alt Hacker NewsI'm not going to stop describing things accurately because someone generated an article that continually undermines its own main point. Limiting the way we talk and think about LLMs to a very narrow set of terms doesn't help us.
EDIT: gentler phrasing
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The distinction I perhaps didn’t make clearly enough is that I’m not really debating the concept of prediction at inference time, although, as I pointed out elsewhere, I think that’s the less interesting interpretation of what “prediction” means.
What’s more interesting to me is its application at training time. In reinforcement learning, there is no ground-truth next token to predict.
So if you’re comfortable calling Deep Blue a “next move predictor,” then I think it’s perfectly consistent to call an LLM a “next token predictor.” But I think it’s more useful to think of Deep Blue as evaluating the value of possible moves. roughly, how likely they are to lead to winning.
And I think effectively the same distinction applies here.
> generated an article that continually undermines its own main point.
I disagree that this accurately describes TFA.