[svantana]

That's not really fair though, since any deterministic function can be "back-propagated" using the chain rule (or even automatic differentiation), even though it's not really necessary for simpler models such as GMM and SVM since there are much easier ways of inspecting them. Also, I don't feel single input/output pairs really describe the function itself -- knowing cos(0) = 1 doesn't reveal much about the cosine function, even though it's a local maximum. Maybe one could extend the technique to show transitions (morphing) between classes as video?

[fugyk]

https://photos.google.com/share/AF1QipPX0SCl7OzWilt9LnuQliat...

[sophcw]

hey, where'd you get that?

[Houshalter]

Here's it applied to each frame of a video https://plus.google.com/photos/+MikeJurney/albums/6161722239...

[RangerScience]

I would absolutely love access to this, but it's showing as locked.

[Houshalter]

There is now a live stream of it producing video: http://www.twitch.tv/317070

[Houshalter]

Looks like they didn't intend to release it to the public. Should have saved it at the time. It was a reaction gif where each frame they applied that algorithm. It was super creepy, with eyeballs appearing and disappearing everywhere.

Perhaps they want to keep it private because they plan to announce more later. So we might see it again.