Comment by docjay

It’s a lot of fun to compare human and LLM black boxes, but it’s important to keep in mind that we don’t need to know what it is to know what it isn’t, and we can use that to define the edges of the box. We don’t know how either of them work in certain ways, but we know they’re not magic that breaks both thermodynamics and every concept loosely correlated with “entropy” as a topic.

Intelligence requires thought/processing, and I think we can all agree on that part, even if we struggle to define intelligence itself. Increased thought or processing requires increased energy, and the universe agrees on that part. There’s no way around it, that’s the thermodynamics of computation and it holds for biological, digital, and as of yet undiscovered systems used by aliens at the edge of the observable universe. Having information means fighting entropy, and that requires energy. The more, the more.

If you give a dense LLM a 100 token long question about the nature of quantum mechanics or a 100 token long sequence of “-“ and limit it to N token responses to both, it will take exactly the same time and energy to provide both responses. If you resist the urge to turn temperature above 0.0 you’ll also get the exact same response for the same input tokens every time. A deterministic response to external stimulus is typically first broad stroke we use to separate thought capable entities from rocks, but even if we grant LLMs their own unique category of “thinking rock” we can see that prompt complexity and energy required to respond are always constant (per token), so the thermodynamics necessarily means there is not additional thought or computation. Physics demands it. That, again, is a deterministic response.

It has a seemingly endless range of potential responses, but it doesn’t. If you don’t add a random number generator, which is common practice, then you can directly map every possible input to every output. I’m pretty sure that’s why Anthropic removed the ability to change temperature on the latest models. They always forced some amount of non-deterministic responses, but it was a small amount and I actually used that fact to track changes in the model by mapping repeated responses.

Most people actually do have some experience with things that have an astronomical range of possible outputs, a nearly equal number of possible inputs, input and output are directly correlated, and input complexity does not change processing time per input unit. One example is a piano, but we don’t worry about confusing it with a complex note.