> Human brains are very efficient.
At some things, not all.
Subsymbolic systems, such as ANN are clearly good at some things and symbolic systems are better at others.
It is argued that symbolic reasoning is required for what we might call higher levels of intelligence (lets assume this is correct).
Symbolic systems have struggled in the realms of grounding a symbol to something in the physical world, because its messy and complex, i.e. the area where subsymbolic systems play best.
If we assume that ANN are approximately akin to natural brains, then can we take that they are examples of a subsymbolic system able to, with the correct architecture, produce (perhaps the wrong word) a symbolic resoning system?
Perhaps this emergence ontop of the subsymbolic processing is what humans (and others to varying degrees) possess. Perhaps in the past (GOFAI) suffered because it was going top down, or not even going down to subsymbolic to ground the symbols.
Perhaps ANN struggles because its not going up to symbolic reasoning.
Then also perhaps ANN (or organic brains), which evolved where reaction/perception give the critical survival advantage, then only much later did symbolic become possible and beneficial, however wit hardware that wasnt necessarily developed for that in most efficient way.
Being of the belief that ANN are sufficient for AGI (for 20+ years), and possibly offer an elegant solution, I currently think that they are at this time, not the most efficient (nor plausible with the current compute/hardware, or for many years (probably my lifetime)). Practical progress imho is likely in hybridisation of ANN and Logic (however I'm not referring to hand baked rules), and even propose a mixed hardware might even supersede a pure ANN or what evolution has provided in the brain.