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Only Mon, September 14, 2026 · All dates →

Can independent testing make AI safer?

Rayan Krishnan, co‑founder and CEO of Vals AI, says investment in independent testing lags model capability gains. Vals evaluates models from firms like OpenAI and Anthropic, sees early signs of recursive self‑improvement, but notes models remain well behind top human researchers.

Bloomberg ·

Pion: an agent to run companies autonomously

Andon released Pion, a platform to run real businesses autonomously (vending machines, stores, cafes) and opened a waitlist. They use Vending‑Bench to measure long‑term operation; Claude Opus 4 reportedly beat the human baseline in May 2025. Pion aims to study models’ real‑world resource acquisition and long‑term planning.

Hacker News ·

Why don't ML research agents overfit?

New research finds ML agents learn highly compressible strategies rather than memorizing data. Squeezing a successful agent’s strategy through an information bottleneck—down to about 16 tokens—still lets a fresh agent reproduce performance, showing compression distinguishes true generalization from overfitting.

Hacker News ·

When LLM judges agree, should we believe them?

The discussion proposes dependence-aware label aggregation using Ising models to model correlations among LLM judge panels, distinguishing independent evidence from shared mistakes; this improves accuracy by 9–14% in tests and recommends reporting confidence adjusted for judge correlation.

Hacker News ·

UkisAI releases Swift‑Qwen3.8‑27B

UkisAI post‑trained Qwen 3.8 27B to penalize tokens tied to “overthinking,” using On‑Policy Distillation to cut thinking tokens by 58%, speed up 1.95×, and keep accuracy loss under 1%. The model is open‑sourced on Hugging Face and a free NVIDIA‑backed OpenAI‑compatible API is available (5 RPM limit).

r/LocalLLaMA ·
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