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[P] GlyphNet: Training neural networks to communicate with a visual language

[P] GlyphNet: Training neural networks to communicate with a visual language

Visualization of glyphs generated by neural network

I did an experiment over winter break to see what would happen if I trained 2 neural networks to communicate with each other in a noisy environment. The task of the first neural network is to generate unique symbols, and the other’s task is to tell them apart. The result is a pretty cool visual language that looks kind of alien.

Notably, I got the best results by dynamically increasing the noise parameters as the networks became more competent (pulling inspiration from Automatic Domain Randomization and POET).

Please take a look and let me know what you think! https://github.com/noahtren/GlyphNet

submitted by /u/noahtren
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.