Rafael Harth comments on Humans Consulting HCH

• It seems to me like there are two separate ideas in this post.

One is HCH itself. Actually, HCH (defined as an infinitely large tree of humans) is a family of schemes with two parameters, so it’s really

where is a human, and the amount of time each human has to think. This is impossible to implement since we don’t have infinitely many copies of the same human—and also because the scheme requires that, every time a human consults a subtree, we freeze time for that human until the subtree has computed the answer. But it’s useful insofar as it can be approximated.

Whether or not there exists any human such that, if we set to an hour, has superintelligent performance on a question-answering task is unclear and relies one some version of the Factored Cognition hypothesis.

Separately, the schemes are about implementations, but they still define targets that can only be approximated, not literally implemented.

Taking just the first one—if is a prediction algorithm, then each for can be defined recursively. Namely, we set to be ‘s learned prediction of ‘s output, and to be ‘s learned prediction of ’s output. Each step requires a training process. We could then set , but this is not literally achievable since it requires infinitely many training steps.