Re:Language models can explain neurons in language models
by VictorLevoso on Tuesday May 09, 2023 @05:05PM
(#35880389)
All programs that you can fit on a computer can be described by a sufficiently large Markov chain(if you imagine all the possible states the memory as nodes)
Whatever the human brain is doing is also describable as a massive Markov chain.
But since the markov chain becomes exponentially larger whit the amount of states this is a very nitpicky and meaningless point.
Clearly to say something its a markov chain and have that mean something you need to say the thing its doing could be more or less compressed to a simple markov chain for bigrams or something like that, but that is just not true empirically, not even for gpt2. Just this is already pretty hard to make into a reasonable size markov chain https://arxiv.org/abs/2211.00593.
Just saying that it outputs probabilities from each state is not enough, the states are english strings, there's (number of tokens)^contex_lenght possible states for a certain length that's not a reasonable markov chain that you could actually implement or run.
But since the markov chain becomes exponentially larger whit the amount of states this is a very nitpicky and meaningless point.
Clearly to say something its a markov chain and have that mean something you need to say the thing its doing could be more or less compressed to a simple markov chain for bigrams or something like that, but that is just not true empirically, not even for gpt2. Just this is already pretty hard to make into a reasonable size markov chain https://arxiv.org/abs/2211.00593.
Just saying that it outputs probabilities from each state is not enough, the states are english strings, there's (number of tokens)^contex_lenght possible states for a certain length that's not a reasonable markov chain that you could actually implement or run.