DeepMind's Nathaniel Daw: the post-training critique has held since ChatGPT
burny_tech · x · 2026-09-27
In the ongoing debate with Melanie Mitchell, DeepMind researcher Nathaniel Daw notes that the shift away from pure next-token prediction via instruction tuning and RLHF has been true for years, at least since ChatGPT — slightly after the stochastic parrots paper, whose authors never retracted their core critique in light of those techniques.
Related event: Melanie Mitchell Sparks Debate: Today's Systems Are Not LLMs(31 posts)→
More from Models
- Running DeepSeek 4.1 locally on an $800 rig with a used RTX 3090 at 2-3 tok/s — LankyGuitar6528 · 2026-11-11
- Google open-sources Harness², an agent that rewrites its own setup per task — Arindam_1729 · 2026-11-11
- Dev dumps Codex desktop app over quality issues, falls back to codex-cli — tekbog · 2026-11-11
- Why do old models get dumber before launches? Lab party, says joking X post — glcst · 2026-11-11
- Grok Bot now detects hidden prompt injections, warns users and refuses to follow them — XFreeze · 2026-11-11
- Shanghai Institute Open-Sources Nex-N2.6, a 321B Multimodal Agentic Model — victormustar · 2026-11-11