Adversarial Examples That Fool Both Computer Vision and Time-Limited Humans

Re:Adversarial Examples That Fool Both Computer Vision and T... by saagarjha on Monday November 12, 2018 @08:53AM (#18432569)

I’m no machine learning expert, but it seems to me that neural networks just don’t really work like people do, as much as people would like to claim that they’ve created something that works like the human brain.

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Re:Adversarial Examples That Fool Both Computer Vision and T... by red75prime on Monday November 12, 2018 @10:06AM (#18432989)

For me people work unnervingly like neural networks, except for cases where stimuli have gone through slow sequential processing by the entirety of brain computational resources, we call consciousness.

Cached responses, for example. A question in a text form, which includes a clause pointing at a flaw in usual answer, gets the same usual answer.

Effectiveness of pointing and calling technique [0], which forces full conscious attention.

And other results in psychology, which can be explained by artificial neural network level dumbness of some behaviors. (If 7 workers can build 7 cars in 7 days, then how many days would it take 5 workers to build 5 cars? Is Winnie-the-Pooh a boar or a pig?)

[0]: https://en.wikipedia.org/wiki/Pointing_and_calling

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Re:Adversarial Examples That Fool Both Computer Vision and T... by aetherson on Monday November 12, 2018 @10:00AM (#18432953)

Sure. So, then, why did you posit a direct parallel between optical illusions and adversarial images?

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Re:Adversarial Examples That Fool Both Computer Vision and T... by saagarjha on Monday November 12, 2018 @05:59PM (#18436786)

Because that’s another thing I can now mention when people tell me neural networks are like the human brain, since this is an example they often like to bring up.

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