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Re:The Limitations of Deep Learning by Klockan on Monday July 17, 2017 @02:32PM (#14791153)
But how does a neuron decide to grow new axons or how to change input weights? Biological neurons does this when solving tasks and not just during training. Isn't it possible that human-like intelligence depends on the network being dynamic? For example, when you play a game for the first time a lot of things suddenly starts to click, couldn't that be the result of new connections forming or at least some weights being changed? If this is true then it would be impossible to create a general game playing AI with human-like performance using our current model.
Re:The Limitations of Deep Learning by bitL on Monday July 17, 2017 @03:47PM (#14791760)
Biological neurons are fundamentally different to models used in deep learning. They can have multiple outputs, can span over whole brain and do local protein-based computations we don't really understand yet. What we have in perceptron is just a very simple model based on what we observed using rudimentary electricity detectors.
Re:The Limitations of Deep Learning by SomeStupidPoint on Monday July 17, 2017 @03:20PM (#14791535)
Don't fully connected layers do exactly what you describe?