Recent AI news and official updates

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.

TechCrunch AI published: Spotify will let you generate daily or weekly briefs based on your prompts

MIT Technology Review published: The vibes were strong at Code with Claude, Anthropic’s two-day event for software developers in London that kicked off on May 19, the same day as Google’s I/O in Palo Alto. (A coincidence, not a flex, Anthropic staffers assured me.) “Who here has shipped a pull request in the last week that was completely written…

TechCrunch AI published: The Path says its AI model has scored 95 on the mental health safety AI benchmark, Vera-MH. This compares to a top score of 65 for the consumer bots.

TechCrunch AI published: Hark expects to release its first multimodal models this summer, which it says will power a personal AI platform that works with existing products and services. The company expects to follow that with hardware devices built specifically for those systems.

TechCrunch AI published: One of the most promising introductions at Google’s I/O developer conference on Tuesday was a new way for consumers to use the web: AI agents. Unfortunately, it was also the most confusing.

TechCrunch AI published: Recycling startups are using AI to improve the recovery of critical minerals like aluminum, aiming to build a massive source of the metal.

MIT News AI published: A new study of the postwar U.S. shows which kinds of workers historically filled new tech-enabled jobs.

TechCrunch AI published: The next big thing for Nvidia will be CPUs for AI agents, $200 billion worth, CEO Jensen Huang predicts.

Simon Willison's AI Notes published: We have the ability to use compute resources to support our proprietary AI applications (such as Grok 5, which is currently being trained at COLOSSUS II), while also providing access to select compute capacity to third-party customers. For example, in May 2026, we entered into Cloud Services Agreements with Anthropic PBC (“Anthropic”), an AI research and development public benefit corporation, with respect to access to compute capacity across COLOSSUS and COLOSSUS II . Pursuant to these agreements, the customer has agreed to pay us $1.25 billion per month through May 2029, with capacity ramping in May and June 2026 at a reduced fee. The agreements may be terminated by either party upon 90 days’ notice. — SpaceX S-1 , highlights mine Tags: ai , generative-ai , llms , anthropic , grok

Google AI Blog published: This year at Google I/O 2026, we announced Gemini Omni, Google Antigravity, Universal Cart and so much more. Here are the highlights.

Simon Willison's AI Notes published: How fast is 10 tokens per second really? Neat little HTML app by Mike Veerman ( source code here ) which simulates LLM token output speeds from 5/second to 800/second. Useful if you see a model advertised as "30 tokens/second" and want to get a feel for what that actually looks like. Via Hacker News Tags: ai , generative-ai , llms

Simon Willison's AI Notes published: It's hard to find much to write about Google I/O this year because I have a policy of not writing about anything that I can't try out myself, and a lot of the big announcements are "coming soon". I actually prefer to write about things that are in general availability, because I've had instances in the past where the previews didn't match what was released to the general public later on. Aside from Gemini 3.5 Flash the most interesting announcement looks to be Google's upcoming OpenClaw competitor Gemini Spark , described as "your personal AI agent" which can "connect natively with your favorite Google apps like Gmail, Calendar, Drive, Docs, Sheets, Slides, YouTube, and Google Maps". The FAQ for that also includes this confusing detail: What Gemini model does Gemini Spark run on? Gemini Spark runs on Gemini 3.5 Flash and Antigravity. The antigravity.google website currently lists Antigravity as a desktop app, a CLI agent tool (written in Go), the Antigravity SDK (an open source Python wrapper around a bundled closed source Go binary), and the original Antigravity IDE (a VS Code fork). I guess Gemini Spark, the user-facing hosted agent product, might be running on that Go binary, but I'm not sure why that's worth mentioning in the FAQ! Naturally I went looking for notes on how Gemini Spark intends to handle the risk of prompt injection. The best information I could find on that was in the Everything Google Cloud customers need to know coming out of Google I/O post aimed at enterprise customers, which includes: Spark operates in a fully managed, secure runtime on Google Cloud, meaning you get enterprise-grade security without ever having to manage the underlying infrastructure. Every task executes in a fresh, strictly isolated, ephemeral VM to help ensure data never overlaps between sessions. To protect your enterprise, all traffic routes through our secure Agent Gateway that enforces Data Loss Prevention (DLP) policies, while user credentials remain fully encrypted and are never exposed directly to the agent. Given how many people are going to be piping very sensitive data through Gemini Spark in the near future I hope they've made this bullet-proof, or this could be a top candidate for the agent security challenger disaster that we still haven't seen. Also of note: in Transitioning Gemini CLI to Antigravity CLI Google announce that the open source Gemini CLI tool (Apache 2.0 licensed TypeScript) will stop working with their AI subscription plans on June 18th, replaced by the new closed source Antigravity CLI . Tags: gemini , google , generative-ai , ai , google-io , llms , prompt-injection

MIT News AI published: Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.

Simon Willison's AI Notes published: Today at Google I/O, Google released Gemini 3.5 Flash . This one skipped the -preview modifier and went straight to general availability, and Google appear to be using it for a whole lot of their key products: 3.5 Flash is available today to billions of people globally: For everyone via the Gemini app and AI Mode in Google Search For developers in our agent-first development platform Google Antigravity and Gemini API in Google AI Studio and Android Studio For enterprises in Gemini Enterprise Agent Platform and Gemini Enterprise. As usual with Gemini, the most interesting details are tucked away in the What's new in Gemini 3.5 Flash developer documentation. It mostly has the same set of platform features as the previous Gemini 3.x series, albeit with no computer use . The model ID is gemini-3.5-flash . The knowledge cut-off is January 2025, and it supports 1,048,576 input tokens and 65,536 maximum output tokens. Google are also pushing a new Interactions API , currently in beta, which looks to me like their version of the patterns introduced by OpenAI Responses - in particular server-side history management. The price has gone up Gemini 3.5 Flash is accompanied by a notable price bump. The previous models in the "Flash" family were Gemini 3 Flash Preview and Gemini 3.1 Flash-Lite . The new 3.5 Flash is 3x the price of 3 Flash Preview and 6x the price of 3.1 Flash-Lite (see price comparison here ). At $1.50/million input and $9/million output it's getting close in price to Google's Gemini 3.1 Pro, which is $2 and $12. The Gemini team promise that 3.5 Pro will roll out "next month" - presumably at an even higher price. This fits a trend: OpenAI's GPT-5.5 was 2x the price of GPT-5.4, and Claude Opus 4.7 is around 1.46x the price of 4.6 when you take the new tokenizer into account . Given the price increase it's interesting to see Google roll it out for so many of their own free-to-consumer products. It feels like all three of the major AI labs are starting to probe the price tolerance of their API customers. Artificial Analysis publish the cost to run their proprietary benchmark against models, which is a useful way to take things like tokenization and increased volume of reasoning tokens into account. Some numbers worth comparing: Gemini 3.5 Flash (high) : $1,551.60 Gemini 3.1 Pro Preview : $892.28 Gemini 3 Flash Preview (Reasoning) : $278.26 Gemini 3.1 Flash-Lite Preview : $93.60 Running the benchmark for 3.5 Flash (high) cost significantly more than 3.1 Pro Preview! Here are some numbers from other vendors: Claude Opus 4.7 (Adaptive Reasoning, Max Effort) : $5,117.14 Claude Opus 4.7 (Non-reasoning, High Effort) : $1,217.23 GPT-5.5 (xhigh) : $3,357.00 GPT-5.5 (medium) : $1,199.14 A pelican on a bicycle I ran "Generate an SVG of a pelican riding a bicycle" against the Gemini API and got back this pelican, which is a lot : From the code comments: <!-- Pelican Eye / Sunglasses (Cool Retro Aviators) --> hedgehog on Hacker News : That pelican looks like it's in Miami for a crypto conference. That one cost me 11 input tokens and 14,403 output tokens, for a total cost of just under 13 cents . Tags: google , ai , generative-ai , llms , gemini , llm-pricing , pelican-riding-a-bicycle , llm-release

Google AI Blog published: The latest from Google I/O: See how we’re helping you get more done with Gemini.

Google AI Blog published: At Google I/O 2026, we shared how we’re making AI more helpful for everyone. See everything we announced.

Google AI Blog published: Introducing a $100 AI Ultra plan — plus, new features and benefits for Google AI Plus, Pro and Ultra subscribers.