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Stochastic Parrots: Frequently Unasked Questions

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Re: Stochastic Parrots: Frequently Unasked Questions

#61

Post by tootie »

aoeusnth1 wrote: post #60
tootie wrote: post #57

Earlier quoted context omitted.

Well this is probably the same kind of semantic trap she's fighting with. Yes, you're right it's a model. The distinction is that they models of _language_ and not thoughts or feelings.

When I read your reply, I’m also modeling language. Tokens are just the discretization of the model’s eyes and ears. My brain does a huge amount of work to represent what’s happening in the world based on discrete information received from the outside world, just like language models do.

Sure but you've also probably formed a model of who I am and what I'm thinking and formulated a response that isn't just grammatical and relevant but designed to provoke an outcome.

Re: Stochastic Parrots: Frequently Unasked Questions

#62

Post by afthonos »

majormajor wrote: post #46
afthonos wrote: post #18

Earlier quoted context omitted.

Nothing about an LLM is “just”. In what precise sense do you mean it is probabilistic?

There's a reason stochastic was used in the original phrase instead of "probabilistic." While most inference executions are intentionally non-deterministic, even a purely deterministic one would still be stochastic in that the model itself was built in a process such that the statistical frequency, sequencing, etc of the training text and followup processes all heavily influence the result. Because of that, the outpu…

Agreed. My point was to question the use of “just“ to obscure an incredibly complicated process, which has been shown repeatedly to rely on generalizations that are indistinguishable from world models.

Now, it is true that the world they’re modeling is the world of tokens. But insofar as those tokens, be they text or images or videos, are themselves modeling the real world, LLMs do have a model of the real world.

Re: Stochastic Parrots: Frequently Unasked Questions

#63

Post by aoeusnth1 »

tootie wrote: post #61
aoeusnth1 wrote: post #60

Earlier quoted context omitted.

When I read your reply, I’m also modeling language. Tokens are just the discretization of the model’s eyes and ears. My brain does a huge amount of work to represent what’s happening in the world based on discrete information received from the outside world, just like language models do.

Sure but you've also probably formed a model of who I am and what I'm thinking and formulated a response that isn't just grammatical and relevant but designed to provoke an outcome.

We're discussing whether they are models or not, not whether they have goals and agency. A language model does form a model of who you are and what you're thinking, because language is causally connected to those aspects of the generating distribution and modeling those aspects reduces cross-entropy.

RL provides the goals and agency. Pretraining provides the model.

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