Thread

1. stratos123 · 1791107241 · focus · HN ↗

   LeCun also said back in 2022 that "if you train a machine, as powerful as it could be, your 'GPT-5000', on text", it will never be able to learn basic common-sense physics like that objects placed on tables will move along with them.

   1. mdp2021 · 1791117069 · focus · HN ↗

      > never be able to learn basic common-sense physics

      And has it at this stage, within in-depth take of said "learning", foundationally?

      I have not been able to properly check the studies for a long time now, but I remain unaware of achieved solutions on the problem of reliably referencing a world model out of a language model - that "counting the 'r's in 'raspberry'" be not guessing, not memory, but actually counting.

      1. Version467 · 1791121712 · focus · HN ↗

         LeCun's argument wasn't about the definition of learning though. He stated that they would never get these common sense things correct because they weren't sufficiently part of the training data. A statement that we can hopefully all agree has been thoroughly refuted.

         1. intended · 1791126331 · focus · HN ↗

            No?

            This is always the issues in the discussions.

            There’s the outcomes camp (objectivists?), which points at the things LLMs can do.

            Then there’s the process methods camp, which talks about what is actually going on.

            If you only care about the outcome, then the process does t matter.

            If you are talking about what is happening, what the underlying mechanics and science of it is, then the process matters.

            These models aren’t thinking. They simulate cognition well enough to do useful work in several fields and domains.

            Both are true.

            1. IshKebab · 1791131534 · focus · HN ↗

               > These models aren’t thinking.

               They are for any definition of the word that makes any kind of sense. I'm sure you have a contorted definition that magically only includes humans though...

               1. intended · 1791139161 · focus · HN ↗

                  [delayed]

                  1. aesthesia · 1791140320 · focus · HN ↗

                     It depends on whether you assume that thinking requires doing everything that humans do. I think it would be silly to say that an AI doesn't think because it doesn't wrinkle its forehead in concentration. So you need to decide which parts of the way that humans think are actually necessary components of the process.

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