Nvidia-backed Perplexity launches AI-powered browser to take on Google Chrome
The launch marks Perplexity AI's entry into the competitive browser market, aiming to replace traditional navigation with agentic AI that can think, act, and decide on behalf of users.
Google Chrome held a commanding 68% share of the global browser market in June, according to StatCounter, cementing its position as the world's most widely used browser—far ahead of Safari, Microsoft Edge, and Firefox.
Comet enables users to ask questions, perform tasks, and conduct research in a single, unified interface. The browser integrates a built-in assistant that can compare products, summarize content, book meetings, and transform complex workflows into simple, conversational experiences.
Comet is currently available to subscribers who pay $200 per month for Perplexity Max, with broader access rolling out via invite over the summer.
Backed by high-profile investors like Jeff Bezos, SoftBank, and Nvidia, Perplexity is leveraging the launch of Comet to directly challenge incumbents such as Google's Chrome and Microsoft's Edge, while also exploring new revenue streams in advertising and e-commerce.
Last year, OpenAI added a search engine to ChatGPT and recently made the service available to all of its users. Google also introduced an AI-powered search feature, called AI Overviews, last May.
Comet stores data locally and avoids model training on personal information—a move likely to appeal to privacy-conscious users.
However, the company has come under criticism from media organizations such as News Corp-owned outlets, Forbes and Wired, and Wall Street Journal parent Dow Jones for using their content without consent or compensation. Perplexity has responded by launching a publisher partnership program to collaborate with news outlets.
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Business Wire
21 minutes ago
- Business Wire
Fresha Enhances Customer Engagement with RCS for Business Powered by Twilio and Google
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Tom's Guide
an hour ago
- Tom's Guide
I walked 4,000 steps with the Pixel Watch 3 vs Samsung Galaxy Watch 8 — here's the winner
I just walked 4,000 steps with the Google Pixel Watch 3 on my right wrist and the new Samsung Galaxy Watch 8 on my left to determine which is the more competent fitness tracker. To keep things fair, I manually counted my steps as the primary control for this showdown; I also ran Strava on a separate device (iPhone 12 mini) as a control for distance, elevation and pace data. After 4,000 steps and roughly 2.3 miles, one smartwatch proved (slightly) more accurate in this match-up of the new Samsung Galaxy Watch 8 vs Google Pixel Watch 3. Read on to find out which. But first, here's a quick look at how these two flagship models compare. Both run Google's Wear OS platform, and neither plays nicely with the iPhone. The Galaxy Watch 8 is Samsung's new release for 2025, while the Pixel Watch 3 represents Google's 2024 model; we'll likely get a Pixel Watch 4 model in August, if rumors prove true. Design-wise, the Galaxy Watch 8 features a "cushion" case design, borrowed from 2024's Galaxy Watch Ultra, compared to a circular case for the Pixel Watch 3, though both feature circular displays. The Pixel Watch 3 comes in two sizes, 41mm and 45mm; the latter is represented here. The Galaxy Watch 8 standard model similarly comes in a smaller, 41mm, and larger, 44mm option. There's also a 46mm Galaxy Watch 8 Classic with a rotating bezel, used for this comparison. The standard Galaxy Watch 8 models start at $349 for the 40mm model, which is the same starting cost as the 41mm Pixel Watch 3 (though you can score one on sale right now, link below). Get instant access to breaking news, the hottest reviews, great deals and helpful tips. The Google Pixel Watch 3 in 45mm is my favorite long-lasting smartwatch for Android, offering two full days of battery with normal use during my testing. It also has Google's ground-breaking and possibly life-saving new Loss of Pulse Detection, and is loaded with other insightful wellness tools and helpful smart features. I'm still in the process of testing the new Samsung Galaxy Watch 8 Classic, available for preorder as of this writing and shipping July 25. But I've found a lot to like, including the design — I'm a huge fan of the rotating bezel and customizable Action button — as well as its impressive suite of holistic tools, including some of the most in-depth sleep insights you'll find on a smartwatch. Both smartwatches feature handy safety tools and access to the same enormous app library. Each is also brimming with wellness and fitness features, including deep insights into sleep quality, helpful workout training recovery tools, and potentially life-saving health-monitoring apps. The Pixel Watch 3, for instance, is the only smartwatch on the market with Loss of Pulse Detection. Similarly, Samsung's new cardiovascular load monitoring tool is only available on the latest Galaxy Watch 8 and Galaxy Watch Ultra models. Still, either can perform an ECG, check your heart rate, or monitor your blood oxygen saturation levels. Nuances aside, these two devices are remarkably well matched. So, which came out ahead in this walk test? In my previous article, where I walked 5,000 steps with the Apple Watch 10 vs. the Samsung Galaxy Watch 8, Cupertino took home the trophy. Can Samsung score some redemption? Find the results of my walk test with the Pixel Watch 3 vs Galaxy Watch 8 below. Samsung Galaxy Watch 8 Classic Pixel Watch 3 XL Control Step count 4,044 steps 4,042 steps 4,000 steps (manual count) Distance 2.30 miles 2.33 miles 2.33 miles (Strava) Elevation gain 151 feet 157 feet 143 feet (Strava) Average pace 14 mins 42 secs per mile 15 mins 4 secs per mile 14 mins 29 secs per mile (Strava) Average heart rate 133 bpm 132 bpm n/a Max heart rate 158 bpm 158 bpm n/a Total calories burned 247 calories 339 calories n/a Device battery usage 10% 6% n/a Both the Pixel Watch 3 and Galaxy Watch 8 each produced step count totals within 50 steps of my actual total. This is a very impressive level of accuracy and well within a reasonable margin for error. Strava also measures step count, and was even more spot-on with a total of 3,990 steps. All three devices also essentially measured the same distance covered and similar amounts of elevation gained; the 14 feet separating Strava's tally from Google's is equivalent to 1.5 flights of stairs, i.e., not enough for concern. The Pixel Watch 3 and Galaxy Watch 8 produced step count totals within 50 steps of my actual total. This is a very impressive level of accuracy. Average pace data additionally matches nicely; I was moving fairly quickly for the duration of this walk and made minimal stops, except for one or two traffic lights. Strava measured the fastest moving time, but also provides an averaged elapsed pace, which came out to 15 minutes and 17 seconds per mile. Both Samsung and Google wearables have a well-earned reputation for accurate heart rate data — something I can attest to based on reviewing numerous devices from each — and the results from this walk test are in near-perfect agreement with not only each other, but also my expectations based on numerous prior tests. Finally, Samsung calculated fewer calories burned during my roughly 35-minute walk, but coincidentally, also burned nearly twice the amount of battery tracking my trek as the Pixel Watch 3. And the winner of this challenge is... the Google Pixel Watch 3. That said, this is about as close as these walk tests come to being called a tie. Over the years, I've probably written 25-plus head-to-head comparisons of this type, and I can't think of another time where the winner was determined by just two steps. Stay tuned for more testing on the Samsung Galaxy Watch 8, including my full review where I'll share the inside scoop on the device's newest features, like Run Coach, bedtime reminders, antioxidant tracking and Vascular Load monitoring. Which smartwatches or fitness trackers would you like to see me test head-to-head next? Let me know in the comments below. Until next time, happy walking!


Tom's Guide
2 hours ago
- Tom's Guide
No, The Simpsons didn't predict that — here's how AI is fueling viral hoaxes (and how to spot them)
I've mentioned AI scams getting worse, but 've noticed another pattern lately: viral hoaxes are popping up more often, and they're spreading faster than ever. Two recent examples claim that "The Simpsons" predicted oddly specific events, like a Coldplay concert kiss cam scandal or a July 5 megaquake in Japan. But when I looked closer, these 'predictions' were paired with images and clips that just didn't feel right. That's because many of today's viral hoaxes weren't exaggerations. They were actually created by AI-generated images, fake video clips and deepfakes designed to mislead. Ironically, while AI is fueling some of the most convincing hoaxes we've ever seen, it can also help uncover the truth. With the right prompts, tools and a bit of digital detective work, AI can actually reverse-engineer a viral fake; tracing its origins, analyzing visual clues, and cross-referencing content across the web. Here's a guide to using AI tools to investigate and potentially debunk internet hoaxes or something you may see online that just doesn't seem accurate. Each tool serves a different purpose and can help you determine for yourself what's real and what's fake. Get instant access to breaking news, the hottest reviews, great deals and helpful tips. As ironic as it may seem, ChatGPT is surprisingly good at fact-checking when prompted correctly. Contextual analysis, historical comparisons and myth-busting logic can all be done with ChatGPT because it can cross-reference known information, flag inconsistencies and explain why a claim might feel true even when it isn't. I started by dropping the viral claim into ChatGPT with the prompt: 'Did The Simpsons really predict a Coldplay concert kiss cam scandal?' ChatGPT flagged whether the episode exists (no), explained why the claim might sound familiar (inspired by an old meme) and provided credible context to debunk the myth. While ChatGPT is pretty good about citing the source, you can always ask if you do not see sources cited. Just prompt it and ask for the source. You can even ask follow-ups like, 'What are common hoaxes involving The Simpsons predictions?' to uncover patterns, manipulation tactics and why certain rumors go viral. Perplexity is a great resource when it comes to tracing source material and linking to real articles, Reddit threads or archived posts. Start by pasting the hoax headline or a quote from the viral video into Perplexity and prompt the AI with something like: 'Where did this claim originate?' You'll get search-backed responses, often with exact publication dates and hyperlinks; perfect for tracking how widely (and quickly) the hoax spread. For deeper dives with more citation-based answers with Perplexity, toggle "Copilot" mode. If you enjoy myth busting and plan to do it often, give Perplexity Spaces a try. This designated workspace uses templates, and you can choose one and adapt it to hoax-busting by adding steps like 'specify source type,' 'check date & origin,' or 'cross-reference with trusted outlets." In this spot you can also upload reference materials (e.g., fact-check reports, official statements) alongside web searches. Using the Space allows you to create custom AI instructions so you can tell Perplexity to always check sources or highlight inconsistencies every time. See an image while scrolling that doesn't seem real? You can upload it into ChatGPT and ask if it's AI generated, but Google Lens takes it a bit further. If you're uncertain about the provenance of a photo, take a screenshot of the viral image or video thumbnail and upload it into Google Lens. Then ask something like: 'Where does this image appear online?'or 'Is this photo real or AI-generated?' You might discover it was pulled from a stock image site or altered from an old meme, which is a clear red flag. Wayback Machine is essentially the internet's time machine. It's good for checking if articles or websites were quietly edited after going viral. Although this is not an AI tool, you can plug the URL into to compare older snapshots. From there, you may discover that details were changed, added or deleted once attention picked up and the image or video went viral. We've covered how to detect AI in images and writing and these two sites are useful for that. You can upload a clip or frame into one of these platforms and the AI tool will analyze the content for signs of AI manipulation. This is especially useful for fake faces or voices. The tools will scan for red flags like mismatched lip movements, strange lighting or inconsistent blinking; all signs that the video may have been AI-generated or altered. AI hoaxes are going viral every day and are getting harder to detect by the minute. But knowing how to use AI to help combat misconceptions means anyone can become a digital mythbuster. Diving deep into their origins is fun, empowering and dare I say, habit forming. Don't say I didn't warn you because you may find yourself going down some seriously cool hoax rabbit holes. So now, whether you're side-eyeing a suspicious TikTok or wondering why "The Simpsons" is trending again, AI can help you separate fact from fiction. Follow Tom's Guide on Google News to get our up-to-date news, how-tos, and reviews in your feeds. Make sure to click the Follow button.