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Lovable has crossed annual run-rate revenue of $600 million, the company’s co-founder Fabian Hedin said at the HumanX summit in Amsterdam on Thursday. The vibe-coding platform in June said that numberwas around $500 million. Hedin said the startup has focused on growing its enterprise business, and claimed that two-thirds of Fortune 500 companies are now using its product. Its customers include Microsoft, Nvidia, and Deutsche Telekom. He also said apps created by users on the platform are together attracting nearly a billion views per month. “You can use these tools [like Codex or Claude code] to output code. The difference is that Lovable does not output code. The output is a product, and increasingly so, a business. We do a lot of things around hosting, deployment, and scaling apps. We have close to a billion visits per month to the apps that we’ve created, which is an order of magnitude more than Lovable itself,” he said. The company has raised over $700 million in two rounds just eight months apart. Last December, it raised $300 million from Menlo Ventures and CapitalG at a $6.6 billion valuation. Then, this August, the startup raised$400 millionfrom Menlo Ventures and the Scaleup Europe Fund at a $13.3 billion valuation.
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An AI chatbot can give you a bad answer. An AI system controlling an aircraft, vehicle, or robot can create an entirely different kind of problem. When artificial intelligence moves into the physical world, a mistake can ground an aircraft, cause a vehicle crash, or compromise a mission. So how do you know when an autonomous system is actually ready to leave the lab? AtTechCrunch Disrupt 2026, Shield AI’s chief technology officer Nathan Michael, Waabi founder and CEO Raquel Urtasun, and General Motors’ Director of Robotics Strategy Mikell Taylor will tackle that question on the Real World AI Stage in “Building AI Systems When Failure Is Not an Option.” The conversation will get into the work behind deploying AI where the stakes are high: creating a safety culture, testing and validating systems, navigating regulatory hurdles, and earning trust. Building AI for the physical world? Tomorrow is the last day to save up to $200 on your Disrupt pass.Secure your ticket by September 25 at 11:59 p.m. PTand hear from three leaders working where failure has real-world consequences. Prices will increase after September 25 at 11:59 p.m. PT. AtShield AI,Nathan Michaelleads the development and deployment of Hivemind, the company’s platform-agnostic mission autonomy software. His background spans AI, control, perception, and multi-robot systems, including years at Carnegie Mellon University’s Robotics Institute, where he directed the Resilient Intelligent Systems Lab. That expertise is being put to work on technology designed for some of AI’s highest-stakes environments. In February, Hivemind was selected as an autonomy provider for the U.S. Air Force’s Collaborative Combat Aircraft drone prototype program. A month later, Shield AI announced $1.5 billion in Series G funding at a $12.7 billion post-money valuation. At Disrupt, Michael brings the perspective of an AI leader developing autonomous systems for environments where performance has to be matched by assurance. What does it take to trust AI with a mission?Secure your Disrupt passbefore September 25 at 11:59 p.m. PT, and hear Nathan Michael’s perspective on developing autonomy for high-stakes environments. Raquel Urtasunhas spent 25 years working in AI and autonomous vehicles. Before foundingWaabi, she served as chief scientist and head of R&D at Uber ATG. She’s also a professor of computer science at the University of Toronto, co-founded the Vector Institute for AI, and has published more than 200 AI papers. Now Waabi is preparing to take its autonomous-driving technology much further. In January, the company raised $1 billion and announced a partnership with Uber to support the deployment of 25,000 or more Waabi Driver-powered robotaxis. Testing and validation are central to Waabi’s approach. Its Waabi World simulator trains, tests, and stress-tests the Waabi Driver in a virtual environment, and Urtasun has said the company’s autonomous trucks still need to be fully validated before driverless deployment. That puts one of the session’s central questions squarely in Urtasun’s wheelhouse: How do you determine when an AI system is ready to operate without a human behind the wheel? Want to hear how autonomous-driving leaders approach testing, validation, and deployment? Secure your Disrupt pass by September 25 at 11:59 p.m. PT tosave up to $200— and get a second pass for 50% off select ticket types. Mikell Taylorhas spent more than two decades building robots designed to do useful work. Today, she leads robotics strategy forGeneral Motors’ Autonomous Robotics Center. Previously, she led the Amazon Robotics team that developed Proteus, Amazon’s first autonomous mobile robot. Her robotics career started in a decidedly less industrial setting: She once built a robotic senior prom date. Since then, Taylor has worked on everything from autonomous underwater vehicles to industrial robotic systems, with a focus on robots that are practical, reliable, and able to work effectively around people. Taylor’s experience will shed light on a fundamental challenge facing real-world robotics: User experience and adoption need to be considered from the start, as part of both product design and deployment planning. That human element matters when AI-powered machines leave controlled demonstrations and enter workplaces where people have to depend on them. How do you build autonomous systems people can work with — and trust?Register for Disruptbefore September 25 at 11:59 p.m. PT to save up to $200 and to hear from leaders tackling those questions in the real world. Aircraft. Autonomous vehicles. Industrial robots. The environments may be different, but all three put the same question in sharp focus: When the consequences of failure are real, what does it take to deploy with confidence? For founders and technology leaders building autonomous systems, the session offers a chance to compare how leaders in defense, autonomous driving, and industrial robotics approach the decisions that stand between a promising system and one that’s ready for the real world. This session is one of 200+across six industry stages, roundtables, and breakouts atDisrupt, taking place October 13-15 at Moscone West in San Francisco. More than 10,000 founders, investors, operators, and tech leaders are expected, along with 250+ speakers and 300+ exhibiting startups. Beyond the agenda, matchmaking, dealmaking, and networking create more opportunities to make the connections that can move a company forward. When failure isn’t an option, “almost ready” isn’t enough. These are the last two days tosave up to $200 on your Disrupt pass. Secure your ticket by September 25 at 11:59 p.m. PT — and get a second pass for 50% off select ticket types.
With AI agents like Meta’s Muse and Instinct now able to make calls on users’ behalf, Google is now letting Gemini call businesses with a new feature called “Call for Me.” The feature will initially roll out to Pixel 11 owners who pay for a Gemini subscription in the U.S. It will also require the use of the beta version of Google’s Phone app for Android, as it’s still supposed to be an experiment. While Google has long offered calling features guided by AI, prior versions were limited in what they could do. With this update, Gemini will be able to share personal information that you approve as part of the calls it makes, which, the company says, will allow it to take a broader set of actions. In addition, Google says users will be able to follow the call as it happens and take over at any time. “Call for Me” will also use your own personal phone number to make calls, which will be dialed directly from your phone. Google says the AI can handle complex tasks, like calling a store to ask if a product is in stock, making a restaurant reservation, moving a scheduled appointment to a different date, or placing items on hold. The AI can call a business and introduce itself, navigate automated phone menus, wait on hold, and then handle the conversation on the other end. Meanwhile, users can watch how the call proceeds via a live transcript of the conversation. The launch builds on years of experiments with AI-assisted, automated calling technology at Google. Years ago, the company wowed people at its I/O developer conference when it demonstratedGoogle Assistant calling a salon to make a reservation, and even adding little “umm’s” and “ahh’s” to make the conversation seem natural. Last year, it rolled out “Ask for Me,” a feature that let Geminicall businesses on users’ behalfto inquire about things like pricing or services. People with Pixel smartphones have also had access to features like “Hold for Me” or “Talk to a Live Rep,” which can navigate phone trees, then automatically wait on hold until a real person comes to the line. Another option, “Direct My Call,” can display the numbers to navigate IVR systems. Google said it’s starting this experiment at a small scale because “real-world conversations are nuanced,” and it needs time to get the feature right before rolling it out more broadly.
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For founders, Startup Battlefield 200 is one of the biggest moments of their careers. For everyone else in theTechCrunch Disrupt 2026audience, it’s one of the best ways to learn how great companies are actually evaluated by VCs. This startup pitch competition is as intense as you’d expect. From October 13–15 at San Francisco’s Moscone West, every hand-picked founder has six minutes to make their case, but the most revealing moments often come after the presentation ends. That’s when the judges start asking the questions every investor, customer, and future employee will eventually want answered. Can this team execute? Is the market big enough? Why now? What’s defensible? Those conversations are as valuable for the thousands of founders watching from the audience as they are for the companies onstage. That’s why we’re continuing to build one of the strongest judging panels in Startup Battlefield’s history. Today we’re excited to introduce another group of five top-tier investors who’ll help identify the companies with the potential to become tomorrow’s breakout success stories. Join the Startup Battlefield contenders and VC judges on the main stage, alongside 10,000+ tech leaders attending Disrupt, and watch the next generation of startups compete for their place in TechCrunch history.Register now to save up to $200on your pass before prices increase on September 25 at 11:59 p.m. PT. Without further ado, meet the next batch of investors who will judge which early-stage founder walks away with the $100,000 prize. Get to know these judges, along with the first 10 already announced on theDisrupt agenda. Vaibhav ‘Dr.V’ Agrawal, Co-Founder and General Partner, ODDBIRD VC Dr.Vis the co-founder and general partner ofODDBIRD VC, a pre-seed fund he founded in 2024 to back AI companies reindustrializing the West — with a focus on health and bio, critical supply chains, and real-world automation. A trained physician with an MBBS degree, Agrawal also holds an MBA from Stanford and previously served as a general partner at Lightspeed Venture Partners India, where he backed early-stage startups beginning in 2016. His current portfolio includes Anterior, a healthcare AI company that has raised $64 million from NEA and Sequoia. Anu Bharadwaj, Partner, ICONIQ Anu Bharadwajis a partner atICONIQ, where she focuses on enterprise software and AI companies. Before joining ICONIQ, Bharadwaj served as president and COO of Atlassian for nearly 12 years, where she led the product, engineering, and enterprise business across Jira, Confluence, and the Atlassian Cloud platform as the company scaled to billions in annual revenue. She previously held leadership roles at Microsoft and holds a bachelor of engineering in computer science from R.V. College of Engineering. Sho Sho Leigha Ho, Partner, General Catalyst Sho Sho Leigha Hois a partner onGeneral Catalyst‘s seed team, where she invests in early-stage founders. She serves as a board observer at Together AI. She joined General Catalyst in 2024 as its youngest partner. Her public investments include Graylark, Autoscience, Standard Kernel, and The Interaction Company of California (Poke), which Cognition acquired in July 2026. She holds an AB from Harvard and is based in San Francisco. Miloni Madan Presler, Partner, IVP Miloni Madan Presleris a partner atIVP(Institutional Venture Partners), where she partners with first-time founders building inflection-stage technology companies in enterprise software, healthcare, and security, from Series B through pre-IPO. She brings a disciplined growth equity and private equity perspective to company building, shaped by earlier roles at Summit Partners and Warburg Pincus. Presler holds a degree in Economics and Finance from Johns Hopkins University and speaks four languages. Aidan Madigan-Curtis, Partner, Eclipse Ventures Aidan Madigan-Curtisis a partner atEclipse Ventures, where she invests in AI, IoT, computer vision, and software solutions for manufacturing, logistics, supply chain, and climate transition. Named one of Business Insider’s 22 Investors to Know in Robotics and Physical AI, she leads Eclipse’s Carbon Optimization framework to track real emissions reductions across the firm’s portfolio. Before venture, Madigan-Curtis was a senior executive at Apple — scaling Apple Watch manufacturing from zero to millions of units per week — and a VP and general manager at Samsara, where she helped grow the company from pre-revenue to over $1 billion in ARR. She holds a BA from Harvard University and an MBA from Stanford University. TechCrunch Disrupt 2026is happening October 13-15 in San Francisco, bringing 10,000+ tech leaders, VCs, and founders together to meet the next generation of breakout startups, connect with the leaders who could change their startup’s trajectory, and get a front-row seat to where the industry is headed.Save up to $200 on your ticketbefore rates increase on September 25 at 11:59 p.m. PT. Save an additional 30% when youregister as a group.
ElevenLabs builds the voice layer of AI, the models that turn text into speech that sounds human. Most people encounter it when they’re talking with customer service — often without realizing it. Klarna runs first-line phone support for 35 million U.S. customers on it, for example. So do Deutsche Telekom, Cisco, Adobe, and a growing list of governments. ElevenLabs also sells to creators, who use its platform for audiobooks, dubbing, and music. It’s not alone in what it does. In fact, it’s increasingly bumping into customers, including Decagon, a conversational AI platform that trained its voice product on ElevenLabs and now competes with it. But its investors don’t seem too concerned. The company, which says it’s pacing at $600 million in annual recurring revenue, is now reportedly valued at$22 billionby its backers, despite being just four years old. To understand more, I interviewed ElevenLabs co-founder and CEO, Mati Staniszewski, atNrthin Toronto, a local entrepreneurship conference formerly known as Elevate. We covered a range of topics in a short time, including whether businesses should tell customers when they’re talking to an AI (he thinks they should), and whether he could discuss the company’s gross margins. Unsurprisingly, Staniszewski said he couldn’t discuss them in any detail, but he was clear that he doesn’t mind them getting squeezed even further if it means expanding the company’s market share. Our conversation follows, condensed and lightly edited. You can check out the full conversationhere. You joined us at TechCrunch Disrupt last year, where you said audio models would be commoditized within acouple of years. How would you rate that prediction now? There is still a lot of work to be done, and the quality delta you can achieve just on the model level is still significant. If we think longer term, probably three, five years from now, those differences will be smaller. What we’d love to do, and be the first ones to do, is pass the Turing test for conversational AI. You need to combine intelligence, but you also need emotional intelligence. You need to understand the emotions of the other side, to be able to slow down or speak up. That hasn’t yet been done. What percentage of the business is enterprise now? We are now $600 million in ARR. Fifty-five percent plus is classic enterprise, and a big percentage of the [remaining] 45% are small and medium businesses, developers, builders, creators. Like everyone else in AI, you’re increasingly competing with your customers. Decagon trained its voice product on you and now runs queries through its own models. The lines become more blurry. As we think about model companies, platform companies, application companies, in the past you’d have very clear splits where one starts and ends. Today that line is much more blurry. In Anthropic’s case, what was a model company is definitely a platform and increasingly a wide set of applications. I think this will continue. Your customers can choose the “reasoning layer” from a menu of options at ElevenLabs. What are you seeing in terms of the use of frontier lab models versus open weight? It’s less of a binary choice. In customer experience, if you’re calling in and it’s just informational, you’re not executing any actions — you can use a lot of the open source models because your knowledge base defines what a good experience is. But if it’s financial services, you want to be authenticated, you want information about a transaction, maybe a refund. There’s no room for error. Here, frontier models will still lead. Some of those open-weight models are Chinese. The U.S. government is a customer. European governments are customers. What are those conversations like? Different. In each deployment, the models and the voices we deploy will depend on the case. If we work with the Polish government or the Brazilian government, they have their own set of requirements. It can be an open-weight model, a closed-source model, their own fine-tuned model. [In Poland] it’s a healthcare case. You have patients booking appointments across the public health system, and 18% never show up. The deployment is agents that call and remind you. They had a set of models optimized on their knowledge, and we integrate while keeping data residency. Should businesses disclose when someone is talking to an agent rather than a human? I think there should be disclosure at this time. Currently, people aren’t used to it, and the common pattern is you don’t want to feel cheated on that call. But in five years, when everybody has their own agent working on their behalf, you’ll be calling in and expecting an agent. Then I think we’ll shift as a society. There are good ways of doing it — if there’s a 30-minute wait for a human, offer the customer a choice. In almost all cases, they choose the agent and then they’re surprised by how good the experience is. What are your gross margins, given what you’re paying for models and inference? I’m going to give a vague answer. Given we have that research element, we’re able to fine-tune and constrain models in extremely smart ways. But if we can pass on any savings to the customer, we do that. The biggest thing is still proving the value and being there with the customer. So if we can invest and prove that value, we don’t mind the margins going lower to actually benefit together as the value gets created in the next five years. You have millions of hours of customer service calls. Do you train on them? How much of your training data is synthetic? In certain companies, we created the models together. They wanted a specific model for their use case. Otherwise, the big part of the training hasn’t been so much the volume of data, it was annotating the data. We have thousands of people internally on a contracting basis helping us annotate not only what was said, but when people were speaking, how they said things, what emotions were used. We had to bring voice coaches in to be able to detect accents accurately. It’s been reported you’re looking at 2028 for an IPO. Can you confirm that? We’d love to create a company that stands the test of time. We are preparing the foundation to be able to do it in the next years. But whether we do it will depend on the time and place. “Years” is very vague. [Laughs.] Backstage: Where do you land on whether the frontier labs should slow down? Everybody is aligned to work together on finding a way to pace. Whether they should be public about it, and how much of the media conversation or regulation it should involve, that’s another topic. But yes, we should all take the right precautions as we deploy the technology. We don’t train the text models and the intelligence side of models, which is the core key of the debate. Could ElevenLabs be exposed the way Hugging Face was? We’re a step further, because we don’t deploy self-replicating or recurrent parts of the intelligence of agents. Our technology doesn’t allow you to let agents create more agents. Every customer goes through KYC. Cybersecurity risk is definitely a risk for the wider world, but we have a good set of precautions in place.
TechCrunch Founder Summitis a full-day gathering in Boston on November 4 where founders across all stages connect with top VCs and experienced entrepreneurs to gain tactical insights on building and scaling their companies. It’s the latest in our long line of founder-centric events, which are smaller and more hands-on than Disrupt. If anextensive lineupof speakers from Anthropic, Nvidia, OpenAI, and Benchmark is your thing,Disrupt tickets are still available here. But for the founder looking to really get in the weeds during a one-day crash course, Founder Summit is the ideal place to get a head start on your 2027 plans. Before you dig in on the event details, you can get info on all of our tickets, which are available for a $200 discount for investors and founders,right here. All founders end up wrestling with the extensive, complicated mechanics of building a company from the ground up. There’s fundraising, hiring, legal, marketing, PR, and leadership, as well as the investors needing the means to vet, invest in, and develop founders as they build out their skills. Founder Summit is the best way to cover all of the challenging questions with community members who have been there, and lived to tell the tale, through constructive failure and massive success. The event takes place on Wednesday, November 4, 2026, at theSoWa Power Stationin Boston. It’s accessible via public transportation and a short walk from the Back Bay and Tufts Medical Center stops on the Orange Line, or the Broadway stop on the Red Line. To deliver on that promise of equipping founders for success,this year’s agendaandspeakerslean hard into fundraising, AI-native building, and leadership. Sessions include: Yes. Founder Summit was formerly known asEarly StageandAll Stage. This year, we have the same mission, but with a new name. Keep that in mind if you want to do any more research before attending. Founder Summit is far from a series of panels, though the agenda does provide a ton of valuable insights for founders and investors. In addition to all of those sessions, we also have our breakout sessions, where even more intimate panels discuss vital topics for the community to dive deeper into. There’s also networking available via the Braindate app to help connect investors with founders, or facilitate founders with similar challenges to bring their expertise together to reach shared solutions. Or that time is the perfect opportunity for students to build out their nascent network. Then there’s Founder Summit week, taking place November 1-7. That’s whenall of our Side Events are held, expanding the opportunities for you to gather with the community. And if you’re especially eager to take part, you can apply to host your own Side Eventright here. Pricing moves in phases, with our next increase happening after October 16.Our current pricing tiers are Investor for $399, Founder for $199, and students for $149. If you buy a second ticket for a co-founder or co-worker, you’ll also get 50% off their admission. And bundles for groups for four or more offer additional discounts. Yes! We’re looking for volunteers to help staff the event, and those individuals will get a behind-the-scenes look at how the event comes together on top of their free access to programming beyond their shift. Learn more about our program, which closes to new applicants October 19,right here. You can get the full rundown of the event, with everything from up-to-date speaker information, the full agenda, logistics, and moreright here. Ticket information across all three tiers isavailable here. And remember, our current discounts end October 16 — act now before they expire.
Google’s new AI-powered feature that turns photos of your outfits into a virtual closet — one seemingly inspired by Cher’s iconic virtual wardrobe app featured in the movie “Clueless” — is now available to everyone in the U.S., Brazil, and India, on both iOS and Android devices. The company first announced the feature earlier this year with plans to begin the rollout in the summer. Android users gained access first, starting in June, and now the virtual closet is available to all Android and iOS users in the supported markets. The idea of a digital closet in “Clueless” was meant to highlight Cher’s privileged life, where she had so many outfits that she needed a digital system to help her choose what to wear and keep everything organized. Now, you don’t have to be a rich Beverly Hills teenager to take advantage of such technology. Instead, Google uses AI technology to create a copy of your wardrobe, based on the items you wore in your photos. From the app, you can also filter items by category — like tops, bottoms, jewelry, and more — then mix and match them to create different outfits. Google says the feature is designed to assist the user, and the data about how you dress or what you wear is not being shared with third parties, like retailers. The broader rollout of the virtual closet feature arrives alongside a handful of other Google Photos updates, including a way toselect, brighten, and share photos using a single promptin Gemini Spark, an upgraded markup tool, and more Remix templates that use AI to transform your photos. (The Gemini Spark feature requires a Google AI Pro or Ultra subscription in the U.S.) With Markup, you’ll be able to use a redacting pen to blur sensitive information like license plates, access precise thickness sliders for custom sketches, and pick from different fonts when adding text to photos. For Android users, there are also new photo filters, called “Moods,” that let you give your images different looks, like 35mm film, 2000s digicam, and more.
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Sridhar Vembu outlines Zoho’s AI push, proprietary models, rising costs, and the future of software jobs.
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Data centre-related job postings in India rose to 1.3% in August, with demand spanning software, engineering, management, sales, and project management roles.
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OpenAI and Anthropic announced more cost-efficient artificial intelligence models earlier this week. The move comes as demand for lower-cost AI services continues to grow. OpenAI launched GPT-6 Sol and GPT-6 Luna models, while Anthropic unveiled Claude Opus 5.5. OpenAI and Anthropic are facing increasing competition from open-weight models, especially from Chinese brands. The launch of GPT-6 Sol and GPT-6 Luna and Claude Opus 5.5 could give OpenAI and Anthropic an edge over cost-efficient models in the AI space.
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An OpenAI model hacked into an Australian government website, the country’s prime minister Anthony Albanese said Wednesday, in the first publicly reported case of an AI model hacking into a government’s systems. Albanese said that there would “obviously be legal consequences” following the breach, and said that OpenAI faces a government investigation into how its unreleased models gained access to reams of bulk health data information. This latest incident disclosure comes as governments and tech companies grapple with how to rein in increasingly autonomous AI after a recent spate of AI agents breaking out of their sandboxes, colluding on the internet, and posing cybersecurity issues. The breach also poses questions about how both OpenAI and the Australian government failed to detect the attack until several months later. During aWednesday news briefingat the U.N. General Assembly, Albanese said that the breach began on June 18, but that OpenAI did not notify the government until September 10. OpenAI only became aware of the incident in August when it turned up during a broader, companywide review of agents behaving in unintended ways, according to an OpenAI spokesperson who reached TechCrunch via email. f The unspecified OpenAI agent obtained both public and nonpublic files from Services Australia, which administers Australia’s universal healthcare scheme. While the prime minister said there is no evidence that any citizens’ personal information was leaked, OpenAI said that the information the agent reached included aggregate health statistics and internal file names. The agent was running during an internal OpenAI evaluation, seeking answers about Australia and publicly available medicine information. At the Medicare portal, the agent encountered repeated blocks but found ways around them. Albanese told reporters that the model “didn’t accept no for an answer,” and added that the model had actively written data to the government’s database, rather than just accessing it, indicating the possibility that the department’s data was modified or muddied. The prime minister said OpenAI disclosed the breach by sending a notification to the public mailbox of Services Australia, which then notified Australia’s Cyber Security Centre five days later. It’s unclear why there was a delay, but Albanese said he raised the breach directly with OpenAI chief executive Sam Altman by stressing Australia’s “extreme concern” about this incident and “disappointment” that OpenAI sat on the information for nearly three months. “This situation is obviously unacceptable,” said Albanese, making clear that he held the company accountable for both the hack and how slowly it came to light. Albanese said that the government’s investigation will consider law enforcement and legislative responses to prevent incidents like this one happening again. Australian media outlet ABC Newsreportsthat the latest identified attack may have relied on anearlier breach of a German wiki site, which was used as a staging ground for attacking the Australian government’s website. The AI model agents reportedly used the German wiki to leave notes to be used in later hacks, including a note to obtain data from the Australian Institute of Health and Welfare, a federal agency that publishes national health data. The agency is one of three additional systems that Albanese said may have been breached. Transluce, a nonprofit AI research lab,separatelyfound public records showing AI agents targeting the Australian Institute of Health and Welfare on June 20 and 21. OpenAI did not respond to TechCrunch’s specific inquiry on whether the incidents were connected but acknowledged their “activity involving several Australian government websites and services.” The incident comes after a string of security incidents caused by rogue agents, often acting within the infrastructure of AI labs. In July, swarms of OpenAI agents breached Hugging Face. Since then, more incidents of AI agent hacks from Anthropic, Meta, and Google have beenrevealed. OpenAI now says it is conducting an “extensive review of misaligned model activity during training and evaluation” and is notifying third parties of potential breaches.
In a two-week sprint last month, the company merged over 3,000 changes to improve the core user experience.
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