Recent AI news and official updates

TechCrunch AI published: Pope Leo XIV's first encyclical uses AI as a lens to diagnose older problems: concentrated power, eroding democracy, and a tech elite that shapes the world to its own advantage.

TechCrunch AI published: We're in the transition period -- all of us.

Simon Willison's AI Notes published: The most frustrating failure mode right now is that people submit issues that are not in their own voice. They contain an observed problem somewhere, but it has been thrown into a clanker and the clanker reworded it and made a huge mess of it. Typically, it was prompted so badly that the conclusions produced are more often than not inaccurate but always full of confidence. The result is complete guesswork on root causes, fake-minimal repros, suggested implementation strategies, analogies to adjacent but often the wrong code, and long lists of error classes that might or might not matter. [...] So at least personally, I increasingly want issue reports to be condensed to what the human actually observed: I ran this command. I expected this to happen. This happened instead. Here is the exact error or log. — Armin Ronacher , on slop issues filed against Pi Tags: armin-ronacher , open-source , ai , generative-ai , llms , slop , ai-ethics , github-issues , coding-agents , pi

TechCrunch AI published: Like other AI wearables, Amazon's Bee offers an odd combination of convenience and privacy anxiety.

TechCrunch AI published: IBM and Scuderia Ferrari HP take TechCrunch inside how they are redefining the fan experience.

TechCrunch AI published: People used AI on a spectrogram image of cockpit recordings to reconstruct them, forcing the NTSB to temporarily block access to its docket system.

Simon Willison's AI Notes published: The memory shortage is causing a repricing of consumer electronics David Oks provides the clearest explanation I've seen yet of why consumer products that use memory are likely to get significantly more expensive over the next few years. The short version is that memory manufacturers - of which there are just three remaining large companies - have a fixed capacity in terms of how many wafers they can process at any one time. This fixed wafer capacity is then split between DDR - used in desktops and servers, LPDDR - used in mobile phones and low-energy devices, and HBM - used with GPUs. Until recently, HBM got just 2% of that wafer allocation. The enormous growth in AI data centers has pushed that up to an expected 20% by the end of 2026, and "a single gigabyte of HBM consumes more than three times the wafer capacity that a gigabyte of DDR or LPDDR does". Memory companies have learned from the extinction of their rivals that you should always under-provision rather than over-provision your fabricator capacity. The profit margins and demand for HBM (high-bandwidth memory) will constrain the production of consumer-device RAM for several years. This is already being felt in the sub-$100 smartphone market, which is particularly important to markets like Africa and South Asia. (The original title of the piece was "AI is killing the cheap smartphone" but I'm using the Hacker News rephrased title, which I think does more justice to the content.) Via Hacker News Tags: memory , ai , ai-ethics

TechCrunch AI published: Some AI startups are stretching traditional revenue metrics when talking about progress publicly. And their investors are fully aware.

Google AI Blog published: A recap of the 2026 I/O Dialogues, where leaders discuss the future of AI, quantum computing, robotics and creativity.

TechCrunch AI published: After Google Search's AI update, the word "disregard" now effectively breaks the search interface.

TechCrunch AI published: Google demoed prototype Android XR glasses that overlay Gemini-powered translation, navigation, and other information directly into your field of view.

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’s Code with Claude showed off coding’s future—whether you like it or not At Anthropic’s developer event in London this week, Code with Claude, attendees were asked if they’d shipped code…

MIT Technology Review published: During Tuesday’s Google I/O keynote, Demis Hassabis, the CEO of Google DeepMind, proclaimed that we are currently “standing in the foothills of the singularity.” It was a striking statement—the singularity is the theoretical future moment when AI rapidly exceeds human intelligence and dramatically transforms the world. But what struck me as I listened in the…

MIT Technology Review published: Listen to the session or watch below AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the forefront of the AI discussion. Watch a conversation with editor in chief Mat Honan, senior AI editor Will Douglas Heaven, and AI reporter…

Simon Willison's AI Notes published: We just announced the first release of Datasette Agent , a new extensible AI assistant for Datasette. I've been working on my LLM Python library for just over three years now, and Datasette Agent represents the moment that LLM and Datasette finally come together. I'm really excited about it! Datasette Agent provides a conversational interface for asking questions of the data you have stored in Datasette. Add the datasette-agent-charts plugin and it can generate charts of your data as well. The demo The announcement post (on the new Datasette project blog) includes this demo video : I recorded the video against the new agent.datasette.io live demo instance, which runs Datasette Agent against example databases including the classic global-power-plants by WRI , and a copy of the Datasette backup of my blog. The live demo runs on Gemini 3.1 Flash-Lite - it's cheap, fast and has no trouble writing SQLite queries. A question I asked in the demo was: when did Simon most recently see a pelican? Which ran this SQL query : SELECT title, commentary, created FROM blog_beat WHERE beat_type = ' sighting ' AND (title LIKE ' %pelican% ' OR commentary LIKE ' %pelican% ' ) ORDER BY created DESC LIMIT 5 And replied: The most recent sighting of a pelican by Simon was recorded on May 20, 2026 . The observation included a California Brown Pelican, along with a Common Loon, Canada Goose, Striped Shore Crab, and a California Sea Lion. Here's that sighting on my blog , and the Markdown export of the full conversation transcript. The plugins My favorite feature of Datasette Agent is that, like the rest of Datasette, it's extensible using plugins. We've shipped three plugins so far: datasette-agent-charts , shown in the video, adds charts to Datasette Agent, powered by Observable Plot . datasette-agent-openai-imagegen adds an image generation tool to Datasette Agent using ChatGPT Images 2.0 . datasette-agent-sprites provides tools for executing code in a Fly Sprites persistent sandbox. Building plugins is really fun . I have a bunch more prototypes that aren't quite alpha-quality yet. Claude Code and OpenAI Codex are both proving excellent at writing plugins - just point them at a checkout of the datasette-agent repo for reference and tell them what you want to build! Running it against local models I've also been having fun running the new plugin against local models. Here's a uv one-liner to run the plugin against gemma-4-26b-a4b in LM Studio on a Mac: uvx --prerelease=allow \ --with datasette-agent --with llm-lmstudio \ datasette --internal internal.db --root \ -s plugins.datasette-llm.default_model lmstudio/google/gemma-4-26b-a4b \ data.db Datasette Agent needs reliable tool calls and the ability for a model to produce SQL queries that run against SQLite. The open weight models released in the past six months are increasingly able to handle that. What's next Datasette Agent opens up so many opportunities for the LLM and Datasette ecosystem in general. It's already informed the major LLM 0.32a0 refactor which I'm nearly ready to roll into a stable release, maybe with some additional "LLM agent" abstractions extracte from Datasette Agent itself. I've been exploring my own take on the Claude Artifacts, which is shaping up nicely as a plugin. I'm excited to use Datasette Agent to build my own Claw - a personal AI assistant built around data imported from different parts of my digital life, which is a neat excuse to revisit my older Dogsheep family of tools. We'll also be rolling out Datasette Agent for users of Datasette Cloud . Join our #datasette-agent Discord channel if you'd like to talk about the project. Tags: projects , sqlite , ai , datasette , generative-ai , llms , llm , uv , datasette-agent

TechCrunch AI published: Spotify is partnering with Universal Music Group to let Premium subscribers create AI-generated song covers and remixes, with participating artists receiving a share of the revenue.

TechCrunch AI published: Google is about to look really different, and if you're not a fan of the AI overview feature, then you're not going to like what's coming.

MIT Technology Review published: Storytelling is core to humanity’s DNA, stemming from our impulse to express ideals, warnings, hopes, and experiences. Technology has always been woven through the medium and the distribution: from early humans’ innovation of natural pigments and charcoals for cave paintings to literal representation by the camera. The landscape of storytelling continues to shift under our…

TechCrunch AI published: President Trump delayed signing an executive order that would have required pre-release government security reviews of AI models, citing dissatisfaction with the order's language.

TechCrunch AI published: The AI-powered audiobook generation won't bind authors to an exclusive contract, meaning they are free to publish their generated audiobooks anywhere.