Earlier quoted context omitted.
> 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 rega…
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…
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).