Computer pioneer Alan Turing’s remarks in 1950 on the question, “Can machines think?” were misquoted, misinterpreted and morphed into the so-called “Turing Test”. The modern version says if you can’t tell the difference between communicating with a machine and a human, the machine is intelligent. What Turing actually said was that by the year 2000 people would be using words like “thinking” and “intelligent” to describe computers, because interacting with them would be so similar to interacting with people. Computer scientists do not sit down and say alrighty, let’s put this new software to the Turing Test - by Grabthar’s Hammer, it passed! We’ve achieved Artificial Intelligence!

  • deranger@sh.itjust.works
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    1 day ago

    The Chinese room experiment only demonstrates how the Turing test isn’t valid. It’s got nothing to do with LLMs.

    I would be curious about that significant body of research though, if you’ve got a link to some papers.

    • DragonTypeWyvern@midwest.social
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      1 day ago

      No, it doesn’t render the Turing Test invalid, because the premise of the test is not to prove that machines are intelligent but to point out that if you can’t tell the difference you either must assume they are or risk becoming a monster.

      • CheeseNoodle@lemmy.world
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        1 day ago

        Okay but in casual conversation I probably couldn’t spot a really good LLM on a thread like this, but on the back end that LLM is completely incapable of learning or changing in any meaningful way, its not quite a chinese room as previously mentioned but it’s still a set model that can’t learn or understand context, even with infinite context memory it could still only interact with that data within the confines of the original model.

        e.g. I can train the model to understand a spoon and a fork, it will never come up with that idea of a spork unless I re-train it to include the concept of sporks or directly tell it. Even after I tell it what a spork is it can’t infer the properties of a spork based on a fork or a spoon without additional leading prompts by me.

        • Blue_Morpho@lemmy.world
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          21 hours ago

          even with infinite context memory

          Interestingly, infinite context memory is functionally identical to learning.

          It seems wildly different but it’s the same as if you have already learned absolutely everything that there is to know. There is absolutely nothing you could do or ask that the infinite context memory doesn’t already have stored response ready to go.

          • CheeseNoodle@lemmy.world
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            23 minutes ago

            Interestingly, infinite context memory is functionally identical to learning.

            Except for still being incapable of responding to anything not within that context memory, todays models have zero problem solving skills; or to put it another way they’re incapable of producing novel solutions to new problems.

      • deranger@sh.itjust.works
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        1 day ago

        The premise of the test is to determine if machines can think. The opening line of Turing’s paper is:

        I propose to consider the question, ‘Can machines think?’

        I believe the Chinese room argument demonstrates that the Turing test is not valid for determining if a machine has intelligence. The human in the Chinese room experiment is not thinking to generate their replies, they’re just following instructions - just like the computer. There is no comprehension of what’s being said.