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OpenAI published a claimed solution to Navier-Stokes existence and smoothness, one of the seven Millennium Prize Problems, produced by an internal AI model rather than human mathematicians. The company says the proof took roughly 88 hours of compute across about 10,000 parallel agents. It remains unpublished and unreviewed, and 700 HN comments are arguing about what "AI solved it" actually means.
Meta launched Muse, a personal agent that can send email, book travel, fill out web forms, and manage long-horizon goals like a yearlong fitness plan or standing up a business. It runs in an isolated per-user virtual machine and reportedly never sees raw passwords or payment details. Available via a standalone app or WhatsApp, US-only, with a free tier plus twenty and one hundred dollar monthly plans.
NYU Courant mathematician Tristan Buckmaster released a statement saying he and Levent Alpöge independently reached a nearly identical result on one component of the problem using several AI models. He alleges a parallel OpenAI effort built on their pre-publication work, including private Codex session material. Buckmaster and Alpöge shipped Lean-verified finite-time blowup proofs for three fluid systems; OpenAI's full claim has not been released.
DeepMind shipped a database of predicted functional effects for every possible single-nucleotide variant across the human genome. Instead of studying variants one at a time, researchers get a unified reference for the entire mutation space. It's a plausible accelerant for disease-variant discovery and personalized medicine.
Inception Labs released Mercury 2.5, billed as the most capable diffusion LLM in production, claiming a 40 percent jump over Mercury 2 and rough parity with cost-optimized frontier models. It runs 1,107 tokens per second on standard NVIDIA GPUs with a 260K context window at twenty cents in and seventy-five cents out per million tokens. The pitch is latency-critical work: voice apps near 170 millisecond median response and coding assistants cutting latency by 82 percent.
Argonaut Labs released Deltafin, a native binary that runs the full 2.8-trillion-parameter Kimi K3 on an M5 Max laptop by streaming mixture-of-experts weights off four SSDs on demand. No pruning, no compression — all 16 experts vote on every token — landing at roughly 1.0 tokens per second with speculative decoding. Streaming mode loads 215GB up front instead of the full 1.7TB and caches experts as it goes, with prefill still the ugly bottleneck at about 376 seconds.
Quesma benchmarked Unsloth GGUF quantizations of Qwen3.8 27B across GPQA Diamond, IFBench, and Terminal-Bench 2.1. The 4-bit build matched the full model on agentic coding and fits a 24GB card with about 64k context, while 1-bit fell below random guessing on graduate science questions. The headline lesson is that quantization damage is nonlinear — fine, fine, fine, then a cliff.
Blackmagic shipped Resolve 21.1 with a native MCP server, letting Claude, ChatGPT, and Codex drive multicam, markers, audio, transcripts, and renders via natural language. The release also adds stills support on the Photo page, new camera log formats from DJI, GoPro, Leica, and Vivo, over 25 Krokodove shape and 3D tools, and 20 new scripting APIs. It's one of the first mainstream creative suites to treat agent control as a first-class feature.
A portable skill for Claude, Cursor, Gemini, and friends that enforces ten formatting rules on assistant output: action first, numbered steps, no preamble, no tangents, five-item list cap, and concrete time estimates in minutes. The premise is that agents bury the actionable bit under paragraphs of throat-clearing. 176 comments suggest it struck a nerve well beyond its titular audience.
Martin Uecker walks through how GCC lowers nested functions into a single shared synthetic frame struct passed as a hidden argument, versus C++ lambdas which create a separate closure object per expression. He argues the runtime semantics are effectively identical and nested functions are a small semantic subset of lambdas. The implication: any compiler with lambda infrastructure could implement nested function syntax on top of it.