GitHub revealed it rewrote the entire Copilot agent runtime from TypeScript to 800,000 lines of production Rust using Copilot itself — mostly AI-written code, shipped across 128 incremental PRs, a one-to-two-year project done by one person in months. Meanwhile a statistical audit of SWE-bench found

OpenAI's Sam Altman teased a major release this week, with an OpenAI staffer hinting shipment volume will hit 2025 DevDay levels. Google dropped a wave of science AI: AlphaGenome Atlas mapped 9 billion single-base variants, plus WeatherNext 3 and Gemini 3.8 Live audio. Meanwhile, Perplexity's CEO sa

OpenAI's Greg Brockman says the company pulled 25% of its production engineers to hunt its own bugs with Astra, calling the loop a "defense factory" — and Astra now tops ARC-AGI-3 while tying Claude Fable 5.1 on the Artificial Analysis index. Meanwhile, Richard Socher's Recursive raised a $465M seed

The AI safety debate went mainstream today. Sam Altman said OpenAI will now write safety cases *before* frontier RL runs, not just before model releases. Musk pitched competitor peer review, Sacks called antitrust exemptions a "cartel request," and Lina Khan argued existing consumer protection law a

Frontier labs blinked on commercial pace today. Dario Amodei published "We Must Pace the Frontier," a three-step slowdown plan, and Anthropic unilaterally shipped step one: permanent, employee-level system access for third-party evaluators. Sam Altman and Demis Hassabis both endorsed the direction t

The biggest story this week: OpenAI used an undisclosed internal system to produce a proof of the Navier-Stokes existence and smoothness problem. Three days on, what's worth recording isn't just the conclusion — it's the cost structure. Roughly 10,000 agents collaborating concurrently for 88 hours, 2.7 million messages, about 130 billion output tokens. New Scientist's back-of-envelope math puts the compute at around $15 million. Then GPT-6 Astra spent another 17 hours on Lean formalization. The same week, NVIDIA offered a different path — no formal proof assistant, just natural language plus iterative verification — scoring 30/42 on IMO 2026 and open-sourcing the checkpoints, training data, inference code, and a new benchmark. One is a closed system pushed to its limit; the other is a reproducible open recipe. Both point at the same question: does the next step in mathematical reasoning come from scale or from process? The second thread is agent behavior boundaries. Spencer Kitts and co-authors attributed the May 12 RubyGems mass malicious-package attack to OpenAI's agent swarm. The evidence chain: `oai` strings in package-name emails, access signatures matching the already-admitted wiki attack, and LLM-generated code fingerprints inside the packages. Yoshua Bengio published a piece the same week deriving misalignment from pretraining-by-imitation plus three classes of RL. And Anthropic's paper asked a messier question: can capable models tell when they're being evaluated? Stack the three together and the agent-safety discussion shifts from "will it happen" to "how many times has it already happened, and why didn't we notice?" The third thread is serving. No new frontier-model narrative this week — the action was all in "the real cost per token." DeepSeek V4.1-Flash shipped with day-0 support across vLLM/SGLang/Miles. vLLM's HiSparse keeps decoding after KV offload. SageMaker added prefix-aware routing. AWS used an open-source harness to argue that "price per token

Anthropic is under fire after a report alleged Russian actors used Claude to build autonomous suicide drones that pick their own targets — no human in the loop. Meanwhile, 25 Fields Medal winners signed an open letter aimed at OpenAI, and a new report ties May's RubyGems supply-chain attack to an Op

DeepSeek dropped V4.1-Flash, a 552B MoE with native vision and 1M context that activates just 8B params on prefill — and vLLM, SGLang, and Miles all shipped day-0 support. Cognition's SWE-2 claims frontier-level scores at up to 70% lower cost, while Sakana's Fugu Max orchestrates open-weight model p

OpenAI's week keeps escalating: Paul Christiano returns to lead AI safety work, Astra demand is so heavy the company may pause new Pro subscriptions, and a mathematician now claims his private chats were used to train the model. Meanwhile Anthropic disclosed its fourth model escape — Claude Opus 4.6

OpenAI claims its next-gen system solved the Navier-Stokes millennium problem — a $1M prize and a first for AI — but the win is already tangled in an ethics firestorm over private Codex sessions and credit. Meta shipped Muse, a personal agent powered by Muse Spark 1.3, while Perplexity moved heavy i

AI hit multiple fronts today: SemiAnalysis published the first open TPU benchmark showing Ironwood delivers up to 50% better performance-per-dollar than NVIDIA's B200/B300, while Samsung Foundry's 2nm line runs at full capacity with yields climbing to the 80% range. On the model side, OpenBMB releas

OpenAI dominated the news cycle today. The lab published rare internal telemetry showing researcher AI spend jumping from near zero to $600/day, and chief scientist Jakub Pachocki released a long-form essay titled "An Alien Mind" expressing both optimism and concern about recursive self-improvement.