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May 2-4, 2018 - Copenhagen, Denmark
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Thursday, May 3 • 11:10 - 11:45
Building a Go AI with Kubernetes and TensorFlow - Andrew Jackson & Josh Hoak, Google (Beginner Skill Level) (Slides Attached)

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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.
Speakers
avatar for Josh Hoak

Josh Hoak

Software Engineer, Google
Josh has been a software engineer at Google for the last 7 years, the 3 of which have been on Google Kubernetes Engine. Most recently, Josh has led efforts to improve the GKE release systems and provide better reliability for managing GKE's fleet of Kubernetes clusters.
AJ

Andrew Jackson

Software Enginer, Google
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.

minigo slides v3C pdf
Thursday May 3, 2018 11:10 - 11:45 CEST
C1-M5
  Machine Learning & Data, Beginner