Earlier quoted context omitted.
I've long felt that Artificial Life or an approach rooted in that is the best way to get a novel and interesting machine intelligence. The breakthrough with more conventional methods was surprising, but it still seems like it might hit a ceiling (or may have already?). The major thing that's always stumped me is how to design a universal fitness function that can take you from soup to a brain. IRL there is "the envir…
this is my personal take; I agree, for the same reasons you mentioned, resource constraints will need to be baked in (they are already, to some extent, if you consider the constrained resource to be z80-CPU-seconds the program has access to). something more akin to energy in our real world, which can be manipulated, aggregated, shared, pooled, stolen, etc feels more natural, however. imo meaningful intelligence could…
Obviously, you have to "cheat" biology somewhere, we don't have hundreds of millions of years. Neural networks cheat by essentially throwing out the whole evolutionary process and environment that led to the brain, attempting to make a model that works like the brain. IMO that is too much cheating.
Starting with a substrate of random bits of assembly code strikes me as a little too low-level (which is not to dismiss this research at all, I think it's valuable, I'm just spitballing big-picture ideas). Have you considered starting with something like the Unreal or Unity engine, or even Minecraft?
You would lose the elegant and unopinionated search space of all programs, and you would have to engineer a more structured system (kind of like Spore but more simulation than game), but I feel like you might be able to get some more readily relatable behaviors sooner?