Miscellaneous

Building a Go AI with Kubernetes and TensorFlow - Andrew Jackson & Josh Hoak, Google (Beginner Skill Level)

Reinforcement learning approaches can be massively parallelized, so Kubernetes seems like a natural fit, as Kubernetes is all about reducing the overhead for managing applications. However, it can be daunting to wade into Kubernetes and Machine Learning, especially when you add in hardware accelerators like GPUs or TPUs! This talk will break down how you can use Kubernetes and TensorFlow to create, in relatively few lines of code, a tabula rasa AI that can play the game of go, inspired by the AlphaZero algorithm published by Deepmind. This talk will rely on GPUs, TPUs, TensorFlow, KubeFlow, and large-scale Kubernetes Engine clusters.

"About Josh
Josh has been a software engineer at Google for the last 6 years, most recently working on Google Kubernetes Engine. Josh learned to program a decade ago writing python scripts to generate go books, and has been a go enthusiast ever since.

About Andrew
Andrew Jackson currently works on machine learning at Google, previously working on the Google Clips camera. Outside of Google, Andrew Jackson serves on the board of directors of the American Go Association.

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TensorFlow meets Andrew Jackson, one of the authors of MiniGo - an open source, unofficial implementation of AlphaGo Zero that you can find on the TensorFlow GitHub site. Josh Gordon chats with Andrew to learn more about the game of Go, the MiniGo GUI, and a bit about how parts of the algorithm works.

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