[emaciatedslug]

Just hypothetically speaking could AGI evolve out of a system where several different models trained with highly and intentionally biased data recursively "argue" against each other then use RLHF as a seed to guide the models to find a consensus where the objective is to mimic the Socratic Method? Then synthetically add the consensus to the model retrain and repeat. To me, this dialectal type of strutured language seems to be the basis of how language is the conduit of intelligence. I understand that it really is impossible to know the totality of the inputs for I cannot understand what it is like to understand the math as Terrence Tao does but I could foresee using a system like this which eventually would produce an analogue so close that it would be a building block towards it because to me at least ASI is predicated upon arriving at that one way or another...or would it just arrive at some digital first order logic version of the incompleteness theorm and determine that it's turtles all the way down?

[measured_step]

This is a great idea but it is only possible if the model(s) can actually reason.

Currently, even GPT-4 struggles with: - Scope

- Abduction (compared to deduction and induction which it appears already capable of)

- Out-of-distribution questions

- Knowing what it doesn't know

Etc.

General understanding and in-context learning are incredible, but there are still missing pieces. A council of voices that all have the same blind spots will still get stuck.

[creer]

For one thing, this would help the understandability problem - can the AI explain its reasoning? It would mostly be there in the conversation.

But yeah, three super-human mathematicians arguing some math problem among themselves - at full fiber speed - are not going to be much help to any human.