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Vol. 2026 · No. 214
Refreshed 7:15 am
Sun · Aug 2 · 2026
The stack 4 picks · curated
01
Simon Willison txt 6 am

Open letters about AI development

Willison walks through the past few weeks of duelling open letters on AI policy. Microsoft shepherded 'Open Weights and American AI Leadership,' signed by 235 companies including NVIDIA, Amazon, Y Combinator and (later) OpenAI, arguing that concentrating capability behind a handful of closed models is itself a single point of failure — and, notably, defending distillation as legitimate model development. Anthropic declined to sign and published its own position three days later, with Dario Amodei calling for a crackdown on industrial-scale distillation while denying he has ever wanted open weights banned.

02
Lobsters txt 16h

Postmortem for Lean kernel soundness bug #14576

On July 25 Ramana Kumar published an AI-assisted, sorry-free 'disproof' of the Collatz conjecture. It wasn't a proof — it exploited a hole in how the Lean kernel handles phantom parameters on nested inductive types, letting an ill-typed term slip past and yield False. Kiran Gopinathan reduced it to a minimal repro on July 28; de Moura shipped a fix an hour after the report. The uncomfortable detail: nanoda, the independent Rust checker people use as a second opinion, had its own unrelated bug, and the proof was built to thread both needles at once.

03
Hacker News txt 75 c · 162 pts

Running Kimi K3 on MI355X at better performance per dollar than B300

Kimi K3 is 2.8T parameters — over 1.5TB of weights before any KV cache, which won't fit on a single B200 node. Wafer benchmarked it on eight AMD MI355X (288GB each, same as a B300) and got 952 tok/s aggregate and 118 tok/s single-stream, versus 498 tok/s across sixteen B200s. A B300 node still wins on raw aggregate by about 1.65x, but costs roughly 2.4x more per GPU-hour, so the MI355X lands at 48 tok/s per dollar against the B300's 33.