On a technical level, sure, you could say it's a matter of time, but that could mean tomorrow, or in 20 years.
replyAnd even after that, it still doesn't really solve the intrinsic problem of encoding truth. An LLM just models its training data, so new findings will be buried by virtue of being underrepresented. If you brute force the data/training somehow, maybe you can get it to sound like it's incorporating new facts, but in actuality it'll be broken and inconsistent.
It’s an extremely difficult problem, and if you know how to do that you could be a billionaire.
replyIt’s not impossible, obviously—humans do it—but it’s not yet certain that it’s possible with an LLM-sized architecture.
> It’s not impossible, obviously—humans do it
replyIt's still not at all obvious to me that LLMs work in the same way as the human brain, beyond a surface level. Obviously the "neurons" in neural nets resemble our brains in a sense, but is the resemblance metaphorical or literal?