Ask HN: Can GPT improve itself ala AlphaGo Zero?

Yann LeCun is making the case that generative models are fundamentally divergent: at every token, there is a probability of getting something wrong, and errors accumulate exponentially over the number of generated tokens.

I tend to agree with the premise, however, what if the generative process is overlaid with an "inner debate", as a substitute to having the model play against itself, ala AlphaGo Zero?

The sequence of prompts would go:

1. Please explain X

2. Criticize your explanation for X, use reason and logic.

3. Based on your own critics, improve your explanation of X.

I have manually toyed with this approach (the prompts are longer, you get the gist), and it gives very interesting results. This could lead to GPT re-create, on its own, a better high-quality corpus to learn from.

Is anybody pursuing this approach for LLM?