Latest AI News
Meta to Axe 10% of Workforce as It Shifts 7,000 Employees to AI Teams: Report
The changes are part of a broader overhaul at Meta as the company ramps up spending on AI infrastructure and products.
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Google I/O 2026 Starts Today: How to Watch Keynote Live and What to Expect
Google I/O 2026 is all set to begin today (May 19), and the tech giant is expected to make several announcements about software features coming to its services over the coming months. In recent weeks, the Mountain View-based tech giant has provided us with a glimpse of what's to come, courtesy of The Android Show. The 2026 edition of the developer conference is expected to outline Google's roadmap across artificial intelligence (AI), Android, and developer tools.
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SandboxAQ brings its drug discovery models to Claude — no PhD in computing required
Drug discovery is one of the most expensive pursuits in modern industry. Finding a single viable molecule can take a decade and cost billions, and most candidates still don’t make it. A generation of AI startups has promised to fix that — most have made the problem less painful for researchers, who are already technically sophisticated enough to use the tools. But SandboxAQ thinks the bottleneck isn’t the models. It’s the interface. The company has teamed up with Anthropic to integrate its scientific AI models directly into Claude — putting powerful drug discovery and materials science tools behind a conversational interface that requires no specialized computing infrastructure to use. Founded roughly five years ago as an Alphabet spinout, SandboxAQ counts Eric Schmidt, Google’s former CEO, as its chairman. The company, which has raisedmore than $950 million from investors, has built out a number of different business lines, includinga cybersecurity business. One of the more unique things SandboxAQ does, however, is produce large quantitative models, or LQMs. These proprietary models are “physics-grounded,” meaning they’re built on the rules of the physical world rather than patterns in text. They can run quantum chemistry calculations and simulate both molecular dynamics and microkinetics, the study of how chemical reactions unfold at the molecular level. That matters because it tells researchers how candidate molecules are likely to behave before anyone sets foot in a lab. “Trained on real-world lab data and scientific equations, LQMs are AI models engineered for the quantitative economy, a $50+ trillion sector spanning biopharma, financial services, energy, and advanced materials,” the company said in a news release that strongly suggests Sandbox AQ isn’t building another chatbot or code assistant — it’s chasing the economy that AI is supposed to transform. Chai DiscoveryandIsomorphic Labs— both well-funded bets on better models — have focused on the science. SandboxAQ is focused on who can actually use it. “For the first time, we have a frontier [quantitative] model on a frontier LLM that someone can access in natural language,” Nadia Harhen, SandboxAQ’s general manager of AI simulation, told TechCrunch. Previously, users of SandboxAQ’s LQMs would have had to provide their own digital infrastructure to run the models. SandboxAQ’s customers tend to be computational scientists, research scientists, or experimentalists. Generally, these people work at large pharmaceutical or industrial companies and are searching for new materials that can become marketable products. “Our customers come to us because they’ve tried all the other software out there, and the complexity of their problem is such that it didn’t work or didn’t yield positive results for them when that translation went to take place in the real world,” said Harhen.
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Elon Musk has lost his lawsuit against Sam Altman and OpenAI
Elon Musk’s claim that he was mistreated by his OpenAI co-founders failed after nine California jurors returned a unanimous verdict that his lawsuits had been filed too late. Musk accused Sam Altman, Greg Brockman, OpenAI, and Microsoft of “stealing a charity” by creating a for-profit affiliate of the frontier AI lab. Jurors, however, found that any harms that Musk may have suffered came before the deadline for filing his claims under the law. While the trial delved deeply into the melodramatic history of OpenAI and featured testimony from leading figures in Silicon Valley, it ultimately turned onfairly narrow questionsof the law. The trial focused on whether and when Altman and the other defendants had made and broken promises to Musk, but his case failed to convince jurors that he had a valid claim. In particular, OpenAI had advanceda statute of limitations defense, which sought to prove that any harms Musk sought to litigate had taken place before 2021. (The specific date varied by the charge: before August 5, 2021, for the first count; August 5, 2022, for the second count; and November 14, 2021, for the third count.) Ultimately, the jury found that argument persuasive, which made for a short deliberation period. “There was a substantial amount of evidence to support the jury’s finding, which is why I was prepared to dismiss on the spot,” Judge Yvonne Gonzalez Rogers said after the verdict was delivered. The end of the case means that one major threat to OpenAI — a possible restructuring — is now off the table ahead of its reported IPO. “It did not take [the jury] two hours to conclude … that Mr. Musk’s lawsuit is nothing more than an after-the-fact contrivance that bears no relationship to reality,” OpenAI’s lead attorney, Bill Savitt, said after the verdict. “They kicked it exactly where it belongs — just to the side. This lawsuit is a hypocritical attempt to sabotage a competitor.” Microsoft, which Musk sued for aiding and abetting OpenAI’s alleged breach of charitable trust, welcomed the verdict. A spokesperson for the company said it “remained committed to our work with OpenAI to advance and scale AI for people and organizations around the world.” The verdict came in the middle of a hearing to determine the potential damages to Musk if the verdict had gone the other way. While that discussion is moot for now, the judge appeared unconvinced by the analogy Musk’s lawyers drew between his charitable contributions and investments in a for-profit startup. “Your analysis seems to be devoid of connection to the underlying facts,” she told Dr. C. Paul Wazzan, the expert who came up with Musk’s estimate of OpenAI and Microsoft’s wrongful gains at his expense — some $78.8 billion to $135 billion. In a tweet after the ruling, Musk appeared to take the procedural grounds of the dismissal as a moral victory. “There is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity. The only question is WHEN they did it!” Musk wrote. “I will be filing an appeal with the Ninth Circuit, because creating a precedent to loot charities is incredibly destructive to charitable giving in America.” Reached for comment by TechCrunch, Musk’s lead counsel, Marc Toberoff, said, “One word: Appeal.”
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Anthropic has acquired the dev tools startup used by OpenAI, Google, and Cloudflare
Anthropic announced Monday it has acquired Stainless, a startup founded by former Stripe engineer Alex Rattray whose software is widely used by rival AI labs, including OpenAI and Google. Anthropic didn’t disclose terms of the deal. However, The Informationreportedlast week that the company was in talks to acquire Stainless, which is backed by Sequoia Capital and Andreessen Horowitz, for more than $300 million. The acquisition will take a key infrastructure supplier out of the hands of Anthropic’s competitors. The company told TechCrunch it will wind downall hosted Stainless products, including its SDK generator. An Anthropic spokesperson said Stainless customers will still own the SDKs they’ve generated to date and have full rights to modify and extend them however they wish. The New York-based startup, founded in 2022, rose to prominence in the emerging AI industry for automating the creation and maintenance of software development kits, or SDKs — the libraries developers use to interact with APIs. Rattraydeveloped softwarethat could take API specifications and turn them into production-ready SDKs across multiple programming languages, including Python, TypeScript, Kotlin, Go, and Java. It became a popular tool because the platform automatically updates the SDKs as APIs change and eliminated the time-consuming process of manually maintaining them. The technology is particularly valuable tocompanieslike Anthropic, OpenAI, Google, Replicate, Runway, and Cloudflare that are building AI agents that can connect to external software and complete tasks on behalf of users. Stainless’s SDK tools are an easy way to build and maintain those connections — but going forward, the tools will only be available to Anthropic, not its competitors. According to Anthropic, Stainless software has powered the generation of every official Anthropic SDK since the earliest days of its API. “I started Stainless because SDKs deserve as much care as the APIs they wrap,” Rattray saidin a press releaseposted Monday. “Anthropic was one of the first teams to bet on this with us. We have been watching what developers have built on Claude over the last few years, which made bringing our teams together an easy decision. The team gets to keep doing the work we love, on the platform where it matters most.”
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Amazon’s new Alexa+ powered feature can generate podcast episodes
Amazonannouncedthe latest update to Alexa+ on Monday: the ability to generate podcast episodes on demand. The new feature, called “Alexa Podcasts,” is rolling out to customers in the U.S. today. Amazon describes the capability as a way to “turn any topic you’re curious about into a podcast episode, ready in minutes.” To use the feature, all users have to do is ask Alexa+ to create a podcast about a topic they’re interested in. Users don’t need to upload documents, write scripts, or plan anything ahead of time. Instead, Alexa+ researches the request, gathers information, and generates a quick overview of what the episode will cover. From there, users can tweak things like the length, tone, and focus of the episode. Once finalized, Alexa+ uses AI-generated host voices to narrate the podcast. When the episode is ready, users get a notification through their Echo Show device and inside the Alexa app. Episodes are also saved in the app’s “Music” and “More” sections so they can be replayed later. The feature is another example of how Amazon is trying to turn Alexa+ into more than just a voice assistant. Instead of only answering questions or controlling smart home devices, Alexa+ is starting to act more like a personalized AI content creator. At the same time, the launch is likely to spark some debate. AI-generated voices and automated content continue to raise questions around ethics, accuracy, and the future of traditional creators. There are also concerns about how reliable AI-generated podcasts will be, especially when covering news or complex topics. Amazon emphasized its partnerships with major news organizations to improve content accuracy and reliability. The company says Alexa+ can access real-time information through agreements with outlets including the Associated Press, Reuters, The Washington Post, Time, Forbes, Business Insider, Politico, USA Today, Condé Nast, Hearst, and Vox Media, alongside more than 200 local newspapers across the U.S. Beyond podcasts, Amazon says it is exploring additional forms of personalized AI audio, including custom news briefings and content generated from users’ own documents and shared information.
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Mustafa Suleyman's White-Collar Doomsday is Just Tech-Bro Hype
When Microsoft's AI chief Mustafa Suleyman predicted the near-total automation of white-collar work, he set off a debate that cuts to the heart of India's IT economy.
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YouTube’s Likeness Detection Tool Is Now Available to All Adult Creators
YouTube is finally ready to release its Likeness Detection tool to all adult creators on the platform. After first announcing it in 2024, the company has also expanded its access to users. Last year, a select group of content creators received the tool, and in March this year, the streaming giant opened the deepfake spotting tool to government officials and journalists. With a wider rollout just a few weeks away, the artificial intelligence (AI) tool will allow creators to learn about their deepfakes being circulated on the platform. They will also be able to report such content as well.
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South Korea’s LetinAR is building optics behind AI glasses
Imagine you’re riding a motorcycle at 160 kilometers per hour when an arrow appears, floating on the road ahead, telling you exactly where to turn. No phone, no dashboard. Just your helmet, and a lens the size of a thumbnail. This is not a concept video. It’s heading to European roads as early as this year. And it’s one early glimpse of where smart glasses are heading. Over the past few years, Big Tech has been quietly (and not so quietly) placing its bets. Meta has been selling AI-enabledRay-Ban glasses since 2023, Google isbuilding Android XR, andApple is expected to enter the market. Last week, Samsung wasreportedlyset to unveil its first AI-capable smart glasses, co-designed with Gentle Monster, at a Galaxy Unpacked event in London this July. China’sHuawei,Alibaba,Xiaomiand others are all moving too. The numbers reflect the momentum. Global AI glasses shipments surged to 8.7 million units in 2025, up more than 300% from the prior year, and analysts project that figure will cross 15 million this year,per Omdia. Suppliers and component makers of AI-powered smartglasses are also positioning themselves for what comes next. One of the companies, a South Korean startup calledLetinAR, has spent the last decade building the optical technology that could make all of this actually wearable. The LG Electronics-backed startup just secured $18.5 million from Korea Development Bank and the South Korean retail giant’s venture arm, Lotte Ventures, among others, ahead of its planned 2027 IPO in South Korea. Its previous investor,LG Electronics, has since begun developing its own AI smart glasses, according to alocal mediareport, which is a sign of how seriously South Korea’s largest consumer electronics company takes the category. CEO Jaehyeok Kim and CTO Jeonghun Ha, who have been friends since high school, founded LetinAR together in 2016. LetinAR doesn't make the glasses. It makes the part that makes the glasses work. The optical module, the tiny lens component that projects images into your field of vision, is what determines whether a pair of smart glasses feels like a sci-fi headset or something you'd actually wear to work, Ha told TechCrunch. It has to be light, thin, and power-efficient, while still delivering a sharp, clear image. Getting all of that right in a single component, small enough to fit inside a normal-looking frame, is the central engineering challenge of the entire industry. That's what LetinAR is building. “We see AI glasses as that next platform,” Kim said. “And the optical module is the hardest part to get right as AI glasses makers will need a lens that is thinner, lighter, and more power-efficient than what exists today.” The co-founders said LetineAR wants to be the company those glasses makers call. The company calls its technology PinTILT: a way of arranging tiny optical elements inside a lens so that light is directed precisely where it needs to go, into the user's eye, rather than scattered in every direction. Think of a TV. It broadcasts light across an entire room, but only the light that actually reaches your eyes matters. Most existing smart lens technologies, particularly a dominant approach calledwaveguide, work a bit like that TV, splitting and spreading light across the full lens to create a wide image. The result is a thin lens, but an inefficient one. A lot of light gets thrown away before it ever reaches the eye, which means dimmer images and, critically, a battery that drains fast, Ha explained. The alternative, a mirror-based approach known asbirdbath, delivers light more directly to the eye, but the structure is bulky, making it nearly impossible to fit inside something that looks like a normal pair of glasses. PinTILT sidesteps that tradeoff, Ha said. By focusing only on the light that can actually enter the eye and carefully engineering the angle of each tiny element inside the lens, LetinAR claims it can produce a brighter image in a thinner, lighter form factor, using less power. In a category where every gram and every hour of battery life matters, that's the problem the entire industry has been trying to solve. In the space, there are a number of peers likeWaveOptics,DigiLensandLumus. Its modules are already shipping. LetinAR counts Japan's NTT QONOQ Devices and Dynabook, formerly known as Toshiba Client Solutions, among its customers, giving the company real manufacturing experience at scale. It is in talks with Big Tech companies on R&D of next-generation AI glasses, though it declined to name them. One of LetinAR's most demanding customers isAegis Rider, a Swiss deeptech company spun out of ETH Zurich's Computer Vision Lab. Aegis Rider is building an AI-powered AR helmet that displays navigation, speed, and safety alerts directly in a motorcycle rider's field of vision, not floating on the visor, but anchored to the road itself, as if the information is physically painted on the world ahead. LetinAR's module is inside the helmet. Aegis Rider is targeting the EU and Swiss markets in 2026. The latest funding, which brings the total raised to $41.7 million, will go toward scale-up as the AI glasses market shifts from early adopters to mass production, said Kim, adding that hardware devices, such as AI glasses, are the next layer that will bring AI into everyday life.
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Ex-Genpact VP Megha Sinha, Sr VP Sreekanth Menon Launch Book on Enterprise AI Adoption Challenges
The authors say enterprise AI adoption often breaks down due to low trust, unclear accountability, and workflows that were never redesigned for how employees actually work.
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Can AI Prevent Enterprise System Failures? A Bengaluru Startup Thinks So
Kusho AI is helping enterprises automate software testing and reliability using AI, moving from manual workflows to large-scale simulation.
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Ashok Jhunjhunwala Thinks India Must Solve Its Hardest Problems First
Ashok Jhunjhunwala, now in his seventies, shows little interest in slowing down.
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