> But for many purposes you will not find it helpful to think of human beings as bags of chemicals

But when we talk about humans, we're not talking about the chemicals involved in those humans.

When we talk about LLMs, the tokens are the valuable thing they produce for us. We want LLMs because they give us sequences of tokens.

It can be pretty helpful to think of human function in chemical terms. Its at least unhelpful to deny it.

Humans are next state of their local world predictors, given all previous states they are aware of. That's an entirely fair analogy. The reverse analogy for calling a human a bag of chemicals would be calling an LLM a sequence of bytes loaded from disk to memory, the most reductive possible description of any piece of software at all.

To be clear, all life is a next state of the local world predictor. What makes humans somewhat unique among life is we're much better at predicting states of the world neither we nor any of our ancestors have ever experienced, for various reasons such as having the ability to legibly communicate very complicated information strings to each other, being able to build and use tools to record states of the world we can't directly sense.

Similarly, what makes LLMs and multimodal versions of the same architectures "better" than previous generations of electronic predictive models is factors like being able to read and understand roughly the same corpus of data humans have been recording all these millennia, being able to read and remember much more of it than any individual human, and being better at generalizing than other electronic predictive models, but not better than humans. And, of course, they can produce far more predictions in far less time. Frankly, that is probably the key advantage that makes the Hacker News crowd love them so much. They're not any better at predicting byte strings that can be compiled or interpreted into executable code than humans are if you gave both infinite time to do it, but they're a lot faster.