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Interestingly in the article, they try to differentiate the system from machine learning: Advances in machine learning have been made by training a computerize
by supernumerary 9y ago
Interestingly in the article, they try to differentiate the system from machine learning:
Advances in machine learning have been made by training a computerized mimic of a neural network on a given task. Though the networks are successful, they are also a black box because it is hard to reconstruct how they achieve their result.
“This has given neuroscience a sense of pessimism that the brain is similarly a black box,” she said. “Our paper provides a counterexample. We’re recording from neurons at the highest stage of the visual system and can see that there’s no black box. My bet is that that will be true throughout the brain.”
- taneq 9y agoAt this stage I don't think "black box" is a very fair description. We now understand a fair bit about how artificial neural nets encode information and calculate things. And what we don't understand, we can still see and study the processes.
- bonzini 9y agoWe cannot be entirely sure of the behavior in any situation that is sufficiently different from anything that was presented during training. You can't necessarily expect a "common sense" response in that case, and in this sense the neural networks are black boxes.
- taneq 9y agoThe same applies to any complex system. 'Black box' means 'not inspectable', not 'anything which doesn't have predictable behaviour over all conceivable inputs'.
- reader5000 9y agoI believe it is the case that deep NNs at the highest/deepest levels have interpretable feature-specific cells as well. Not sure what they think the difference is.