Don’t be fooled—LLMs don’t reason
On an afternoon in Seoul in March 2016, I watched a program I helped build put a stone on the fifth line of a Go board in what looked like a gift to its human opponent. Move 37 in game two of the five-game match looked so absurd that some commentators thought it was a…
Résumé
AlphaGo's breakthrough
In March 2016, the AI program AlphaGo defeated world champion Go player Lee Sedol 4-1 in a five-game match.
Go is a complex board game with more possible moves than atoms in the universe, making traditional brute-force computing impossible.
Move 37 in game two baffled commentators, as it defied human intuition and appeared creative.
However, this move was not pure intuition but the result of AlphaGo's reasoning process.
AlphaGo consists of two systems: a policy network that mimics human-like moves (with a 1 in 10,000 chance of selecting move 37) and a search machinery that explores thousands of future game branches to evaluate consequences.
This split mirrors human cognition, where fast, intuitive thinking (System 1) pairs with slow, deliberate reasoning (System 2).
AlphaGo's victory highlighted the need for AI systems capable of genuine reasoning, not just pattern recognition.
Lire l'analyse complète en 5 points →
Commentaires (0)
Connecte-toi pour commenter
Se connecterAucun commentaire pour le moment.
Voir aussi
Plus de contenus dans cette catégorie →Découvre plus de contenu sur Napseflow
