Yarin Gal: LLMs are really not good at doing science
yaringal · x · 2026-09-23
Oxford's Yarin Gal argues LLMs are really not good at doing science: even for questions not requiring real-world interaction, give a model a nontrivial research question without scaffolding steering it to the answer and it fails. LLMs optimize well-defined objectives fine, but collapse open-ended problems into known work instead of actually answering them.
Related event: Oxford's Yarin Gal: LLMs are poor at real science without scaffolding(3 posts)→
More from AGI Musings
- Scale AI's Alexandr Wang mocks AI skeptics: ignoring AI's consumer impact 'lacks humility' — alexandr_wang · 2026-09-23
- ARK analyst: AI is the most powerful joule in history, converting energy to GDP ~10x better than humans — DMaguireARK · 2026-09-23
- Google Fellow John Platt: ERA AI scientist grew out of an attempt to automate Kaggle — Latent Space · 2026-09-23
- Snorkel cofounder Alex Ratner: SaaS-to-DaaS shift is more fundamental than most realize — ajratner · 2026-09-23
- Pedro Domingos: the AI pause isn't just wrong, it's unworkable — pmddomingos · 2026-09-23
- Researcher's update: AI ahead of expectations, likely top issue of 2028 US election — Jsevillamol · 2026-09-23