Exploring Neural Networks Visually in the Browser

It's good that we get visualization tools to explore artificial neural networks: the problem of "transparency" - understanding what an instance of ANN does instead of remaining a "black box", hence "teaching us something" as opposed to "just somehow working" -, is in fact much reduced when the right visualization - e.g. revealing the patterns that the connectional weights come to identify - is applied.

It is a primary goal to understand what causes an emergence of function. ...Which should be necessary to build (and tweak, and hack, and refine, and export) further. (This point of view should be a basic tenet, yet it does not seem to get the proper focus in this realm.)

Wonderful tool, reminds me of a similar visualization done for an image processing NN:

https://distill.pub/2017/feature-visualization/

It's really incredible to move from a black-box hard-math understanding of NN to something that makes sense to our senses.

Really cool! Love that it's Rust + Webassembly. Also I hadn't encountered the GCU activation, so thanks for that!

Neural networks feel like a type of strange magic, like a hack that shouldn’t work but definitely does. This helps reduce that feeling, in the best way possible.

The wisdom of that curly activation can be debated, since in every extreme-point (horizontal) the gradients are zero, and all activations will eventually be trapped or centered there. Histogram plots can be revealing to understand activations.

Very cool graphics.

I'm not convinced as to the usefulness of the visualizations themselves, but this is a very nice exploration of the space.