Chess Study: When Players Spend Thinking Time Is Key to Cheating Detection
TZahavy · x · 2026-09-09
DeepMind researcher Tom Zahavy notes that knowing when to spend time thinking is a huge chess advantage — and the same time-allocation pattern is a primary signal for detecting over-the-board cheating, since unusual think-time distributions at critical moments betray engine assistance.
More from Research
- APEX-Agents 1.1 benchmark update: Claude Fable 5.1 tops leaderboard at 68.6% — amaarora · 2026-09-09
- Edinburgh & ESA build COP-GEN, a latent diffusion model that treats Earth observation as a distribution, not a single prediction — anselm · 2026-09-09
- Cryptographer Matthew Green sits on an AI-assisted ZK result over 'AI slop' writeup — matthew_d_green · 2026-09-09
- Pick embedding models by your use case, not the leaderboard: a practical guide — victorialslocum · 2026-09-09
- Dev reproduces fly simulation in MuJoCo with visual perception and navigation demo — i_dg23 · 2026-09-09
- NVIDIA paper enables cross-model KV cache transfer, skipping prefill 2.7-25x faster than recompute — blaizedsouza · 2026-09-09