| HN Mirror

Just like a computer science freshman I imbued computer systems with magic. Oh look I feed this machine numbers and it spits out words (text to speech). Or I search for something and a magic algorithm find me the result. As I learned more about algorithms and data-structures, that magic disappeared. Now I had the same feeling about hardware. This magic black square on the motherboard that can execute a set of couple of hundred or so assembly instructions many billions of times per second. Then I took a hardware architecture class and poof! magic disappeared. We started with transistors and build to designing our own CPU chip.

I am guessing something similar is going on with our understanding of the brain and mind. I think we just haven't figured out a good way to model and represent knowledge. There was terrible optimism at the end of 50s that super human AI will take over in just a decades. But it didn't happen. We have sort of been stomping our feet (I personally don't consider playing chess an AI achievement). I think there will be a breakthrough -- maybe it will be a simple organization of existing ML and knowledge representation methods (neural networks, mixed with evolutionary algorithms) or some new framework - OR - enough of very specific applications (chess playing, image recognition and speech recognition) advanced will slowly chip away at this "magic" AI core until maybe nothing will be left. And we'll look back at that and at our brains and say "ah, it wasn't that complicated after all, it is just all these specific subsystems working together"...