alt Hacker NewsYour examples are not LLMs, though, and don't really behave like them at all. If we take the chess analogy and design an "LLM-like chess engine", it would behave like an average 1400 London spammer, not like Stockfish, because it would try to play like the average human plays in it's database.
It isn't entirely clear what problem LLMs are solving and what they are optimizing towards... They sound humanlike and give some good solutions to stuff, but there are so many glaring holes. How are we so many years and billions of dollars in and I can't reliably play a coherent game of chess with ChatGPT, let alone have it be useful?
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>because it would try to play like the average human plays in it's database.
Why would it play like the average? LLMs pick tokens to try and maximize a reward function, they don't just pick the most common word from the training data set.
Maybe you didn't realise that LLMs have just wiped out entire class of problems, maybe entire disciplines- do you remember "natural language processing"? What, ehm, happened to it?
Sometimes I have the feeling that what happened with LLMs is so enormous that many researches and philosophers still haven't had time to gather their thoughts and process it.
I mean, shall we have a nice discussion about the possibility of "philosophical zombies"? On whether the Chinese room understands or not? Or maybe on the feasibility of the mythical Turing test? There's half a century or more of philosophical questions and scenarios that are not theory anymore, maybe they're not even questions anymore- and almost from one day to the other.