Re:Identifying the dimensions used by the primate brain to d...
by reader5000 on Sunday June 04, 2017 @12:38PM
(#14482292)
I 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.
Re:Identifying the dimensions used by the primate brain to d...
by taneq on Sunday June 04, 2017 @02:09PM
(#14482677)
At 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.
Re:Identifying the dimensions used by the primate brain to d...
by bonzini on Sunday June 04, 2017 @03:43PM
(#14483140)
We 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.
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.”