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> The amount of non-technical people who have very little intuition around the limitations of LLMs is actually fairly startling Is this surprising though? To b

> The amount of non-technical people who have very little intuition around the limitations of LLMs is actually fairly startling Is this surprising though? To be honest, I don’t think we have any such thing as “AI experts” currently. LeCun, Hinton, etc. were early pioneers in neural networks and Hutter did a lot of the first work with reinforcement learning, but none of these people seem to agree on much now with regard to AGI, and I wouldn’t even say they have any particularly deep insight into LLMs beyond that of a research scientist at OpenAI (perhaps less even, given the time spent on social priorities now). We’re reaching a point where it’s likely that further development just isn’t going to be well-understood by either the general public or the people creating the tech, and this will lead to a lot of “voodoo” explanations of how things work. Progress is increasingly driven by trying things and seeing what works rather than a theory-first approach, and whenever this occurs, a lot of mysticism tends to accompany the process.

hnfong 3y ago
It isn't surprising to the least, and given how little humanity knows about quasi-human level intelligence, I would suggest taking any hard claims about limitations of LLMs with a grain of salt. > Progress is increasingly driven by trying things and seeing what works rather than a theory-first approach, and whenever this occurs, a lot of mysticism tends to accompany the process. This sounds wrong. It sounds as if you're arguing that empiricism and the usual scientific method ends up in mysticism. If it does, maybe the things we're creating should command that respect from us, as much as all other natural phenomena that we don't understand. The traditional idea that many CS experts popularized that computers are just applied maths and you could infer anything on a computer with pure thought is wrong IMHO.
- Xcelerate 3y ago
  > This sounds wrong. It sounds as if you're arguing that empiricism and the usual scientific method ends up in mysticism I think we’re on the same page... I’m arguing that the current approach to creating better LLMs is more akin to an art involving educated guesses and tinkering than it is a hypothesis-driven process with randomized controls (e.g., traditional engineering disciplines or applied physics / chemistry).

hnfong 3y ago

It isn't surprising to the least, and given how little humanity knows about quasi-human level intelligence, I would suggest taking any hard claims about limitations of LLMs with a grain of salt. > Progress is increasingly driven by trying things and seeing what works rather than a theory-first approach, and whenever this occurs, a lot of mysticism tends to accompany the process. This sounds wrong. It sounds as if you're arguing that empiricism and the usual scientific method ends up in mysticism. If it does, maybe the things we're creating should command that respect from us, as much as all other natural phenomena that we don't understand. The traditional idea that many CS experts popularized that computers are just applied maths and you could infer anything on a computer with pure thought is wrong IMHO.

Xcelerate 3y ago
> This sounds wrong. It sounds as if you're arguing that empiricism and the usual scientific method ends up in mysticism I think we’re on the same page... I’m arguing that the current approach to creating better LLMs is more akin to an art involving educated guesses and tinkering than it is a hypothesis-driven process with randomized controls (e.g., traditional engineering disciplines or applied physics / chemistry).