The Asteroids demo is cool too: https://xviniette.github.io/AsteroidsLearning/ https://xviniette.github.io/AsteroidsLearning/ AI Lab at UTexas Austin has more

The Asteroids demo is cool too: https://xviniette.github.io/AsteroidsLearning/ https://xviniette.github.io/AsteroidsLearning/ AI Lab at UTexas Austin has more Atari 2600 NEAT demos as well. The Kung Fu Master "button masher" style makes me think a Street Fighter V agent would be hilarious to see in Human vs AI competitive action! http://www.cs.utexas.edu/~ai-lab/?atari http://www.cs.utexas.edu/~ai-lab/?atari For a proof of concept, this shows the capability of ML in a web browser. Creating an ad hoc cluster of a hundred webrtc peers would yield a formidable (but slow) meta learner. And just to put it in perspective: sentient.ai's petascale darkcycle cluster consists of ~1M CPUs and ~1k GPUs: https://www.sentient.ai/platform/scale/ https://www.sentient.ai/platform/scale/ Distributed computation seems to give natural evolution a competitive advantage: it is by design already parallel. Reference for further study: Evolving Deep Neural Networks https://arxiv.org/pdf/1703.00548.pdf https://arxiv.org/pdf/1703.00548.pdf