Before posting, I roll out another sequence of prediction markets that write instructions for me on what images and links I should use in the post, and where.
Good idea. One could also go Turing machine by Turing machine, voting on the ones which would produce the most upvoted content. Then you can just read the binary output as html.
Prediction market with Solomonoff prior. The theoretically most efficient way to do anything.
(I wonder if we just found a solution to AI alignment. Start with the simplest machines, and let the prediction markets vote on whether they will destroy the world...)
Right, just seed a prediction market maker using a logarithmic scoring rule, where the market’s prior probability is given by Solomonoff. There is the small issue of choosing a Turing interpreter, but I think we just choose the Lisp language as a reasonably elegant one.
Before posting, I roll out another sequence of prediction markets that write instructions for me on what images and links I should use in the post, and where.
Oh, I was going to guess going pixel by pixel, with each separate RGB value as a separate market…
Good idea. One could also go Turing machine by Turing machine, voting on the ones which would produce the most upvoted content. Then you can just read the binary output as html.
Prediction market with Solomonoff prior. The theoretically most efficient way to do anything.
(I wonder if we just found a solution to AI alignment. Start with the simplest machines, and let the prediction markets vote on whether they will destroy the world...)
Right, just seed a prediction market maker using a logarithmic scoring rule, where the market’s prior probability is given by Solomonoff. There is the small issue of choosing a Turing interpreter, but I think we just choose the Lisp language as a reasonably elegant one.
Ah, a sort of multi-modal decision-market-only transformer.