Its founder hopes to build on this and challenge Google to become the place to find information online.

This is something Google has dipped its toe into with the opt-in “Search Generative Experience” experiment, but coming from such a dominant position has made it reluctant to rock the boat.

Just as Google disrupted Yahoo, Lycos, and Infoseek two decades ago by offering something different, being faster and more efficient — it could be about to suffer the same fate to a smaller, more nimble competitor.

Perplexity uses a range of methods to offer its results, including custom-built large language models, OpenAI’s GPT-4, and, it seems, Google’s own data.

First reported by The Information, results for similar queries seem to be ordered the same in Perplexity and Google. CEO Aravind Srinivas, an outspoken opponent of Google, admitted to using Google's ranking signals if the AI thinks it is the best indicator of link quality.

What is Perplexity?

Founded in 2022 by former Google and OpenAI employees, the company has raised over $100 million, including investment from AI giant Nvidia, whose CEO, Jensen Huang admits to using it "almost every day" as both a search engine and chatbot.

Its interface is more ChatGPT than Google, but at the core, it is primarily a search engine, offering up a list of results but presented with analysis and in a conversational format.

The free version offers simple responses, sources for every statement made, and images. If you want a more immersive experience, you can also pay for the premium plan, which includes image input and generation.

As well as its own base model and offering a range of free models, Perplexity also offers access to a wide range of powerful models to answer questions, such as Claude 3 Opus, GPT-4-Turbo, and Mistral Large in the Pro plan.

Perplexity CEO Aravind Srinivas has previously claimed Google would be viewed as something that is legacy and old, whereas his company would be seen as the next generation and future.

Personally, I'm a huge fan of the way Perplexity works. It is intuitive, simple enough for casual use, and complex enough for those of us wanting to take a deeper dive into AI. It actually gives me answers to the questions I'm asking with sources.

How does Perplexity work?

It is like taking ChatGPT and Google and merging them into a new app, but in a way that actually works, services up information, and respects the source of the information.

While ChatGPT and Google Gemini can provide links and sources of information, it is largely hidden or hard to find. Copilot does a better job, but Perplexity works well at exposing information online in a way that doesn’t make it secondary to the chatbot.

While Google's search signals inform the results, Srinivas says Perplexity doesn't actually copy the results themselves, that it has its own bots to crawl the web and index information — the same as Google. 

It uses APIs from Bing for its ranking signals and likely uses a third party to get the Google data, as the search giant holds this information a closely guarded secret. These rankings determine how important a website is for a specific term or topic. 

Srinivas says they take a number of data points to determine its ranking including how recently it was updated, not just the Google and Bing ranking data. This is then fed into its AI, where further analysis happens, and summaries are created. 

Why is using Google rankings an issue?

On its own, this isn’t a problem at all. If your goal is to answer questions and provide information, then the more data points, the better. Still, Srinivas's past boasts about the newness and value of his technology lose some weight when they utilize the “legacy tech” of Google.

The claims of using Google and Bing in the process of setting rankings for Perplexity also doesn't come at a great time for the company.

According to the Information, OpenAI is building a dedicated search product that is powered by Bing but uses its own powerful AI to provide analysis, ranking, and summarization of results.

This could even be integrated into ChatGPT, offering a fast search product to compete with Google and Perplexity. 

Srinivas, however, may not care. He is a big proponent of competition, writing on X: "Competition doesn't kill companies; companies kill themselves by not focusing on users and long-term thinking."

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Rabbit has signed its first partnership deal for its R1 artificial intelligence device that took CES 2024 by storm. Perplexity AI, the “answer engine” will make its large language model and API available for Rabbit OS to provide live data and responses to a wider range of queries. 

Perplexity AI has quickly become a popular alternative to Google or Bing. It is a combination AI chatbot and search engine, providing answers to queries alongside links to source information. Currently available on iPhone, Android and the Web, this is a new approach for the AI tool.

While the Rabbit R1 doesn’t have apps that the user interacts with directly it will have access to other AI tools in the background. These services will be used to enhance the default features of the Rabbit large action model and provide data not available any other way. Rabbit says Perplexity is the first of many partnerships.

Giving away the pro plan to early adopters

The first 100,000 people to buy a Rabbit R1 will also get Perplexity Pro for free for a year, providing access to more advanced generative AI features and more detailed responses.

Rabbit has already sold out the first 50,000 $199 R1s, initially releasing them in batches of 10,000 at a time. The sixth run will have 50,000 units and is still expected to sell out quickly.

They are being shipped on a first-come-first-serve basis, with those buying in the first batch getting them sometime between May and June. Anyone buying the sixth batch in the U.S. will get an R1 in June or July but those in Europe will have to wait until August.

What difference will Perplexity make?

The R1 was already an impressive device. Designed by Teenage Engineering, it packed a lot into a small and relatively cheap package. 

Using the Rabbit large language model and its own patented large action model, it could perform real-world tasks from a voice prompt.

For example, a user could ask it to plan a date and it would find a restaurant, book the table, send messages and get the Uber to and from the destination.

Perplexity AI will significantly improve the quality of responses, provide a broader knowledge set and allow queries about real-world events in real-time.

How does it get real-time data?

The AI startup explained: “Together, we are introducing real-time, precise answers to Rabbit R1, seamlessly powered by our cutting-edge PPLX online LLM API, free from any knowledge cutoff.”

Most large language models are trained up to a certain point then before release the knowledge is locked away. OpenAI’s GPT-4 has live data up to April last year but supplements this with the ability to search the web using Bing — bringing real-time data into ChatGPT.

Perplexity will do something similar for the Rabbit R1, supplementing the large language model built into the Rabbit OS with the PPLX language model that draws continuously from the internet for its training data.

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