You can implement Doom in a spreadsheet too, so what? That wasn’t the point op or I were making. If you bother to read the sentence before op talks about spreadsheets they are making the conjecture that LLMs are lookup tables operating on the corpus they were trained on. That is the aspect of spreadsheets they were comparing them to, not the fact that spreadsheets can be used to implement anything that any other programming language can. Might as well say they are basically just arrays with some functions in between, yeah no shit.

Which LLMs can’t produce rhyming pairs? Both the current ChatGPT 3.5 and 4 seem to be able to generate as many as I ask for. Was this a failure mode at some point?

I'm not confusing anything. I'm familiar with the Chinese Room Argument and I know how LLMs work.

What I'm saying is arguably philosophically related, in that I'm saying the LLM's model is analogous to the "response book" in the room. It doesn't matter how big the book is; if the book never changes, then no learning can happen. If no learning can happen, then understanding, a process that necessarily involves active reflection on a topic, can exist.

You simply can't say a book "understands" anything. To understand is to contemplate and mentally model a topic to the point where you can simulate it, at least at a high level. It's dynamic.

An LLM is static. It can simulate a dynamic response by having multiple stages that dig through an multiple insanely large books of instructions that cross reference each other and that involve calculations and bookmarks and such to come up with a result--but the books never change as part of the conversation.

> We know definitively that this is not how brains learn.

Ok then, I guess the case is closed.

> an entity needs to be able to form new memories dynamically.

LLMs can form new memories dynamically. Just pop some new data into the context.

> We know definitively that this is not how brains learn.

So you have mechanistic, formal model of how the brain functions? That's news to me.

The problem is that we currently lack good definitions for crucial words such as "understanding" and we don't know how brains work, so that nobody can objectively tell whether a spreadsheet "understands" anything better than our brains. That makes these kinds of discussions quite unproductive.

As the comment I replied to very correctly said, we don’t know how the brain produces cognition. So you certainly cannot discard the hypothesis that it works through “parroting” a weighted average of training data just as LLMs are alleged to do.

Considering that LLMs with a much smaller number of neurons than the brain are in many cases producing human-level output, there is some evidence, if circumstantial, that our brains may be doing something similar.