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Which makes the compelling results of deep networks even more mysterious. (https://gandissect.csail.mit.edu/ https://gandissect.csail.mit.edu/) How could we hav
by lucidrains 8y ago
Which makes the compelling results of deep networks even more mysterious. (https://gandissect.csail.mit.edu/ https://gandissect.csail.mit.edu/) How could we have captured the seemingly enormously complex act of visual object recognition, with all the neurons and synapses and chemicals, in something so crude and simple as backpropagation and stochastic gradient descent with a bunch of ones and zeros? Or perhaps both processes, biological and artificial, point to a more fundamental emergent phenomenon of the computational universe we inhabit?
- scottlocklin 8y agoI'm pretty sure if you threw the number of grad students and GPUs at PGMs or various ensemble techniques, the results wouldn't be very different. Fundamentally prediction as we do it is just a form of data compression. I don't think brains work in a way we understand at all (though pieces like visual cortex are well understood).
- deleted 8y ago[deleted]