[rdlecler1]

Understanding the recipie and salient ingredients by which nature generates intelligence so that we can build a theory of intelligence is long overdue but they’re starting at too high of a level. We don’t have a good model for artificial neurogenesis that allows us to create complex AI from a simpler set of building blocks, we don’t have a genotype-to-phenotype mapping or a generic representation to encode complex phenotypes in a mathematical genetic abstraction, we don’t have an abstraction by which mutation can create open ended phenotypic variation, we don’t have a model for artificial evolution to drive the evolution of novelty.

If we want to solve this problem we’re going to have to reverse engineer intelligence. Otherwise we’re just going to continue to run into walls by trying to either brute force our way from the ground up and by ignore lessons from biological intelligence or philosophize from the top down.

[azinman2]

What is the “problem?” Depending on what you’re trying to solve, you don’t need to go as low level as possible — it’s likely a mistake as to try and model the universe is a futile exercise.