The challenge isn't creating the "Intelligence" but creating a virtual "Environment" that trains the artificial agent to do tasks that learn and alter its envir

The challenge isn't creating the "Intelligence" but creating a virtual "Environment" that trains the artificial agent to do tasks that learn and alter its environment. With a purely computational environment, all tasks - that can be learned/mastered - can be reduced to basic complexity classes, e.g. prime factorization. To our "natural" intelligence, this seems a contrived skill but consider...better prime factorization would allow the artificial agent to mine all the bitcoins, break passwords, etc making the AI a very rich "in the real world". And compared to a human calculator, even the worst computer looks like a super-intelligence in this domain. So to learn the skills we consider important, there needs to be a way to make the AI experience and alter a non-virtual world - the physical (macro) world we live in…basically some physical robot that does I/O from the environment to the intelligence. And until the AI has some reason to optimize for behavior in the non-virtual world - have the most kids instead of have the most bitcoins -natural and artificial will remain alien to each other as neither will recognize the others' reality. With this insight, I'd diagnose the bottleneck in AI to be in engineering robotics at least as complex as insects, to which we're a long way off.