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by danielcasper
19 days ago
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According to a debate I had with Gemini (rofl what an "authoritative statement"), it claimed that LLMs can't get to AGI for three reasons. First, that it has no desire for self-preservation, to which I responded with self-preservation / non-corruption of itself. Arguably enough. Second, that it has no intrinsic motivation, to which I said it can seek to minimize entropy / maximize information gain of the world around us (min/maxing some function built on Information theory) and it relented. But what I can't solve for...LLMs can't learn like people. It is not a 20W piece of wetware running in the real world able to integrate and learn in real-time. It's gotta be batched trained then reinforced. Maybe this is irrelevant if the machine can pretend to be us sufficiently well, but I feel that, in truth, it's not a true AGI until we find a better algo / hardware substrate. Oh...wait a minute...organoids are hitting the market :D |
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