4 ms·

> don't have a shred of intelligence. ... They don't understand, only synthesize from the data they were trained on. Couldn't you say that about 99% of humans

• jryan49 7mo ago
  Yes... maybe not 99%...
• irishcoffee 7mo ago
  The LLM was trained on 100% of humans, the 99% you’re scoffing at is feeding the LLM answers.
  • lateforwork 7mo ago
    100% (or close to it) of material AI trains on was human generated, but that doesn't mean 100% of humans are generating useful material for AI training.
    • coldtea 7mo ago
      Let's train one on just the expert written code and books then, and not the entirety of GitHub or Stack Overflow and such, and see how it fares...
• NewsaHackO 7mo ago
  Yes, and the natural extension is that a lot of what people do day to day is not work-driven by intelligence; it is just reusing a known solution to a presented problem in a bespoke manner. However, this is something that AI excels at.
• chongli 7mo ago
  99% of humans in a particular specialization, sure. It's the 1% who become experts in that specialization who are able to advance the state of the art. But it's a different 1% for every area of expertise! Add it all up and you get a lot more than 1% of humans contributing to the sum of knowledge. And of course, if you don't limit yourself to "advancing the state of the art at the far frontiers of human knowledge" but allow for ordinary people to make everyday contributions in their daily lives, you get even more. Sure, much of this knowledge may not be widespread (it may be locked up within private institutions) but its impact can still be felt throughout the economy.
  • coldtea 7mo ago
    >99% of humans in a particular specialization, sure. It's the 1% who become experts in that specialization who are able to advance the state of the art How? By also "synthesizing the data they were trained on" (their experience, education, memories, etc.).
    • chongli 7mo ago
      No, that's not all we're doing. If that's all humans ever did, we'd still be living in the stone age.
      • sally_glance 7mo ago
        Can we be sure? Maybe it's just very rare for experience, education and memories to line up in exactly the way that allows synthesizing something innovative. So it requires a few billion candidates and maybe a couple of generations too.
        • chongli 7mo ago
          I want to point back to my remark about everyday people. if you don't limit yourself to "advancing the state of the art at the far frontiers of human knowledge" but allow for ordinary people to make everyday contributions in their daily lives, you get even more This isn't a throwaway comment. I do this all the time myself, at work. Everywhere I've worked, I do this. I challenge the assumptions and try to make things better. It's not a rare thing at all, it's just not revolutionary. Revolutions are rare. Perhaps only a handful of them have ever happened in any one particular field. But you simply will not ever go from Aristotelian physics to Newtonian physics to General Relativity by merely "synthesizing the data they were trained on", as the previous comment supposed. Edit: I should also say something about experimentation. You can't do it from an armchair, which is all an LLM has access to (at present). Real people learn things all the time by conducting experiments in the world and observing the results, without necessarily working as formal scientists. Babies learn a lot by experimenting, for example. This is one particular avenue of new knowledge which is entirely separate from experience, education, memories, etc. because an experiment always has the potential to contradict all of that.
• gloosx 7mo ago
  How can you ever say that about humans? Human brain is not trained once on all the data and then you start using it, human brain is constantly training and rewiring in the real time while being used, there is quite a dramatic difference from how LLM transformers work. Human can form new abstractions from sparse experience which is the true conceptual reasoning which LLMs are struggling with