Self-supervised learning is a widely applicable illustration, it extracts computations from a phenomenon as circuits of a model. So you might hide some details of a crate and ask which principles reconstruct them, some theory of parallelepipeds might be relevant, or material properties of wood. These computations take in a problem statement (context) and then arrive at further facts implied by it.
This doesn’t cleanly extract individual computations, and has trouble eliciting potential computations that don’t manifest in actuality under most circumstances. Presence of more general minds helps with that, humans might be able to represent such facts of potentiality about other things and then write them down, so that the less general self-superwised learning can observe their traces on the web corpus.
Another issue is that this gets to lump together all things from the world, the models learn what the world simulates, not what individual things simulate. This is significant when the things in question are people or civilizations, and understanding them on their own, without distortion from external circumstance, is key to defining respect for their autonomy, or aims and decisions that are their own. (I tried to articulate a related point in this post, though I seem to have failed, since there were multiple convergent objections that missed it. I explain more in my comment replies there.)
Self-supervised learning is a widely applicable illustration, it extracts computations from a phenomenon as circuits of a model. So you might hide some details of a crate and ask which principles reconstruct them, some theory of parallelepipeds might be relevant, or material properties of wood. These computations take in a problem statement (context) and then arrive at further facts implied by it.
This doesn’t cleanly extract individual computations, and has trouble eliciting potential computations that don’t manifest in actuality under most circumstances. Presence of more general minds helps with that, humans might be able to represent such facts of potentiality about other things and then write them down, so that the less general self-superwised learning can observe their traces on the web corpus.
Another issue is that this gets to lump together all things from the world, the models learn what the world simulates, not what individual things simulate. This is significant when the things in question are people or civilizations, and understanding them on their own, without distortion from external circumstance, is key to defining respect for their autonomy, or aims and decisions that are their own. (I tried to articulate a related point in this post, though I seem to have failed, since there were multiple convergent objections that missed it. I explain more in my comment replies there.)