Today’s AI news: editorial picks and emerging stories

Announcing No Limit: a bot building tournament hosted by @Sequoia, @citsecurities and @OpenAI. Teams of 1 or 2 get 60 minutes to build a pokerbot from scratch. Agents play thousands of games across six scored rounds. Open to university students and recent grads (‘25 or ‘26). Regionals in Boston, Pittsburgh and the Bay Area in early November. Top five teams from each fly to the Finals. $100K grand prize.

GPT-6.1 Terra: delivering fast and capable computer use at a lower price. GPT-6.1 Terra understands what’s on screen, takes action across apps, writes naturally, and is a more capable model for your whole workday with the efficiency to take on more of it.

@dotey 谁能告诉我这和 Dots、Grok Bot、Muse 到底有啥区别？硅谷四大厂排队给我塞功能一模一样的赛博田螺姑娘，我那点少得可怜的待办事项已经不够它们分了......

My theory is biotech is about to turn into a national security thing and the west doesn't really get a vote Beijing just floated blocking foreign buyouts of china's cell and gene therapy and siRNA platforms And what's interesting is what they're NOT blocking. Licensing individual drugs is still totally fine So you can sell the west a medicine, just not the platform that makes the next 100 of them And the west has been buying like crazy lol. Foreign deals for chinese biotech assets are at $120B through august, up 36% Astrazeneca's $1B gracell deal, that CAR-T platform, probably doesn't happen under this draft Same update hits AI tech too btw we spent years fighting over who gets the chips. Feels like the next fight is over who owns the platforms that spit out the next generation of medicines Once biology is programmable it's not really a healthcare business anymore, it's infrastructure Still just a draft tho, comments open till nov 15 bio/acc.

Gemini 4 Argon from @Google on ARC-AGI (Verified): - ARC-AGI-3: 97.5%, $4.8K (provider adapter harness), 49.8%, $5.8K (standard harness) - ARC-AGI-2: 91.3%, $0.32/task - ARC-AGI-1: 98.5%, $0.16/task Google DeepMind is the second frontier AI lab to score above 95% on ARC-AGI-3. https://t.co/8siwgfBJcr

Gemini 4 Argon is amazing for knowledge work and coding - and it’s super fun to build with! We asked it to create this wizard chess game and it's so cool to see Argon's physics understanding & 3D modelling capabilities, makes me nostalgic for Battlechess on the Amiga - fun times! Argon is rolling out today to Google Ultra and Pro subscribers in the @GeminiApp and Search, and Ultra subscribers in @antigravity! More info & full availability in the blog: https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/

Nano Banana 2.1 is here! This upgraded version outperforms our previous models across the board, with notable leaps in: - visual design - mask-based editing - subject consistency - more natural-looking imagery Try it now in @GeminiApp, @GoogleAIStudio, and more.

Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.

In our Nature paper, we introduce the first superhuman Stratego AI, which we built using general techniques that we developed for RL & test-time compute under imperfect information. 1/N

Introducing Claude Sonnet 5.5, the second model in the Claude 5.5 family. It’s a clear upgrade over Sonnet 5, runs more than 30% faster, and costs up to 30% less for most work.

New on the Science Blog: Yes, Claude can do Nine Loops. Theoretical physicists predict how particles behave using formulas called scattering amplitudes. These are notoriously hard to compute, so researchers work with layers of increasingly fine corrections called “loops”—each added loop makes the answer more precise but takes exponentially more computation. Most calculations stop at two or three loops. Eight loops was the previous record in a simplified model physicists use as a testing ground (planar N=4 super-Yang-Mills), set by SLAC's Lance Dixon and collaborators. Last month, physicist and science writer @4gravitons issued a challenge: could an AI push past eight loops in this model, using only the compute budget an academic could reasonably access? Given a single prompt describing the nine-loop problem, Claude ran largely unsupervised for days in Claude Science and solved it using methods developed by Dixon and his colleagues, at a total cost of a few thousand dollars. Dixon independently verified the result, and von Hippel wrote about the experience for our blog. Read more: https://www.anthropic.com/research/yes-claude-can-do-nine-loops