Recent AI news and official updates

TechCrunch AI published: Apple alleges the misconduct was directed by OpenAi's senior leadership, including a long-time former employee.

TechCrunch AI published: Open source AI is booming, according to Hugging Face CEO Clem Delangue. The company has grown into something like a GitHub for AI in recent years, where AI builders can share and download open models and datasets, now used by roughly half the Fortune 500. Delangue has seen the same story play out again and again: companies start […]

TechCrunch AI published: The AI chip boom just produced its biggest Wall Street moment yet. Now SK Hynix and Samsung are being asked to build U.S. factories.

Simon Willison's AI Notes published: The reality is to make augmented reality glasses, you need to put a camera next to your eyes that is continuously recording everything you see and processing that to put information over it. There is not another way around it. And there's certainly not a chip that can fit in the stem of a glasses that is both powerful enough and power miserly enough to do that in real time. You have to send that data to a cloud. You gotta do it. [...] Or you can build something the size of a Vision Pro with a battery pack that lives somewhere else. Those are the current choices in this world. And it means if you want to build the product that everyone thinks is the next thing, you are going to have to invade people's privacy. And maybe you shouldn't. Like, there's an incredible argument for, nope, you shouldn't do that. Nope, the trade-offs required to make this product are so high at a societal level that we should stop it. — Nilay Patel , The Vergecast Tags: augmented-reality , privacy , ai , nilay-patel , ai-ethics

TechCrunch AI published: Open source AI is booming, according to Hugging Face CEO Clem Delangue. The company has grown into something like a GitHub for AI in recent years, where AI builders can share and download open models and datasets, now used by roughly half the Fortune 500. Delangue has seen the same story play out again and again: companies start […]

MIT Technology Review published: This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Anthropic found a hidden space where Claude puzzles over concepts The AI firm Anthropic has got the clearest glimpse yet at what’s really going on inside large language models as they…

Simon Willison's AI Notes published: [...] Work on web and mobile runs in the cloud. Work in the desktop app can also use local files and desktop apps with your permission. At launch, cloud Work conversations do not appear in desktop Work; desktop Work threads and local files remain on that computer. — OpenAI , trying (unsuccessfully) to clarify ChatGPT Work Tags: ai , openai , chatgpt

TechCrunch AI published: OpenAI's new family of models will continue to power Microsoft's suite of workplace and productivity apps.

TechCrunch AI published: OpenAI's No. 2 executive, Fidji Simo, is stepping down from her full-time role after her medical leave proved longer than expected — a leadership vacuum that comes at a tricky time as the company eyes a possible IPO and races to catch Anthropic in the enterprise market.

TechCrunch AI published: OpenAI's latest family of models promises improvements across a range of areas, including cybersecurity.

TechCrunch AI published: Lyzr, a startup that builds AI agents for enterprises, used its own AI agent to raise a $100 million round — proof, evidently, that the product actually works.

TechCrunch AI published: OpenAI is sunsetting its AI-powered browser after less than a year. But it's moving some agentic browsing features to its desktop app and a Chrome extension.

TechCrunch AI published: Should Anthropic trust Elon Musk to host its models? With about $40 billion in revenue at stake, Musk insists that the company can.

TechCrunch AI published: The AI ROI debate has returned and the numbers are even bigger, as are, perhaps, the consequences.

MIT Technology Review published: The AI firm Anthropic has developed a technique that has given it the clearest glimpse yet at what’s really going on inside large language models as they answer questions or carry out tasks. What they found ranges from the mundane to the unnerving. Researchers at the company built a tool called the Jacobian lens (or…

Simon Willison's AI Notes published: OpenAI's latest flagship model hit general availability this morning , and comes in three sizes: Luna, Terra, and Sol (from smallest to largest). The new models are priced per 1M input/output tokens as Luna $1/$6, Terra $2.50/$15, Sol $5/$30. For comparison, the Claude Opus series are $5/$25 and the Claude Fable 5 is $10/$50, but price-per-million tokens doesn't tell us much now that the number of reasoning tokens can differ so much between models for the same task. All three models have a February 16th 2026 knowledge cutoff, a million token context window, and 128,000 maximum output tokens. OpenAI's biggest benchmark claim concerns long-running agentic performance, with one benchmark showing all three models outperforming Claude Fable 5: We trained GPT-5.6 to get more useful work from every token. On Agents’ Last Exam , an evaluation of long-running professional workflows across 55 fields, GPT-5.6 Sol sets a new high of 53.6, eclipsing Claude Fable 5 (adaptive reasoning) by 13.1 points. Even at medium reasoning, it beats Fable 5 by 11.4 points at roughly one-quarter the estimated cost. That efficiency extends to smaller models, which are essential to making intelligence more abundant and affordable: GPT-5.6 Terra and GPT-5.6 Luna outperform Fable 5 at around one-sixteenth the cost. Amusingly, one self-reported benchmark that Fable 5 crushed the GPT-5.6 family on was SWE-Bench Pro, where Fable 5 got 80% compared to GPT-5.6 Sol getting 64.6%. This may help explain why OpenAI chose to publish this article yesterday specifically calling out SWE-Bench Pro for problems they found while auditing that benchmark: In light of these results, we estimate that ~30% of SWE-bench Pro tasks are broken, and advise that model developers carefully examine results I've had some early access to GPT-5.6 Sol - it's definitely very competent, though so far it hasn't struck me as better than Fable at the kind of complex coding tasks I've been using with Anthropic's model. As usual, the model guidance for using GPT-5.6 has the most interesting details. There are a bunch of new API features that I need to explore (and probably add support for in LLM ), including: Programmatic Tool Calling allows the models to "compose and run JavaScript that orchestrates tool calls" - which sounds to me like it could help bridge the gap between MCPs and full terminal sessions that can compose CLI utilities in useful ways. Also reminiscent of the dynamic filtering mechanism Anthropic added to their web search tool, which allows code execution against web results as part of a single model turn. Multi-agent lets the model "spin up subagents for parallel, focused work" - the sub-agent pattern now baked into the core API. Prompt cache breakpoints brings the Claude model of prompt caching to OpenAI, letting you be explicit about where the cache breakpoints are rather than relying on the API to detect them automatically. Personally I much prefer automatic detection (still supported by OpenAI), but presumably there are optimization cost savings to be had here if you put the work in. You can now set detail: original on image requests to avoid resizing the image at all before it is processed. Here's a full page with 18 different pelicans - for reasoning efforts none, low, medium, high, xhigh, and max across the three different models. It also lists their token and calculated costs - the least expensive was gpt-5.6-luna at effort none for 0.71 cents, the most expensive was gpt-5.6-sol at max reasoning level for 48.55 cents. In further pelican news, if you jump to 17:50 in their livestream from this morning you'll see OpenAI's own demo of 3D pelicans riding a tricycle, a bicycle, a pony, and another pelican! Tags: ai , openai , generative-ai , llms , llm-tool-use , llm-pricing , pelican-riding-a-bicycle , llm-release , gpt-5

TechCrunch AI published: Meta's pitch to users is Spark's ability to handle large agentic workloads, fix bugs, and help with large code migrations — the kind of automation that enterprises are increasingly turning to AI companies to provide.

TechCrunch AI published: News publishers say OpenAI hid tools and datasets that could identify copyrighted journalism in ChatGPT outputs, escalating their lawsuit with a new motion for sanctions.

TechCrunch AI published: While Google prohibits misleading and deceptive ads, an ad can still leverage AI to create some type of synthetic or digitally altered content. Until now, that's something Google only required election ads to disclose.

TechCrunch AI published: The company is using the cash to open an office in the Bay Area and compete for talent there, "strengthening its position at the heart of the world's leading AI ecosystem."