We fed all of human knowledge into the system and now we can just decompress bit by bit. Issue is the moment ai is fed the ai stuff it’s like that meme jpeged ten times. It’s getting so bad you can not even understand it anymore.

AI is just a thought compression algorithm and can not come up with new ideas.

  • turdas@suppo.fi
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    9 days ago

    You clearly have absolutely no idea how LLMs work, so I’m looking forward to your explanation of how they have been able to solve novel problems that have eluded humans for decades. Say, these:

    And since OP wasn’t talking about LLMs but AI in general, it would be remiss to not mention AlphaFold.

    • Alex@lemmy.ml
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      9 days ago

      In the Stokes case a number of researchers that where close to the solution suspect OpenAI was reading their homework.

      LLM’s certainly have the capability of extracting novel correlations from their vast training sets. But whether that really counts as “new thinking” remains to be seen.

    • rockerface🇺🇦@lemmy.cafe
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      9 days ago

      LLMs had been used to solve problems as tools long before corporations started shoving it down our throats. That’s doesn’t give it some magical self awareness or ability to innovate. It was able to do all the things you linked because of people that know how to use it.

      • turdas@suppo.fi
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        9 days ago

        LLMs had been used to solve problems as tools long before corporations started shoving it down our throats.

        [citation needed]. LLMs didn’t exist “long before” corporations started shoving them down our throats. GPT-1 only came out in 2018 and the paper that invented the architecture was released in 2017. And they were pretty useless until like 2022 or 2023.

    • TryingSomethingNew@sopuli.xyz
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      9 days ago

      On a couple of those, it’s because the scientists involved had been using LLMs in their work and it scooped them because it knew where to look. IIRC the consensus in the field had been that computer time would have been required.