> There's no way in hell people can make sense of 19 billion separate concepts. Likely what's going on in the chip is just repeated patterns designed to make a very simple machine operate really really quickly.

You are right about human designed chips. If you use something like simulated evolution or backpropagation or some other techniques from machine learning or mathematical optimization, you can get machines with billions of parts but not necessarily any clear pattern nor repetition.

The human brain might be an example of such a mechanism.

The human brain IS an example of such a mechanism.

We've done it artificially as well with machine learning and genetic algorithms.

The amount of concepts in the neural network of an LLM is too large for us to fully understand.

At best we can only hope to understand these things as a sort of curve fitting optimization problem.

I was using some weasel words, because the human brain does have some structure that we can decipher. Specific injuries to the brain, even in different people, tend to cause the same specific problems. (With heavy emphasis on 'tend to', this is not deterministic, like removing the 'e' key from your keyboard.)

We can do the same with LLMs. We can tease out some macro structure behaviors by looking at intermediate output from the feed forward network.

But you see how this is far from true understanding. It's like removing the WiFi module from a PC and you lose WiFi, therefore you know the WiFi module does WiFi stuff but in the end this action contributes nothing towards cohesive understanding of the PC.