Don’t be fooled—LLMs don’t reason

MIT Technology Review · 1 week ago · 21

Thore Graepel argues that AlphaGo’s famous move 37 reflected true reasoning from an explicit search over future possibilities, not “intuition” alone, and contrasts this with how today’s large language models generate answers token by token. He says LLM reasoning attempts via techniques like “chain of thought” still rely on the same next-token prediction process and often lack an explicit epistemic state, citing move 37 as a case where the policy ranked it as about a 1 in 10,000 chance. He concludes that trustworthy AI systems need a new machine-reasoning approach modeled on AlphaGo’s architecture, including an auditable state of beliefs that gets updated with evidence rather than post-hoc rationalizations.