> deeply unsatisfying to "solve" the problem by blindly copying nature The image that jumped to my mind, was the wing flapping airplane prototypes that, quite

> deeply unsatisfying to "solve" the problem by blindly copying nature The image that jumped to my mind, was the wing flapping airplane prototypes that, quite literally, never got off the ground, and that we all laugh at today. Perhaps, in the end, our solution won't match natures. That also leads me to another thought, which is the definition of the problem. Going back to the airplane. If the problem had been defined as "to build a machine with birdlike agility and control", than we still wouldn't be there. Instead of patting ourselves on the backs, we would still be miserably failing, over 100 years later. But we didn't really need birdlike agility, we just wanted to fly, which, it turns out, is much easier. The problem statement for a lot of AI research seems similarly ambitious. Do we really want to create some sentient being, trapped in a box? Or is what we're really after, a little more practical and obtainable? I think folks like the military, get this. They have a definite objective that they are trying to accomplish. Autonomous desert navigation, autonomous urban navigation, autonomous enemy identification. These are things you can define, measure, and make progress on.