Something about this reminds me of the 'Winning Ticket Hypothesis' in artifical neural networks: that some 'random' initializations prime a network far better for later faster learning. From https://arxiv.org/abs/1803.03635 - the abstract: Neural network pruning techniques can reduce the parameter counts of trained networks by over 90%, decreasing storage requirements and improving computational performance of infere…
> Are these innate patterns of activity priming mammalian brains in a similar way? A newborn foal can stand within 55 minutes of being born and can walk or run within 90 minutes. That is crazy fast training speed. Is it training initialization or is it a form of transfer learning? Most human babies take 9-18 months to walk, and this is commonly attributed to the fact that human babies have immature brains that cannot…
Is it? If we ignore compute requirements, how long would a good algorithm take to learn something like balancing a quadrupedal robot, based on real-time feedback to its outputs? It is a simpler problem, but drone flight software based on learning, can re-learn how to fly a quadcopter after something like losing a propeller and a sudden shift in weight distribution, in a few seconds.
A robot could be built that learns how to adapt to something like a limb being lost or added or half its weight shifted to the other end. It could probably learn an approximate optimal to move under those conditions in just seconds, as well. Though, I suspect that foal might actually be nearly as adaptable. Adult horses, or humans... not so much. We have many overlapping models of how to move, probably. I would take only seconds to adapt to half my weight being added on my shoulders, in the same ballpark as our best robotic systems. But if my left leg grew four inches it would take me a lot longer than the robot to learn and internalize the best way to move again. I could barely keep up with that when it was just a few inches a year when I was a kid.