alt Hacker News> For instance, you can learn how much introspection has been trained in during RL,
That's not introspection: that's a simulacrum of it. Introspection allows you to actually learn things about how your mind functions, if you do it right (which I can't do reliably, but I have done on occasion – and occasionally I discover something that's true for humans in general, which I can later find described in the academic literature), and that's something that language models are inherently incapable of. Though you probably could design a neural architecture that is capable of observing its own function, by altering its operation: perhaps a recurrent or spiking neural network might learn such a behaviour, under carefully-engineered circumstances, although all the training processes I know of would have the model ignore whatever signals it was getting from its own architecture.
> all chip analysis, say of an unknown chip, starts with etching away layers
Good luck running any software on that chip afterwards.
Introspection: all heard. As a practical matter, you can rl or prompt inject information about the model into context and most major models do this, not least I expect because they’d like to be able to complain when that output is taken for rl by other model training firms.
I agree that an intermediate non anthropomorphic but still looking at one’s own layers sort of situation isn’t in any architecture I’m aware of right now. I don’t imagine it would add much to a model.
Chip etching: yep. If you’ve never seen an unknown chip analyzed in anger, it’s pretty cool.