I don’t know enough details about the circuit prior or the NAH to say confidentiality yes or no, but I’d lean no. Bicycles are more modular than addition, but if you feed in the quantum wave function representing a universe filled to the brim with bicycles versus an addition function, the circuit prior will likely say addition is more probable.
Another interesting note: If we’d like a prior such that the best search processes drawn from that prior themselves draw from the prior to resolve search queries, then whatever prior describes the distribution of high-level objects in our universe seems like it has this property.
ie. We can use approximately the same Ockham’s razor when analyzing human brains, and the objects they create, and the physical and chemical processes which produce human brains.
Thanks a lot for the reference, I haven’t came across it before. Would you say that it focuses on gauging modularity?
I don’t know enough details about the circuit prior or the NAH to say confidentiality yes or no, but I’d lean no. Bicycles are more modular than addition, but if you feed in the quantum wave function representing a universe filled to the brim with bicycles versus an addition function, the circuit prior will likely say addition is more probable.
But it would still be interesting to see work on whether a circuit complexity prior will induce more interpretable networks!
Another interesting note: If we’d like a prior such that the best search processes drawn from that prior themselves draw from the prior to resolve search queries, then whatever prior describes the distribution of high-level objects in our universe seems like it has this property.
ie. We can use approximately the same Ockham’s razor when analyzing human brains, and the objects they create, and the physical and chemical processes which produce human brains.