CGIH: there are compact universal algorithms for predicting stimuli in the real world.
Becoming better at prediction in one domain reliably transfers across several/many/all domains.
This could also be reframed as “there is only one/a few domain(s) under consideration when improving predictive accuracy”
I believe this possibility tends to be contradicted by empiricism, e.g. people practicing one thing do not tend to become better at unrelated things, and AIs tend to be fairly specialized in practice.
The exponential decay to marginal returns on predictive accuracy holds for domains where predictive accuracy is leveraged by actions analogous to betting on the odds implied by credences (e.g. by selling insurance policies).
I think when betting, the value you gain is often based on your difference in ability compared to the person you’re betting with, which in practice would get you a sigmoidal curve, with the inflection point being reached when you’re ~as intelligent as the people you are betting with. So there would be exponential decay to being smarter than humans, but exponential return to approaching human smartness.
EGIH suggests that “superprediction” is:
Infeasible: If one seeks to become exceptional at prediction in n domains, they would have to learn all n domains.
Why is it infeasible to just learn all n domains? Especially for an AI that can presumably be run in parallel.
I believe this possibility tends to be contradicted by empiricism, e.g. people practicing one thing do not tend to become better at unrelated things, and AIs tend to be fairly specialized in practice.
I think when betting, the value you gain is often based on your difference in ability compared to the person you’re betting with, which in practice would get you a sigmoidal curve, with the inflection point being reached when you’re ~as intelligent as the people you are betting with. So there would be exponential decay to being smarter than humans, but exponential return to approaching human smartness.
Why is it infeasible to just learn all n domains? Especially for an AI that can presumably be run in parallel.