[datathrow0007]

Not a fan, OP.

No, reducing LLMs to just “statistical text predictor” is an absurdity; but so is leisurely stringing together observations from unstructured experimentation to form a “matter-of-fact” conclusion.

Read the ChatGPT paper and specifically hone in on “transformer” and “input processing” (paraphrased). It will give you a clearer picture of what it actually is, rather than appears to be.

[sebzim4500]

We do not expect just knowing the differential equations governing biological neurons to give us much insight into human intelligence. Why do you think it should be different for artificial ones?

I've read the relevant papers, I've even implemented some of them, and I do not think any of this gave me a better understanding of it's capabilities than playing with it as a black box for a few weeks.

[FPGAhacker]

> We do not expect just knowing the differential equations governing biological neurons to give us much insight into human intelligence.

No, I expect not.

But I think it’s a mistake in thinking and loose use of language to say that differential equations, or any mathematical representation, governs anything. They are models of whatever may actually be happening, and are necessarily modeling a simplification of the behavior observed.

Don’t mistake the model for reality.

[famouswaffles]

There is no "reality" for you either. Everything you perceive is a pleasant model based fabrication of data the brain receives. This is why you see a second tick by faster when you suddenly look at the clock. This is why it seems you see something when you shift your eyes quickly instead of the completely black you should be seeing. This is why most will not see what they should be seeing here - https://www.youtube.com/watch?v=Ahg6qcgoay4

Every memory you store is part-fabrication too. Only what the brain perceives as "key" is stored, scaffolded by made up events. Every memory you retrieve is even more fabrication because the brain rewrites memories every time they're recalled. This is why implanting false memories is extremely easy and why leading questions work so well. https://en.m.wikipedia.org/wiki/Lost_in_the_mall_technique

The vast majority of what you know and perceive was not derived from first principles.

Make no mistake here, you are working off a model of reality too.

[sebzim4500]

Fair enough, but I would argue that even having perfect knowledge of everything happening in a biological neuron down to the quantum level would not help very much when you are trying to understand how the brain makes decisions.

[readyplayeremma]

This is a good overview of a number of emergent things that remain unexplained about the capabilities of some large language models:

https://www.scientificamerican.com/article/how-ai-knows-thin...

You can follow the multitude of things from there to the papers published that describe each of the cases in greater depth.