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A new IMF report exaggerates the gloomy economic backdrop, but there are valid reasons for policymakers to be glumView the full article

Bank of England should not lower interest rates before price pressure shows signs of easing, says chief economistView the full article

Fund upgrades outlook for global growth but warns of more ‘pass-through’ of tariff costs to consumersView the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. If you’ve been looking for a great pair of noise-canceling earbuds that don’t cost a fortune, the JBL Tune Buds are now down to $44.95, their lowest price yet, according to price trackers. That’s less than half of what they’re originally sold for, which makes them a strong contender in the under-$50 range. JBL Tune Buds $44.95 at Amazon $99.95 Save $55.00 Get Deal Get Deal $44.95 at Amazon $99.95 Save $55.00 These are true wireless earbuds that focus on delivering that signature JBL bass (deep and thumpy) but with enough flexibility to tweak the sound using the JBL app. Out of the box, they lean heavy on the low end, which works well for pop and EDM, but you can easily adjust the EQ if you prefer something more neutral. Performance-wise, the Tune Buds pack in more than you’d expect for the price. They support Bluetooth 5.3, AAC, and SBC codecs, along with multipoint pairing, so you can jump between your phone and laptop without reconnecting. The active noise cancellation is solid for casual use—good enough to dull traffic noise or a chatty office, even if it can’t fully block the low rumble of a subway, notes this PCMag review. There’s also an IP54 rating, meaning these can handle sweat and light rain, making them suitable for workouts or daily commutes. Touch controls are customizable through the companion app, and there’s built-in Alexa support if you like using voice commands hands-free. As for the battery life, JBL claims up to 10 hours per charge with ANC on and 12 hours without, plus an extra 30 to 36 hours from the charging case. That’s easily a few days of use (your mileage may vary) without needing to plug in. The 10mm drivers cover the standard 20Hz to 20kHz range, and the earbuds come with three silicone tip sizes to help with comfort and fit. They don’t offer premium-level sound or the silence of high-end ANC sets from Sony or Bose, but they strike a good balance between affordability, sound, and everyday convenience. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods Pro 2 Noise Cancelling Wireless Earbuds — $197.00 (List Price $249.00) Samsung Galaxy S25 Edge 256GB Unlocked AI Phone (Titanium JetBlack) — $819.99 (List Price $1,099.99) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $319.00 (List Price $349.00) Blink Mini 2 1080p Indoor Security Camera (2-Pack, White) — $34.99 (List Price $69.99) Ring Battery Doorbell Plus — $149.99 (List Price $149.99) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $34.99 (List Price $69.99) Ring Indoor Cam (2nd Gen, 2-pack, White) — $79.99 (List Price $99.98) Amazon Fire TV Stick 4K (2nd Gen, 2023) — $29.99 (List Price $49.99) Shark AV2501S AI Ultra Robot Vacuum with HEPA Self-Empty Base — $359.89 (List Price $549.99) Amazon Fire HD 10 (2023) — $69.99 (List Price $139.99) Deals are selected by our commerce team View the full article

When Apple’s AirTag came out four years ago, one of the most obvious uses for it was for luggage. On my long trips to Asia, I always breathe a sign of relief when I glance at my phone and find that my checked suitcase has been loaded onto the aircraft. And I often wish I had one in my carry-on suitcase, especially when the overhead bins run out of space and the flight attendant checks my bag at the gate. July, a fast-growing Australian startup, has become the first luggage brand to incorporate AirTags directly into its suitcases. The technology was made in partnership with Apple and Google, so the tags are integrated with both Apple’s Find My and Google’s Find Hub networks. On October 14, July unveils this new feature, which will eventually be incorporated into its full line of carry-ons and suitcases. Cofounder Athan Didaskalou believes trackers will soon become standard in all suitcases, but it is still important to him for July to be first to market with this technology. “We have a team of industrial designers on hand, and we like making things,” Didaskalou says. “The only way to stand out today is by continuing to innovate.” The Ubiquitous Roller Suitcase Step into an airport today, and you’ll see virtually every traveler pushing wheeled luggage. Didaskalou points out that each element in the now-ubiquitous roller suitcase was the result of a breakthrough in design. In 1987, an airline pilot developed the concept of a wheeled suitcase with a telescoping handle—a vast improvement over having to carry your suitcase like a briefcase. By the 1990s, most suitcase brands had shifted to this design. In recent decades there have been incremental improvements. After September 11, 2005, the Transportation Security Administration imposed a new regulation that all luggage locks had to have a keyhole that agents could access. Soon after, it became standard for all suitcases to have TSA locks. And a decade ago, brands began incorporating phone chargers into their suitcases so travelers could charge their phones on the go. (The TSA now forbids phone chargers in checked luggage, so chargers in suitcases must be removable.) The global luggage market is enormous: It was $38.8 billion in 2023, according to Grand View Research, and it’s projected to grow to $61.49 billion by 2030. Given that most suitcases today have the same set of standard features, brands often end up competing with each other based on aesthetics. Samsonite dominates the industry, owning a fifth of the market with its many brands, which include American Tourister and Tumi. Samsonite generated $3.68 billion in 2023. But there are many other players. At the high end, there’s Rimowa, known for making durable suitcases with distinct grooves. Over the past decade, a wave of startups has popped up with sleeker and more colorful designs at an affordable price point of $200 to $300 for a carry-on. Direct-to-consumer startups like Away, Monos, Béis, and Floyd all create trendy cases that target the millennial and Gen Z traveler. But it’s a crowded, competitive market, and some brands have struggled. Paravel, for instance, tried to create an eco-friendly suitcase, but it filed for bankruptcy in May of this year, and was acquired by the British suitcase brand Antler. Another luggage brand, Baboon to the Moon, was struggling to grow its revenue and was acquired by turnaround firm the Hedgehog Co. in 2023. Improving the Design of a Suitcase July was founded in Australia in 2019. Its sleek, colorful suitcases have become very popular in Australia and across the Asia Pacific region, which North American brands like Away and Monos have been slower to enter. Didaskalou wants July to stand out from competitors by rethinking the design of its suitcases in a more fundamental way. Over the past few years, the brand has been playing with the configuration of suitcases. It was among the first brands to launch the trunk format, where the suitcase doesn’t open in the middle, but rather toward the top. “Some people want depth when they’re packing,” he says. “It can be awkward to open your luggage in the middle and try to balance it on the luggage stand at your hotel.” When Apple and Google opened up the API for the AirTag, it occurred to Didaskalou that luggage tracking was the next frontier of suitcases. Many consumers were already putting AirTags in their suitcases, but it was not a seamless solution. “They might need to move the AirTag from one suitcase to another, or take it out to use it for something else,” he says. “Or they might forget to use it altogether. It’s just another thing to worry about when you’ve already got a lot on your mind.” July’s designers spent months trying to figure out how to incorporate AirTags seamlessly into suitcases. They ended up putting them into the strip of plastic at the top of the suitcase, right next to the TSA lock. When you first get the suitcase, you pull on the plastic tab that separates the battery from the AirTag to activate it. Then you press a button on the strip to activate it, to see your luggage in your Apple Find My or Google Find Hub app on your smartphone. Didaskalou says that while the experience is simple for consumers, it was complex to design. It was important to make the underside of the AirTag accessible to change its battery. However, the AirTag is on the same strip as the TSA lock. “We needed to have access to the AirTag but not expose the TSA lock,” he says. “We also needed everything to be very tightly secured, because things bounce and move when you travel.” July has patented some aspects of this AirTag component, but Didaskalou believes many other luggage brands will soon realize that consumers now expect to be able to easily track their luggage. So they will soon begin incorporating AirTags or other trackers directly into their suitcases. But he believes they will only become widespread in the next year or so. And ultimately, Didaskalou believes that it’s the larger luggage makers that are more likely to update their suitcases first. In many ways, he’s looking to compete with Samsonite, an innovator with roughly 20% of the market share. “Samsonite has always been first to come up with new materials and manufacturing processes,” Didaskalou says. “We’re proud because this is the first time we’ve beat them.” View the full article

Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. Many established study methods grew out of old research and stuffy pedagogical theories, so when a new one crops up on social media it’s worth checking out—if only to gauge whether a modernized approach can pay dividends. Sometimes, the most tried-and-true, old-school methods are best, but that doesn't mean fresh updates on traditional ideas can't be great, too. One study technique that frequently makes the rounds on social media is dubbed the “2, 3, 5, 7” method (or usually just "2357"). What’s interesting about this method is that while it is new in a sense, it is a modification of one of those older, time-tested techniques. More on that below, as well as what you need to know to use 2357 for your next study session. What is the 2357 study method?When using the 2357 technique, you revise your notes and study materials over and over again, following a set schedule: Day 1: Revise your initial notes Day 2: Revise and review them Day 3: Revise and review again Day 5: Revise and review again Day 7: Revise and review again Each time you revise, you should identify and expand upon key facts that you need to remember. If you usually take notes by hand, digitizing them can serve as your first revision. Conversely, you can play around with note types. On Day 2, you can redo your notes using the Cornell method, for instance, then make a mind map on Day 3. Taking a slightly different approach each time will force you to reconsider the material, identify elements you can expand on or you're not quite grasping, and think a little differently about how it all fits together. By the time you have completed that final revision on day seven, the content should be easy to retrieve from your memory with minimal effort. Days 5 and 7 should also focus a little more on reviewing, not just revising. One of those days can be dedicated to blurting, for instance, which is a technique that asks you to write down everything you can remember about a topic before checking against your notes and other resources for anything you missed. Try blurting a new note outline entirely. Why the 2357 method worksThis study method is effective because it combines elements of a few tried-and-true techniques, including spaced repetition, an established way to combat the so-called “forgetting curve” by increasing the amount of time between your study sessions until the information enters your long-term memory. This TikTok-beloved hack also employs elements of distributed practice, which operates on a similar theory. Studying via 2357 will work best if you slowly start weaning yourself off your notes and materials as you go, which forces you to practice active recall as you progress through the latter days of the cycle. Like I said, those final days of the cycle should be more about reviewing than revising. If you're running across information you're not quite grasping, mix in other techniques, like the Leitner flashcard method, which also relies on distributed practice to help you entrench material in your memory. Doing this all sounds easy, but it isn't quite. It might be harder than you think to remember to stick to this very specific schedule. If you find yourself struggling, call for backup. A school-focused planning app, like My Study Life, can help you create a schedule and carve out time for all these little studying tricks. View the full article

Shares in America’s “Quantum Four” quantum computing companies surged again yesterday. D-Wave, IonQ, Quantum Computing, and Rigetti all saw their stock prices jump by double-digit percentages. But why? The Quantum Four’s big stock price gains had nothing to do with radical new quantum computing breakthroughs. Instead, investors can thank banking giant JPMorganChase for the gains. Here’s what you need to know. Why did quantum computing shares surge yesterday? Yesterday, America’s four most prominent quantum computing companies saw their stock prices surge by double-digit percentages. But the genesis behind these soaring share prices wasn’t directly related to news about the companies. Instead, the upward movement in the Quantum Four’s share prices was largely due to financial giant JPMorganChase. On Monday, the investment bank announced a “Security and Resiliency Initiative” to invest in industries critical to America’s national economic security interests. This initiative will see JPMorganChase invest $1.5 trillion in select industries over the next 10 years. And the first wave of this funding—to the tune of up to $10 billion—has already been decided upon. The banking giant announced it will invest the 11-figure sum via “direct equity and venture capital investments” in companies operating across four key areas, which include: Supply Chain and Advanced Manufacturing Defense and Aerospace Energy Independence and Resilience Frontier and Strategic Technologies For quantum computing investors, it’s that last area—frontier and strategic technologies—that matters. Included in that grouping are companies in the AI, cybersecurity, and quantum computing space. “It has become painfully clear that the United States has allowed itself to become too reliant on unreliable sources of critical minerals, products, and manufacturing—all of which are essential for our national security,” JPMorganChase CEO Jamie Dimon said in a press release announcing the initiative. He added, “This new initiative includes efforts like ensuring reliable access to life-saving medicines and critical minerals, defending our nation, building energy systems to meet AI-driven demand, and advancing technologies like semiconductors and data centers. Our support of clients in these industries remains unwavering.” However, it is worth noting that Dimon did not specify which quantum computing companies would receive investments from the bank. In an accompanying chart, the bank merely said that strengthening capabilities in quantum computing and other areas, including AI and cybersecurity, “could directly translate into higher GDP and create military, intelligence, biotech, and cyber resilience benefits.” Yet despite not name-dropping any of the Quantum Four, their stocks surged. Quantum stocks soared by double digits In the United States, there are four prominent publicly traded quantum computing companies: D-Wave, IonQ, Quantum Computing, and Rigetti. All four companies saw their stock soar yesterday after JPMorganChase’s announcement. D-Wave Quantum (NYSE: QBTS): up 23% to $40.62 IonQ (NYSE: IONQ): up 16% to $82.09 Quantum Computing (Nasdaq: QUBT): up 12% to $21.46 Rigetti Computing (Nasdaq: RGTI): up 25% to $54.91 In addition to America’s Quantum Four, shares in the United Kingdom’s Arqit Quantum (Nasdaq: ARQQ) also jumped 20% to close at $58.27. Despite Monday’s price surges, all Quantum Four stocks and the U.K.’s Arqit are currently down in premarket trading on Tuesday morning, as of the time of this writing. The drops aren’t large: QBTS is down less than 3%, IONQ and QUBT are down around 4%, RGTI is down just over 3%, and ARQQ is down just under 3%. These modest declines suggest that some investors are engaging in profit-taking after yesterday’s share price surge. Still, many quantum investors are likely buoyed by the notion that one of America’s biggest investment firms thinks quantum computing will be critical to national security in the years ahead. If that conjecture is correct, companies operating in those spaces have a lot to gain. Shares in the Quantum Four have had a great year While the real-world benefits of quantum computing, which uses the properties of quantum mechanics to solve computational problems that classical computers couldn’t hope to, are likely still years away, the companies operating in the nascent space have seen tremendous returns over the past year. When it comes to the Quantum Four, all have had incredible returns both year-to-date (YTD) and over the past twelve months (12/m), as of yesterday’s stock market close: D-Wave Quantum (NYSE: QBTS): up 383% YTD, up 4,087% (12/m) IonQ (NYSE: IONQ): up 96% YTD, up 670% (12/m) Quantum Computing (Nasdaq: QUBT): up 29% YTD, up 3,001% (12/m) Rigetti Computing (Nasdaq: RGTI): up 259% YTD, up 6,629% (12/m) These are gains that many investors are hoping will continue well into the future. View the full article

IBM’s recent partnership with Anthropic marks a significant milestone for small businesses aiming to streamline their software development processes. By integrating Anthropic’s advanced AI model, Claude, into its suite of tools, IBM aims to deliver enhanced productivity, security, and governance within enterprise environments. This strategic alliance is particularly beneficial for small business owners looking for ways to leverage technology in their operations. With productivity gains averaging an impressive 45% reported by over 6,000 early adopters using IBM’s new AI-first integrated development environment (IDE), the potential for cost savings while maintaining high standards of code quality is a compelling reason to consider these new tools. Dinesh Nirmal, Senior Vice President of Software at IBM, stated, “This partnership enhances our software portfolio with advanced AI capabilities while maintaining the governance, security, and reliability that our clients have come to expect.” The IDE is designed specifically for enterprise software development lifecycles (SDLC), facilitating tasks like application modernization, code generation, and intelligent code review. These capabilities can not only save time but also lessen the burden on smaller development teams with limited resources. As digital transformation accelerates, the needs of small businesses often mirror those of larger enterprises, particularly in terms of efficient software development and data management. Developers using the new IDE can expect features such as: Application Modernization at Scale: Support for automated system upgrades and multi-step refactoring can help small businesses transition from legacy systems to modern frameworks without extensive downtime. Intelligent Code Generation and Review: AI-assisted code generation tailored to enterprise architecture patterns ensures that security and compliance needs are met, which can be crucial for small businesses operating in regulated environments. Security-First Development: The integration of security measures directly into development workflows allows for quicker addresses to vulnerabilities and compliance with industry standards, enhancing operational safety. End-to-End Orchestration: This capability coordinates tasks across the entire software lifecycle—from development through testing to maintenance—making it easier for small businesses to manage complex projects. Moreover, the partnership extends beyond the tools themselves. IBM has introduced a guide for enterprises on architecting secure AI agents, emphasizing a structured approach to managing AI within business contexts. This guide aims to make AI applications more reliable and safe, aspects that many small business owners find critical when adopting new technologies. However, while the advantages are compelling, small business owners should remain aware of certain challenges. Transitioning to AI-enhanced tools may require initial investment in training, as well as potential disruptions during onboarding. Ensuring that existing systems integrate smoothly with new AI solutions is paramount, particularly for those operating within tight budgets or facing resource constraints. Another consideration is the security aspect of deploying advanced AI tools. Small businesses must remain vigilant regarding data protection and compliance with regulations—challenges that could be heightened with the introduction of new technologies. As Mike Krieger, Chief Product Officer at Anthropic, noted, “Enterprises are looking for AI they can actually trust with their code, their data, and their day-to-day operations.” Ultimately, the partnership between IBM and Anthropic signifies a shift toward more accessible, secure, and efficient software development tools that can directly benefit small businesses. As the marketplace evolves, utilizing enhanced AI capabilities not only helps in modernizing operations but can also offer a competitive advantage. For small business owners eager to explore what AI can bring to their operations, this collaboration could pave the way for transformative growth. For further details about this collaboration and its implications for enterprise software development, you can access the full press release at IBM’s newsroom here. This article, "IBM and Anthropic Team Up to Revolutionize Enterprise Software Development" was first published on Small Business Trends View the full article

IBM’s recent partnership with Anthropic marks a significant milestone for small businesses aiming to streamline their software development processes. By integrating Anthropic’s advanced AI model, Claude, into its suite of tools, IBM aims to deliver enhanced productivity, security, and governance within enterprise environments. This strategic alliance is particularly beneficial for small business owners looking for ways to leverage technology in their operations. With productivity gains averaging an impressive 45% reported by over 6,000 early adopters using IBM’s new AI-first integrated development environment (IDE), the potential for cost savings while maintaining high standards of code quality is a compelling reason to consider these new tools. Dinesh Nirmal, Senior Vice President of Software at IBM, stated, “This partnership enhances our software portfolio with advanced AI capabilities while maintaining the governance, security, and reliability that our clients have come to expect.” The IDE is designed specifically for enterprise software development lifecycles (SDLC), facilitating tasks like application modernization, code generation, and intelligent code review. These capabilities can not only save time but also lessen the burden on smaller development teams with limited resources. As digital transformation accelerates, the needs of small businesses often mirror those of larger enterprises, particularly in terms of efficient software development and data management. Developers using the new IDE can expect features such as: Application Modernization at Scale: Support for automated system upgrades and multi-step refactoring can help small businesses transition from legacy systems to modern frameworks without extensive downtime. Intelligent Code Generation and Review: AI-assisted code generation tailored to enterprise architecture patterns ensures that security and compliance needs are met, which can be crucial for small businesses operating in regulated environments. Security-First Development: The integration of security measures directly into development workflows allows for quicker addresses to vulnerabilities and compliance with industry standards, enhancing operational safety. End-to-End Orchestration: This capability coordinates tasks across the entire software lifecycle—from development through testing to maintenance—making it easier for small businesses to manage complex projects. Moreover, the partnership extends beyond the tools themselves. IBM has introduced a guide for enterprises on architecting secure AI agents, emphasizing a structured approach to managing AI within business contexts. This guide aims to make AI applications more reliable and safe, aspects that many small business owners find critical when adopting new technologies. However, while the advantages are compelling, small business owners should remain aware of certain challenges. Transitioning to AI-enhanced tools may require initial investment in training, as well as potential disruptions during onboarding. Ensuring that existing systems integrate smoothly with new AI solutions is paramount, particularly for those operating within tight budgets or facing resource constraints. Another consideration is the security aspect of deploying advanced AI tools. Small businesses must remain vigilant regarding data protection and compliance with regulations—challenges that could be heightened with the introduction of new technologies. As Mike Krieger, Chief Product Officer at Anthropic, noted, “Enterprises are looking for AI they can actually trust with their code, their data, and their day-to-day operations.” Ultimately, the partnership between IBM and Anthropic signifies a shift toward more accessible, secure, and efficient software development tools that can directly benefit small businesses. As the marketplace evolves, utilizing enhanced AI capabilities not only helps in modernizing operations but can also offer a competitive advantage. For small business owners eager to explore what AI can bring to their operations, this collaboration could pave the way for transformative growth. For further details about this collaboration and its implications for enterprise software development, you can access the full press release at IBM’s newsroom here. This article, "IBM and Anthropic Team Up to Revolutionize Enterprise Software Development" was first published on Small Business Trends View the full article

Watchdog did not have proper basis for decision to write down SFr16.5bn of AT1 debt as part of rescue deal, judges findView the full article

Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. Studying is about so much more than just rereading some chapters and notes. That said, while it's a good idea to have a strategy for actually retaining what you’re going over, if your method is too convoluted, you’ll never stick to it—and then it's just as useless as mindlessly rereading the same section five times. The best study methods not only rely on research and established understandings of how memory works, but are easy to incorporate in a practical way. The "123" method meets all the criteria of a good study method. What is the 123 study method?The 123 study method is a lot like the 2357 method, except it’s much easier to stay on top of and actually execute. With 2357, you review and revise your notes and materials on days two, three, five, and seven after first learning them, which is a tricky schedule to remember and maintain. You can and should, however, call on a study-scheduling app, like My Study Life, to help you with this and other time-based academic tasks. The 123 method is simpler: On day one, you learn your material. On day two, you review it. Review it again on day three, then don’t think about it for a week, at which point you'll review it again. Again, use of a planner, calendar, or scheduler is encouraged here. These techniques are useful, but only if you actually execute and stick to them, so don't be afraid to get a little boost from an app or even your phone's built-in "reminders" function. Why the 123 study method worksThe 123 method relies on distributed practice, which calls for you to review your materials at spaced intervals to better retain them in your long-term memory. That's a technique that works fabulously, but often, adherents expect you to distribute the practice in ways that are difficult to manage. By going over it for three days, then giving your brain a week and seeing how much you retained, you can fit distributed practice into your life a lot more easily than if you follow some elaborate, torturous schedule of off days and on days. This method is best done about 10 days out from a big test, so you can study and review on those first three days, then once more the day before the test. How you review is up to you, but you can try flashcards, which help you with memory retrieval, or blurting, which helps you identify your problem areas by forcing you to recall as much information as you can without looking at your notes. Whatever method you choose for the actual review, try to make sure it incorporates some element of active recall, or the act of forcing yourself to pull key information from your memory. Just know that the one-week interval between reviews is key. When your brain has almost forgotten something, it works a little harder to pull the information out of your memory, which is what will truly help get the facts to stick before your big test. View the full article

Headaches continued for U.S. travelers over the weekend as a combination of bad weather and impacts from the ongoing government shutdown ensnarled many would-be fliers. Flight delays and cancellations piled up over the three-day holiday period, with flight-tracking service FlightAware showing nearly 30,000 delays in and out of U.S. airports from Sunday of last week through Monday. Here’s the latest on the situation at U.S. airports and what travelers need to know: How bad have flight delays been? Delays and cancellations at many airports have grown progressively worse since the U.S. government shut down on October 1. With no end in sight to the political impasse in Washington that brought us here, the shutdown will enter its third week tomorrow. FlightAware data shows there were 7,928 delays in and out of U.S. airports yesterday, along with 592 cancellations. Saturday and Sunday were roughly the same, with 5,007 delays and 114 cancellations on Saturday and 7,981 and 271 cancellations on Sunday. Airlines for America, a trade group representing U.S. airlines, had warned before the weekend that shutdown-related shortages in air traffic controllers could create travel headaches at a number of airports, although the group insisted that flying remains safe, as CNN reported. Bad weather, including a nor’easter that made its way up the East Coast, contributed to the chaos, causing delays at Northeast airports including New York’s John F. Kennedy International Airport and Newark International Airport in New Jersey. Will delays continue this week? As of early Tuesday morning, FlightAware data showed significantly fewer delays and cancellations for today (499 and 26, respectively), but the number was rising rapidly and only time will tell what the future has in store. (We’ll update this post later today with the most recent numbers.) Meanwhile, Republicans and Democrats on Capitol Hill remain deadlocked over key sticking points. Most crucially, Democrats want to extend Affordable Care Act (ACA) tax credits that are set to expire this year. According to estimates from the Kaiser Family Foundation (KFF), the loss of the credits would lead to significantly higher healthcare premiums for millions of Americans. View the full article

FSB launches fresh criminal case against former Yukos oil magnate and 22 other dissidents in exileView the full article

The $4.6 trillion-asset company's report comes after it committed to funneling $1.5 trillion into industries it said were important to national security. View the full article

Attack on Gazans inspecting homes comes days after fragile ceasefire goes into effect View the full article

The President’s latest piece of brinkmanship is likely to result in another climbdownView the full article

Data centers have become the starting blocks in the global race for AI supremacy. Tech giants like Meta, Alphabet, and OpenAI have committed hundreds of billions of dollars collectively to building more of them. States are offering incentives for their development, and President Donald The President signed an executive order in July cutting regulations to speed up construction. For all the breakthroughs they promise, the environmental toll of these facilities is already staggering: According to the International Energy Agency, U.S. data centers used roughly 185 terawatt-hours of electricity in 2024—more than all of Pakistan’s 248 million people used that year. To keep hot servers cool, a typical 100-megawatt hyper-scale data center consumes as much water per day as 6,500 homes. And, as with the factories and railroads that powered previous technological revolutions, the impact on surrounding communities can be especially profound. This premium story, accompanied by original photography commissioned by Fast Company, documents: Why one of Meta’s data center neighbors says, “I haven’t drank my water in years.” The number of homes that could be powered with the electricity consumed by one Meta data center How much the area’s light pollution has increased since 2020 What the ongoing data center boom is doing to electricity prices in states like Georgia What does “the cloud” look like? For Beverly Morris, it’s hulking, windowless buildings, bright lights, and literal clouds of dust. Peter Essick In 2020, two years after Beverly and husband Jeff Morris bought their home in Mansfield, Georgia, construction crews began clearing the way for what would turn out to be one of Meta’s largest data centers, a sprawling, 2.5 million-square-foot complex—larger than the state’s largest shopping mall—just 1,000 feet from their front door. With no official notice to Morris from Meta or surrounding Newton County representatives, the oak forest across her dirt road was felled; eventually, a white glow from a row of perimeter spotlights flooded their home nightly. “Nature was run out of there completely,” Morris says. By 2022, during busy construction days, thick plumes of red dust would storm across their property. After a particularly bad onslaught, Morris called the phone number she found on a construction sign; a crew soon showed up with power washers to hose down her house. “There was a red river running off of my roof,” she says. It was such a spectacle that one of the workers insisted on capturing it on his phone. She now wishes she’d obtained the video. “Everything was covered in red.” Beverly Jeff MorrisPeter Essick The new factories “The cloud” has never been a very helpful description of the global infrastructure of the internet, but as the global race for AI supremacy ramps up, a new, more apt metaphor has emerged. “I think everybody should stop saying data centers,” interior secretary Doug Burgum told a conference in D.C., where in July, The President signed an executive order cutting regulations to speed up data center construction. Burgum cited the term used by the CEO of Nvidia: ”It’s not data centers. It’s AI factories.” But these giant warehouses aren’t factories in the traditional sense. Even the most compute-intensive data centers employ few full-time workers. Most of the work in a data center is done by automated systems and software that manage the infrastructure, while the core computation of training and inference is powered by energy-hungry chips, often made by Nvidia. In the first half of 2025, spending on data centers—including big investments from Meta, Alphabet, OpenAI, Amazon, and xAI— contributed as much to U.S. GDP growth as household consumer spending—an unprecedented economic shift. But tremendous cash isn’t the only cost, and tech companies aren’t the only ones shouldering the burden. In Mansfield, Morris says the impact of all the digging and blasting to build Meta’s data center, known as Stanton Springs, eventually extended to her well water. By 2023, the pipes in her house were clogged with sediment, wrecking appliances and slowing faucets to a drip. “I haven’t drank my water in years,” says Morris, who estimates she’s spent about $5,000 on repairs so far. She said a July appraisal found that her property’s value had cratered. Peter Essick The extent to which the construction of the data center contributed remains unclear. A Meta spokeswoman told The New York Times that “the company had recently commissioned a well study on the Morrises’ property and said it was ‘unlikely’ that its data center affected the supply of groundwater in the area.” Though the study—a copy of which was reviewed by Fast Company—assessed the impact of the facility’s construction and operations on local groundwater and nearby wells, Morris says “Neither Meta nor anyone else came on my property to do a groundwater study.” Meta declined repeated requests for comment on this story. “It has changed the way that I live here,” she says. “And they really accept no responsibility for it. And they’re big enough to do that.” How AI’s power needs affect everyone Tax breaks and relatively cheap power have turned the Atlanta area into the country’s fastest-growing hyper-scale data center market. Demand is so high that the Peach State has delayed closing several coal-fired power plants. Only a few years ago, Big Tech touted bold carbon targets. Now Bob Sherrier, a staff attorney in the Southern Environmental Law Center’s Georgia office, says the data center blitz “will deepen our reliance on dirty, volatilely priced methane gas and coal for decades.” (Stanton Springs consumed 968,000 megawatt-hours of electricity in 2023, according to Meta‘s most recent numbers, enough to power about 90,000 average homes.) Nationally, Morgan Stanley estimates that forecasted data center demand will require an additional 45 gigawatts, or about 10% of all current U.S. generation capacity—equivalent to 23 Hoover Dams. The data center build-out also means that all the “cheap power” that’s drawn developers to states like Georgia isn’t actually that cheap: Nationally, the cost of building out new transmission lines and substations to power the AI push is contributing to surging electricity rates for customers across the country. “In Georgia, our rates have gone up six times,” Morris says. Peter Essick Power is only part of the equation: Keeping chips cool means withdrawing and consuming immense amounts of water, and developers prioritize places that are hot and dry, where power tends to be cheaper, meaning most data centers are being built in areas with high water stress. According to the local water authority, the Stanton Springs facility guzzles about 10% of Newton County’s daily water supply. In Newton County, demand is rising so fast that residents could face a water deficit by 2030, according to a 2024 report. Growing AI’s footprint—and impact Some of the world’s biggest projects are emerging in neighboring Louisiana. In Memphis, a supercomputer for Elon Musk’s xAI has been relying on dozens of unpermitted temporary gas turbines, exacerbating health issues in the surrounding community. In Richland Parish, a plan to build 2 gigawatts’ worth of gas turbines for a Meta data center project was recently approved by planning authorities, despite local objections that the process was rushed and lacked transparency. But the scale of the project is no secret: “Just one of these covers a significant part of the footprint of Manhattan,” CEO Mark Zuckerberg wrote on Facebook. Not to be outdone, OpenAI and Oracle are building an 800-acre data center in Texas that will form part of the Stargate project, a partnership with the The President administration to create a nationwide backbone for training ever-larger AI models. Backed by a $100 billion investment from Nvidia (much of it to be spent on its own chips), the five-data-center project could demand upwards of 10 gigawatts—about as much energy as consumed by all of New York City. Morris, who grew up in Georgia, misses the fireflies that used to surround her house, which glowed until the data center showed up. Even with the spotlights switched off, the facility, now operational, still creates a dome of light visible from miles away. (The area’s Bortle score, a measure of light pollution, shows a 25% increase in artificial brightness since 2020.) The sounds of construction have been replaced by a constant electric hum, periodic alarms, and the intermittent buzz of diesel generators. Morris admits to feeling powerless, but has found some comfort online—even on Facebook—connecting with others across the state who are pushing back against new data center development. “I know I’m not the only one now,” she says. And she’s right. Last month, the city council for the nearby city of Social Circle unanimously enacted a 90-day moratorium on new data centers. A version of this story appears in the latest issue of Fast Company magazine. View the full article

For the past five years, Fast Company’s Next Big Things in Tech awards have celebrated technological breakthroughs that are changing the way we work and live. This year’s awards include 137 honors for innovations impacting everything from applied AI to telecommunications to agriculture. Arriving at that cadre of winners from a pool of 1,200 applicants requires many hours of work sifting through applications, scrutinizing projects, and deciding which achievements rank at the top. Here is a peek into how our small army of editorial staffers make it happen. Methodology Our team of editors and writers assessed each application based on factors such as: Relevancy: What pressing problem does the technology solve? Ingenuity: How novel is the technology? Progress and potential: In what ways has the technology already proven itself? Is it positioned for long-term viability and scalability? Impact: What kind of impact—from economic to cultural—might the technology have over the next five years? Each winner is chosen after multiple rounds of evaluation and conversation between judges about its performance on the above criteria, a monthslong process. “With Next Big Things in Tech, our aim is to honor projects based not only on what they’ve already achieved but where they’re poised to go,” says Fast Company global technology editor Harry McCracken. “Whether honorees are still in the lab or already on the market, they’re driving progress in tangible ways on an array of fronts.” Meet the team Judges Adam Bluestein, Morgan Clendaniel, Yasmin Gagne, Connie Lin, Maia McCann, Harry McCracken, Steven Melendez, Chris Morris, Jared Newman, Alex Pasternack, Rob Pegoraro, Adele Peters, Ross Rubin, Mark Sullivan, Marty Swant, Max Ufberg, Mark Wilson Coordinator Shealon Calkins Design/Photo Jeanne Graves, Anne Latini, Daniel Salo, Mike Schnaidt, Amy Wong Development Bryan Cuellar, Heda Hokschirr, Cayleigh Parrish View the full article

Across both white-collar and blue-collar settings, productivity depends on how well information is organized and communicated. DataSnipper uses AI to help auditors quickly surface relevant details in lengthy legal documents, while Sharebite streamlines employee meal programs for the hybrid workplace. Tines has developed a unified AI platform to manage a wide range of workplace software, and Weavix has reimagined the shop-floor radio for modern communication needs. DataSnipper For helping rapidly sift through lengthy financial documents Auditors often need to extract dates and financial details from dense documents such as leases, loan agreements, and meeting minutes—tasks too complex for a simple “Ctrl+F” search. DataSnipper automates this work directly within Excel, using AI to respond to written prompts and link results back to their source for quick verification. Launched in April 2025, the tool is already credited by audit firms with reducing document review time by 25%. Sharebite For taking the hassle out of employee meal programs Feeding employees has become more complex in the hybrid-work era. Sharebite’s Passport program provides workers with a Visa card that employers can configure to work only at specific times and locations, encouraging in-office attendance. The company’s Stations service simplifies group ordering for central pickup at the office. For every meal purchased, Sharebite donates a meal to people in need through its charity partners. Tines For building one unified AI system to command workplace cloud software While many workplace tools now feature AI assistants, Tines has developed a system that can coordinate across multiple cloud platforms, from trouble-ticketing systems to IT management services. Launched in September 2024, Tines Workbench connects securely to a wide range of software and converts plain-language instructions into precise, preapproved actions. The technology has gained traction quickly, helping Tines raise a $125 million Series C funding round in February 2025. Weavix For building the future of two-way radio communication Worksite radio communication has evolved far beyond the analog walkie-talkie. Weavix’s Walt Smart Radio System adds features such as Slack-style departmental channels, AI-powered translation, and geofencing for security. The radios support voice, text, and photo messages, making them useful in settings like manufacturing plants. Designed for tough environments, they can be operated while wearing gloves or other protective gear, and badge-tap authentication makes handoffs simple at shift changes. The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2025. Read more about the winners across all categories and the methodology behind the selection process. View the full article

This year’s wellness and fitness honorees encompass innovations in sleep, fitness, and mental well-being. They help users chill out, de-stress, and take concrete actions to reduce their chronic disease risk. Sure, some of these may seem over the top. But as technologies improve and reach scale, what’s over the top now could become a basic necessity tomorrow. Ammortal For building the ultimate rejuvenation machine The Ammortal Chamber may be the ultimate self-care flex at the moment. The fully immersive “wellness experience” combines red light therapy for cellular regeneration, vibro-acoustic sound therapy to harmonize the nervous system, pulsed electromagnetic fields to reduce inflammation and accelerate recovery, molecular hydrogen to combat oxidative stress, and guided breathwork and visual meditation for deep mental relaxation. After rolling out to luxury hotels and some two dozen wellness centers earlier this year, it’s now available for consumers who aren’t stressed out by the $160,000 price tag. iFutureLab For making sleep more restorative Autonomous furniture? Why not? iFutureLab’s Heka AI Mattress combines artificial intelligence—its TrackR AI Sleep Chip System—with an array of biomedical sensors to sense and release body pressure and adjust lumbar support based on body position. Since launching in 2018, the company has opened more than 630 “experience centers” worldwide and reached 200,000 users. Molecular You For tracking the metrics of healthy longevity Unlike traditional blood tests, which focus on a limited set of biomarkers for a few conditions, Molecular You measures more than 280 proteins and metabolites from a single blood draw, identifying presymptomatic signals of dozens of chronic conditions, including Alzheimer’s disease, heart and liver disease, autoimmune disorders, and diabetes. The results include targeted suggestions for addressing patient concerns. The Vancouver-based “healthy longevity” company launched its $1,100 test in Canada in 2023 and is now available in the U.S. market through a partnership with lab-testing company HealthQuest Esoterics. It raised a $5 million Series A in August, bringing total funding to $29 million. Saucony For giving running shoes a “non-Newtonian” bounce Saucony’s latest technological advance in footwear engineering sounds more like an advance in quantum engineering: Its new proprietary IncrediRUN foam exhibits “non-Newtonian behavior.” It softens under light impact and stiffens under force, offering significant improvements in cushioning, energy return, and durability compared to the three main foams used in most running footwear. The material’s responsiveness springs from its novel polyester elastomer (TPEE) and Saucony’s advanced foaming process. Fine-tuned through mechanical testing, athlete feedback, and material engineering in Saucony’s Human Performance and Innovation Lab, IncrediRUN debuted in Saucony’s Endorphin line of training shoes in March 2025. The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2025. Read more about the winners across all categories and the methodology behind the selection process. View the full article

Our honorees in the new tech visionaries category are executives who applied new thinking to pressing problems. One is working to take cellular broadband places it’s never gone before. Another aims to make the tech industry less dependent on the risky business of mining rare earth materials. And the third is applying AI to the thorny challenge of defending against ever-smarter missiles and drones. Abel Avellan, CEO, AST SpaceMobile For sending cellular broadband to space Founded in 2017 by chairman and CEO Abel Avellan, AST SpaceMobile has launched six of its BlueBird satellites into low Earth orbit, with plans to have 60 more in orbit by the end of 2026. The goal is to deliver the world’s first satellite-based cellular 4G/5G broadband to unmodified smartphones, soaring past the technological limitations that have kept reliable high-speed cellular delivered through other means from reaching nearly half the world’s population. Under Avellan’s leadership, the company has signed more than 50 wireless providers as strategic partners and raised $2 billion-plus from investors such as AT&T, Google, Rakuten, Verizon, and Vodafone. Ahmad Ghahreman, Cyclic Materials For giving rare earth materials a new lease on life Rare earth materials such as neodymium and dysprosium are critical to everything from consumer electronics to data centers to energy production. But mining them is saddled with issues relating to geopolitics (China dominates the market), human rights, and climate change. Cyclic Materials CEO and cofounder Ahmad Ghahreman oversaw the invention of CC360, a process that recycles these materials—99% of which currently go to landfill—from disk drives. Among those working to help the company commercialize its technology are Amazon, BMW, Hitachi, and Microsoft, all of which participated in its $55 million Series B funding round. Amy Gilliland, General Dynamics Information Technology For using AI to defend against missiles and drones An $8.5 billion unit of defense giant General Dynamics, GDIT is led by president Amy Gilliland. The company worked with Amazon Web Services to develop an AI platform for the U.S. Department of Defense called Defense Operations Grid-Mesh Accelerator, or DOGMA. It helps protect against attacks by highly maneuverable missiles and drones by ingesting data from a network of sensors, analyzing it, and notifying the right operators on the ground—all swiftly enough to evade any attempts to jam communications systems. During tests at the DoD’s Technology Readiness Experimentation (T-REX) event in 2024, DOGMA reduced the time necessary to make decisions from 30 minutes to 30 seconds. The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2025. Read more about the winners across all categories and the methodology behind the selection process. View the full article

After federal funding for renewables evaporated this year, the future path of the energy sector has been unclear. But even in uncertain times, companies are advancing the technology needed to push for a clean-energy transition—while also accommodating for a new grid that needs to keep up with the huge power demands of the wave of data centers coming online. From new battery tech to all-day solar power to better ways to track emissions and more, these innovations can help see the sector through this precarious period. Exowatt For generating solar power even when the sun isn’t shining Exowatt’s P3 unit is a power plant in a 40-foot-long shipping container. The unit uses solar energy to heat a thermal battery—essentially a very hot piece of clay—that can then provide consistent power from solar even at night. The modular design will allow a series of P3 units to be quickly deployed to power new data centers without overwhelming the existing grid and needs no rare earth materials like lithium to operate. The company has raised $70 million so far from investors including Andreessen Horowitz and Open AI’s CEO Sam Altman. General Motors For rolling out a new kind of battery Lithium batteries may only have one element in the name, but they also require quite a bit of nickel and cobalt, two rare earth elements that have expensive (and sometimes ethically fraught) supply chains. Researchers at General Motors say they have recently made a breakthrough with a new kind of lithium-manganese rich (LMR) battery, which uses cheap and abundant manganese. Besides solving supply chain and cost issues, the automaker’s innovation has also addressed old issues with LMRs losing charge quickly. The company is planning to roll out its new formulation batteries by 2028, and it says they could boost the range of its EVs to 400 miles per charge. Greenlane For building the electric truck charging infrastructure network As the electrification wave comes for freight trucking fleets, the truck stop must also evolve, providing fast charging for large vehicles on highways around the country. Greenlane, a company founded with backing from Daimler Truck North America and BlackRock’s climate fund, aims for widespread deployment of its Greenlane High-Speed Charging System, with 12 pull-through lane 400 kW chargers. The company opened its flagship charging station on I-15 Southern California in April 2025 and plans to expand to electrify the entire highway from Los Angeles to Las Vegas. Persefoni For powering climate reporting, with some help from AI As governments around the world demand more climate disclosure from companies, the time and money it takes to keep track of all the data can be daunting, especially for small and medium-sized businesses. Climate accounting software company Persefoni’s newest Pro offering helps those companies collect and report that data—even Scope 3 emissions, involving emissions from suppliers and customers, which are notoriously hard to track. To solve the problem, the software’s Scope 3 Data Exchange lets companies request emissions data directly from their suppliers. It also uses generative AI to help generate reports and ensure compliance with major emissions standards around the world. In its first year available, the software amassed more than 6,000 users. X, the Moonshot Factory For building the first map of the entire grid There is currently no working map of the world’s electric grid. Tapestry, a project from Google’s X, the Moonshot Factory, is working to change that. The effort—now active in the U.S., U.K., Chile, South Africa, New Zealand, and Australia, is combining AI-powered inspection and advanced simulation tools to help operators plan, maintain, and scale the grid. Its two products use machine learning to help quickly inspect grids and solve problems and to plan for future grid expansion. This year, the company began partnering with Chinese operators. It’s also helping PJM—the largest grid operator in North America—model ways to bring renewable sources online faster. The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2025. Read more about the winners across all categories and the methodology behind the selection process. View the full article

The space and telecom industries can look increasingly intertwined as satellite roaming—today for messages, tomorrow for data—becomes a standard feature. But while wireless services have the luxury of iterating as often as they want once they start signing up customers, space startups have to take things one launch at a time. Eascra Biotech For making the International Space Station a pharmaceutical research lab Eascra has one of the most interesting worksites of any of this year’s honorees: the International Space Station, where astronauts conduct research on developing nanoparticles to treat cancer and other maladies. Growing these materials in microgravity yields more uniform particles that can store mRNA drugs at room temperature—not the subzero conditions mRNA medication usually requires. Impulse Space For bringing the space tug concept closer to commercial reality Founded by SpaceX veteran Tom Mueller, Impulse Space helps launch providers take their payloads farther with its Helios kick stage—which can send a satellite from low Earth orbit to geostationary orbit in a day—and its smaller Mira space tug. The company has raised $300 million and has won contracts from NASA and the Space Force to develop its platforms further. MobileX For leveraging AI to resell wireless service as cheaply as possible Mobile virtual network operators (MVNOs) can look alike, especially when so many of them are now properties of the big three wireless carriers. But MobileX, which resells Verizon’s network, stands out for extremely low rates, starting at $3.48 a month and maxing out at $24.88. Its secret weapon? The company applies AI to analyze patterns of use to match customers with the most affordable plan that fits. US Mobile For bringing choice and flexibility to the wireless resale market US Mobile has experienced a rocket-launch trajectory since its 2016 debut—in 2025, it made its first appearance on Consumer Reports’ survey of subscribers at the top of that list. Unlike most MVNOs, it resells each of the big three wireless carriers—under cutesy names (“Dark Star” means AT&T, “Light Speed” T-Mobile, “Warp” Verizon). It lets subscribers choose among the three on the fly with its Teleport feature, tapping the best coverage for their everyday whereabouts. Varda For making pharmaceutical materials in space Manufacturing in microgravity has been a part of humanity’s imagined off-world future for decades, but Varda has finally done it by building its own uncrewed satellite and reentry capsule. That allows life-sciences customers to generate crystals for pharmaceutical uses that are more uniform than what gravity would allow. Following successful landings by Varda’s capsule, in June the company launched its first mission built on an in-house satellite bus; a month later, it announced a $187 million fundraising round. The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2025. Read more about the winners across all categories and the methodology behind the selection process. View the full article

Let’s face it: The fact that AI is amazing is no longer all that … amazing. The technology is under ever-increasing pressure to prove its real-world value for consumers, businesses, and researchers in specific contexts. These honorees in the applied AI category are proving AI’s worth for fashion advice, pharmaceutical advice, coding, and much more. Alta For bringing AI to personal styling For people who lack style expertise or time for outfit planning, the task of choosing what to wear can be a daily frustration. Alta built a personal AI stylist app that generates outfits based on users’ actual wardrobes, lifestyle, budget, weather, and upcoming events—whether they’re dressing for a board meeting in Switzerland or a summer wedding in Napa. Users can upload their wardrobe or let the app automatically scrape their fashion buys from receipts and photos, then receive personalized suggestions they can visualize on customized avatars. The style agent learns each user’s unique style preferences, getting smarter with use. Alta raised $11 million from top-tier investors including Menlo Ventures, secured a partnership with the Council of Fashion Designers of America that gives CFDA members access to its AI platform, and partnered with tidiness guru Marie Kondo to offer premium closet organization services. Ambience Healthcare For freeing doctors from documentation drudgery Caregivers spend countless hours every week filling out patient charts—time that could be spent on actual patient care. Ambience Healthcare has developed an AI platform that listens in on patient–physician conversations in the exam room via a phone app and automatically generates comprehensive medical notes. The AI then creates a draft summary of the notes—complete with suggested ICD-10 and CPT codes—that the caregiver can review, edit, and sign. The system integrates with major electronic health record systems such as Epic and Oracle Cerner. Cleveland Clinic is now implementing Ambient’s solution after doing a comprehensive head-to-head test of “AI scribe” solutions for healthcare, testing five leading solutions with hundreds of clinicians and across more than 80 medical specialties over six months. Bolt For bringing vibe coding to the browser Building web and mobile applications traditionally requires multiple development teams, technical infrastructure, and months of coding. Among the highest-profile entrants in the new category of vibe coding tools, Bolt changes app creation by letting users describe what they want to build in natural language then instantly generating code. The platform handles front-end and back-end development logistics as well as hosting without complex setups or cloud services. After launching with a single tweet in October 2024, Bolt’s business grew quickly, scaling from zero to $40 million annualized recurring revenue in just four months. The company secured $83.5 million in Series B funding at a $700 million valuation. Cradle For accelerating protein engineering with AI Traditional protein engineering is slow, expensive, and unpredictable, hindering progress in pharmaceuticals, materials science, and biotechnology. Cradle harnesses generative AI to accelerate protein design by creating entirely new protein sequences tailored for specific functions. This distinguishes Cradle from DeepMind’s AlphaFold, which predicts the structures of proteins. The platform reduces experimental iterations, improves success rates, and uncovers novel structures that were previously out of reach for developing therapeutics, sustainable materials, and industrial enzymes. In 2025, Cradle expanded to 21 customers, including Johnson & Johnson and Novo Nordisk, demonstrating real-world validation of its technology in high-stakes drug development. GitHub For making AI coding collaborative In the age of AI coding assistants, developers are under pressure to ship code faster while maintaining quality, often forcing a choice between speed and control. Since becoming the first widely used coding assistant, GitHub Copilot has evolved beyond simple code suggestions into a tool for creating entire new software features and functions. But GitHub and its parent company, Microsoft, have taken a distinct approach to developing Copilot: Rather than pursuing full automation, GitHub designed Copilot to leave the human coder firmly in control. The assistant works like a good human teammate, GitHub says, showing its work and asking for review before anything ships. GitHub says Copilot’s user base quadrupled year over year in 2025 and now includes 15 million developers and more than 77,000 organizations. Google For applying secure open models to healthcare Healthcare AI developers often struggle to build medical applications because they can’t access specialized models that handle sensitive data securely. Google’s MedGemma family offers the first open multi-modal models trained specifically for medical text and image comprehension, enabling developers to keep sensitive data within private environments while adapting models for specific use cases. The models range from 4 billion to 27 billion parameters, small enough to fine-tune and serve on a single GPU, with the 27B version featuring clinical reasoning capabilities useful for patient triage and differential diagnosis. MedGemma achieved over 150,000 downloads from more than 10,000 developers in its first month, with the community creating and sharing more than 100 fine-tuned versions on Hugging Face. Hebbia For extracting insights from financial document chaos While making critical risk assessments and investment decisions, financial services professionals often must rely on unstructured data contained within numerous documents. Hebbia custom-built a generative AI solution for finance that lets users more quickly capture insights from millions of diverse documents located all around the organization. An investment banker might use Hebbia to generate conclusions from a call transcript, or someone in private equity could use it to identify potential risk factors before signing an investment deal. Hebbia can also summarize external documents such as market reports and credit agreements. The platform’s versatility across multiple financial tasks helped Hebbia secure a $130 million funding round led by Andreessen Horowitz. Hebbia says it now serves 30% of all U.S. asset managers and has processed over 100 million documents, or 10 times more than its nearest competitors. Jigsaw For making sense of massive public conversations Governments and other organizations struggle to synthesize thousands of public comments on civic issues. Traditional analysis methods can take months to deliver results, leaving feedback loops open too long for meaningful action. Jigsaw, an incubator inside Google, used Google’s Gemini AI model to create a toolkit called Sensemaker. It identifies key topics and themes from large-scale online conversations, allowing users to understand thousands of perspectives within minutes while preserving discussion richness. The technology surfaces patterns, areas of agreement and disagreement, and actionable insights from data that was previously impossible to process at scale. In its pilot with Bowling Green, Kentucky’s BG2050 initiative—a project addressing the expected doubling of the city’s population by 2050—local leaders used Sensemaker to analyze a four-week online conversation, enabling them to draw insights from community input that would have otherwise remained buried in unstructured data. Pando For taming logistics chaos Global logistics has faced relentless disruption in recent years, from the Russia–Ukraine war to sourcing upheavals caused by the The President administration’s tariffs. Pando recently added an AI agent called Pi to its platform for managing complexity and risk. The agent is powered by proprietary logistics language models and can automate operations such as requesting shipment from a carrier, invoice validation, and anomaly detection. The agent recommends actions, explains its logic, and executes tasks after confirmation. Within weeks of Pi’s launch, a number of Fortune 50 brands, including Meta, onboarded Pando, demonstrating the platform’s ability to handle the complexities of enterprise-scale logistics. Samsung Electronics America For making AI feel natural on mobile devices Smartphone AI features can sometimes feel gimmicky or disconnected from real-life workflows, creating barriers and distractions rather than enhancing the user experience. The features not only have to be useful but they have to show up at the right times and right places in the UX. Samsung did it right with Galaxy AI, which it integrated directly into its smartphones’ Android operating system to provide context-aware, personalized experiences through multimodal AI agents that can interpret text, speech, images, and videos. Users can perform multistep actions across apps, using plain language to get directions, send messages, and update calendars simultaneously. The Galaxy S25 series implementation has earned widespread praise from tech reviewers—Tom’s Guide remarked, “The S25 Ultra is packed with smarter AI features I wish the iPhone 16 Pro Max had.” Sonar For ensuring AI-generated code meets enterprise standards AI coding assistants have proved that they can accelerate software development, but as the tools have evolved to touch more and more parts of an organization’s code, they also can introduce hard-to-detect flaws that show up as bugs later on. Sonar’s platform uses AI to scan software for quality problems then fixes them. Fixes are informed by the platform’s deep experience—it analyzes more than 300 billion lines of code every day, the company says. The platform’s AI Code Assurance mode provides stricter quality gates for AI-generated code, while AI CodeFix generates contextual repair suggestions based on precise analysis findings rather than generic recommendations. Sonar says that 70% of developers rate its fix quality at 4 or 5 out of 5. Typeface For generating end-to-end marketing campaigns Marketers too often must choose between AI-generated content that’s generic or that is off-brand. Typeface created the first AI marketing platform that orchestrates the entire content process from brief to finished campaign. While the Typeface integrates with more than 30 AI models, the company trains custom models that maintain brand voice, tone, and visual identity. The platform’s Brand Hub is a searchable AI content repository that enforces compliance and governance guidelines. Spaces provides a visual workspace where marketers create personalized emails, ads, web pages, and videos without becoming prompt engineers. Typeface secured major enterprise deals with Fortune 100 companies, including Asics, in 2025. Vermillio For arming creators against deepfakes Vermillio makes a new kind of IP protection platform that identifies the unauthorized use of a person’s likeness or voice in synthetic or AI-generated audio and video. Traditional content protection systems can fail to detect AI-generated content derived from a face or voice because they’re better at detecting exact replicas of the original content. Vermillio’s TraceID technology assigns digital signatures to every fragment of intellectual property, creating “soft bindings” through digital hashes and fingerprints that aren’t easily removed by generative AI models. Vermillio’s platform tracks IP usage across images, text, audio, and video, ensuring proper attribution and compensation while detecting harmful deepfakes. Vermillio says it had more than 130,000 pieces of unauthorized AI-generated content taken down in Q4 2024 alone. In March 2025 the company closed a $16 million Series A round led by Sony Music Entertainment and including Disney and Warner Music Group. Warp For reimagining the terminal for the AI age Developers have long preferred to control their machines via a command-line terminal because it’s more direct and precise. Unfortunately, the terminal, which was born in the 1970s, hasn’t kept up with new developments in AI-powered coding assistants and agents. So Warp built a modern, AI‐powered terminal for developers called an Agentic Development Environment (ADE). The environment maintains the command line’s power while adding support for natural-language-based AI coding assistance and the ability to manage multiple AI agents. The result is a platform where AI agents have more visibility into the code base so that they can detect potential problems and offer ways of fixing them. Warp says it has seen 90% year-over-year growth in its user base, with 600,000 active developers now using the platform, including 16,000 engineering teams. The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2025. Read more about the winners across all categories and the methodology behind the selection process. View the full article

These companies aren’t big—but they’re bringing new ideas to some thorny challenges. Kids have been crafting with cardboard for decades, but Chompshop has found a way to make it safer and more fun. Online clothes shopping has long been a bit hit or miss, but Veesual’s found a way to maximize the number of hits. And GoodMaps and Overture Maps have tackled longstanding navigation problems. Chompshop For making kids’ cardboard crafts safer and more fun Cheap, abundant cardboard is great for kids’ art and science projects, but it’s often hard to trim with scissors. Chompshop has developed a kid-safe power tool specifically designed for this versatile material. While it’s called a ChompSaw and looks like a table saw, it’s based on a protected hole-punch mechanism that keeps children’s hands safe. After a successful Kickstarter campaign and Shark Tank appearance, the company has sold more than 17,000 ChompSaws since its October 2024 launch. GoodMaps For helping people navigate indoors as easily as on the road Navigating indoor spaces like airports and museums can be complicated, especially as GPS-style assistance is typically not available. GoodMaps developed an AI-powered system letting venue operators scan and map facilities using just an iPhone. A GoodMaps Studio application lets operators customize maps and guidance. The platform has been embraced by airports from London Heathrow to Dallas Fort Worth International, as well as institutions such as Ohio’s Armstrong Air & Space Museum. Overture Maps For setting the standard for unifying messy map data A collaborative open-data initiative founded by Amazon, Meta, Microsoft, and TomTom and embraced by other big names such as Esri, Tripadvisor, and Uber, Overture Maps built an identification system for more than 3 billion global locations that’s as unique as the human fingerprint. Its Global Entity Reference System makes it clear that “Tom’s Diner” is (or isn’t) the same location as “Tom’s Restaurant,” whichever app or dataset you’re working with. GERS can also benefit governments tracking data like car accidents and serve autonomous cars needing clear navigational information. Veesual For letting online shoppers get an accurate view before they buy clothes Online clothes shopping is notoriously hit-or-miss. While some companies have developed virtual AI models, they can distort the look of garments and the body itself. Veesual created an alternative, physics-informed approach, displaying clothes as they’d actually appear on a range of models and letting customers see how they’ll look on someone like them. The startup has worked with brands such as Eileen Fisher, Lululemon, and Adore Me, and it raised a $7.5 million seed round in 2024. The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2025. Read more about the winners across all categories and the methodology behind the selection process. View the full article