AnalysisOpinion / analysisReinforcement Learning · Evaluation & Benchmarks · Policy & Regulation1 source · Oct 2, 2026

Don’t be fooled—LLMs don’t reason

AlphaGo won the game, ultimately triumphing 4-1 over Lee Sedol, one of the greatest professional Go players of all time. “I thought AlphaGo was based on probability calculation and that it was merely a machine,” Lee said afterwards. “But when I saw this move, I changed my mind.

Proof1 independent outlet

Key points

  • 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 programming glitch.
  • When Deep Blue defeated then reigning world chess champion Garry Kasparov in 1997, it did so by looking six to eight moves ahead per player and evaluating 200 million chess positions per second, using rules hard-coded by humans.
  • It was actually AlphaGo’s powers of reasoning that made this creative choice—and these are powers that today’s AI lacks.

Sources (1)

  • [1]Don’t be fooled—LLMs don’t reason
    MIT Technology Review (AI) · Oct 2, 08:00 AM
    AlphaGo won the game, ultimately triumphing 4-1 over Lee Sedol, one of the greatest professional Go players of all time. “I thought AlphaGo was based on probability calculation and that it was merely a machine,” Lee said afterwards. “But when I saw this move, I changed my mind.
    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.

Extractive summary: sentences quoted from the sources.

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