New models, papers, and benchmarks
The Frontier
Mechanistic interpretability has always had a cost problem: explaining a model meant training a second model. A new preprint from IQuest Research and collaborators at Oxford, Stanford, Tsinghua, and the Safe AI Forum argues the circuits are already sitting in the weights — you just have to pull them out. A
The Frontier
Two research stories this morning: World Labs is betting that simulated worlds can replace expensive hardware time in robot training, and a new decomposition method promises to make model interpretability far cheaper. World Labs, the spatial-intelligence startup founded by Fei-Fei Li, says its Real-to-Sim-to-Real
The Frontier
Frontier models can hold their own on math and code, but Moonshot AI's new benchmark suggests most of them still can't reliably see — and what gets blamed as a reasoning failure may actually start at the eyeball. Moonshot AI, the lab behind Kimi, released PerceptionBench, a
The Frontier
A Chinese university team just proved that an open-weight model plus strong agent scaffolding can out-hack the labs that built the models. Fudan University's Whitzard agent jumped to No. 2 globally — and No. 1 among universities — on CyberGym, the AI security benchmark, cracking 91.2% of
The Frontier
Two research stories this morning, one about what open models are trained on, one about what self-improving agents remember. Denmark's Foundation Models project says a 1-billion-parameter model built only on legally clean data goes toe-to-toe with models four times its size, and a
The Frontier
Every leaderboard number carries a quiet question: did the model learn the material, or memorize the exam? A preprint posted to arXiv this week gives auditors a sharper way to tell the difference — one built for the exact regime where today's detectors go blind. A new protocol proposes
The Frontier
The case for letting AI write GPU kernels just met its sharpest audit yet: a new verifier argues that the field's standard correctness test is so loose it waves through broken code most of the time. A team of researchers built a contract-grade verifier for LLM-generated
The Frontier
The "AI does AI research" narrative took a hit from an independent evaluation today, Google quietly made visible AI watermarks optional, and the company pushed encrypted inference a step closer to production. A busy morning for the frontier — and for the people trying to verify its claims. A
The Frontier
Alibaba's Qwen delivered the open-source model the community kept asking for, and Meta's most expensive hire walked out the door — a Friday that splits cleanly into two stories. Alibaba's Qwen open-sourced Qwen3.8-27B on Friday under the permissive Apache 2.0
The Frontier
Two open-weights signals landed within hours of each other: Alibaba pushed the most practical member of its Qwen3.8 family out to the open-source community, and Meta's most expensive hire of the AI talent war walked out the door. Qwen has open-sourced Qwen3.8-27B,
The Frontier
On Wednesday morning Beijing time, Alibaba's Qwen team posted the weights of its most powerful model to Hugging Face on the exact schedule it had signaled two weeks earlier. The download is 4.45 terabytes spread across 213 files — and with it, for the first time, a Max-
The Frontier
An open-weight model is an AI model whose trained parameters — the billions of numbers that encode everything it has learned — are released for anyone to download, run, modify, and build on. The weights are the model: once they are public, the technology itself is out in the world, not