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What I like about the flying analogy is that we are not optimising for the same scenarios. You have birds flying 10 000 - 20 000 miles without having to go to e
by kungito 5y ago
What I like about the flying analogy is that we are not optimising for the same scenarios. You have birds flying 10 000 - 20 000 miles without having to go to external shops for service, needing replacement parts and being very energy efficient. Our simpler models optimize for specific scenarios like specific routes with this much fuel and optimizing for specific total cost. I guess your example with neural networks would be AI classifying pictures better than humans which is very specific and I guess achievable with our primitive models.
- filoeleven 5y agoThis is an excellent response! I’d also add that the things we can optimize for are very limited—for both flight and AI—by the current state of materials science. Bird wing mechanics are incredibly complex, and we’re still learning how far that extends. This video[0] shows how the feathers are spread apart and turned to decrease drag on the upstroke, something that we probably couldn’t see before slow-motion video was invented. Even though we know now, we cannot (to my knowledge) create artificial feathers with the same properties as real ones, nor can we build the biomimicry required to make use of them. (Plus, nobody wants to be in a bouncing bird-wing body even for a short flight.) [0] https://youtu.be/4jKokxPRtck https://youtu.be/4jKokxPRtck