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Re:Deep Learning’s Impact on Image Processing, Mathematics, ... by YeGoblynQueenne on Monday May 08, 2017 @07:33AM (#14290718)
It's perfectly possible to train a deep neural model with millions of features that outputs a vector of a handful of values, or even just a scalar. That's actually one of their strengths.

[Full disclosure: that comment was originally mine from a different thread; I'm not affiliated with the OP in any way.]

Re:Deep Learning’s Impact on Image Processing, Mathematics, ... by kefka on Monday May 08, 2017 @08:41AM (#14291003)
Yes indeed. Your comment was sarcastically perfectly succinct and to the point. And it left a mark on me as being the best way to get across this "magic math" stuff encroaching into computer science. It does appear to be a very powerful tool, but with absolutely no introspection or any way to validate or invalidate content. Best one can hope, is that the dataset has no inherent biases ~ but even that's no claim the algo won't create a layer to make the biases, and then directly chose on biases.

I probably should have cited it (was on mobile, but oh well :/ ). Well, I'll do it now: https://news.ycombinator.com/item?id=14219450

If anything, please consider this copy/edit as a sign of respect, and not of mockery :)

Re:Deep Learning’s Impact on Image Processing, Mathematics, ... by YeGoblynQueenne on Monday May 08, 2017 @06:47PM (#14296334)
No worries. It's all good :)
Re:Deep Learning’s Impact on Image Processing, Mathematics, ... by p1esk on Monday May 08, 2017 @11:42AM (#14292553)
Are you confusing parameters with outputs?
Re:Deep Learning’s Impact on Image Processing, Mathematics, ... by YeGoblynQueenne on Monday May 08, 2017 @06:46PM (#14296328)
Well, the numbers you get in the output are function parameters.