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Why I'm still bearish on LLMs after Navier-Stokes

496 points · 653 comments · jaykru

  1. carodgers · · focus · HN ↗
    This April 2026 paper is a fun and related read.

    <a href="https:&#x2F;&#x2F;arxiv.org&#x2F;html&#x2F;2509.24239v4" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;html&#x2F;2509.24239v4

    Researchers asked frontier models to play chess. Have a look at the MAR rates in Table 3. When not explicitly told which moves were legal, no model identified legal moves at a rate better than 80%. Many asked for more illegal moves than legal moves. And even when explicitly told which moves were legal, the models continued to ask for illegal moves. With illegal asks discarded, none of the bots could beat a chess model calibrated to 1100 ELO.

    The author of the originating post says that &quot;current frontier models need laborious oversight and guardrails on even the simplest tasks&quot;, and he&#x27;s absolutely correct.

    1. consensus1 · · focus · HN ↗
      This isn&#x27;t how intelligence works. The LLM may not be able to play chess directly through inference, but it can write a program to do it and execute that program. Same as how human intelligence works. We can&#x27;t fly, but we can build planes.
      1. thesmtsolver2 · · focus · HN ↗
        Human beings can play chess directly without coding up a tool.
        1. jstanley · · focus · HN ↗
          Asking an LLM to play chess by writing algebraic notation is like asking a human to play chess blindfolded.

          Yes some people can do it but most people can&#x27;t even if they&#x27;re unusually intelligent.

          You really need to be giving the LLM a board representation.

          EDIT: I see that they actually were giving the LLMs a board representation and they still played badly. Fair enough then.

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