Entries for September 9, 2026

Qwen3.8-27B Unsloth GGUF is now the #1 most-liked GGUF of all time! The model hit 10M downloads and 3.7K likes in just 24 days on Hugging Face - all thanks to you. 🤗🦥 GGUF: huggingface.co/unsloth/Qwen3.… Guide: unsloth.ai/docs/models/qw…

🚀 Meet MiniCPM5-2B, a 2B-parameter language model bringing high intelligence density to the edge, now open source! It ranks #1 among open-source models under 4B parameters on the @ArtificialAnlys Intelligence Index, with a score of 23. It also scores 20 on the Agentic Index, bringing an early form of general-purpose agent capability to the edge. Across 34 benchmarks, MiniCPM5-2B achieves an average score of 53.9, covering coding, math, long-context understanding, tool use, and agentic tasks. And this release goes beyond the model itself. We’re opening up the data, training recipes, and RL stack behind MiniCPM5-2B. 🤗 Hugging Face: huggingface.co/openbmb/MiniCPM5-2B 💻 GitHub: github.com/OpenBMB/MiniCPM Modelscope: modelscope.cn/models/OpenBMB/MiniCPM5-2B Web:

Terry Tao is probably the most measured, pro-AI mathematician on the planet - which makes this quote especially concerning to read. 😟 If sharing your hunches means getting scooped ~immediately without acknowledgement, then we're going to see not just math but all other science / engineering disciplines go dark.

There is a heated debate right now. Tristan Buckmaster says OpenAI told him its AI had solved the Navier–Stokes Millennium Prize Problem. That claim remains unverified, and the discussions around it have erupted into a dispute over scientific credit. Here is what happened and what we know so far: Several different things are getting mixed together. Here is what the available evidence actually says. Building on work by Córdoba and Martínez-Zoroa, Alpöge and Buckmaster used Claude and OpenAI models to establish how initially smooth fluid flows can develop singularities under smooth external forcing. They released papers and Lean formalizations, and Terence Tao praised the advance. Their results cover Euler and related equations. They do not solve the Navier–Stokes Millennium Problem, which additionally involves viscosity. A suitable extension could resolve it, even with smooth external forcing. Then comes the disputed part. According to Buckmaster, OpenAI told him on September 6 that an internal model had already produced a proof for forced Navier–Stokes, potentially taking that final step. He says OpenAI’s effort began after information about their progress reached the company. He also disputes the initial description of minimal human involvement, reporting that the discussions revealed a team effort, multiple attempts, and substantial compute. Buckmaster further says publication proposals included having him write up OpenAI’s result without Alpöge as a coauthor, with Alpöge’s employment at Anthropic cited as an obstacle. He reports being asked, “Why would you ruin your career?” after saying he would make the circumstances public. Bubeck has publicly rejected allegations against him as “false and inflammatory.” These accounts are contested. The social posts do not establish what happened in the private discussions. There is also no established evidence that OpenAI trained on their private Codex sessions or stole their drafts. Buckmaster raises the question but explicitly writes: “I do not know whether our data was used.” tl;dr Alpöge and Buckmaster used AI to prove new results about how smooth fluid flows can develop singularities, advancing a research program relevant to the Navier–Stokes Millennium Problem. Their published work does not solve that problem, but Buckmaster says OpenAI privately told him its internal model had taken the remaining step. He has not seen that proof, and the claim remains unverified. But rumors are that OpenAI actually fully solved that milleniun problem.