After AlphaGo beat Lee Sedol, a young mechanical engineer at Google thought of another game reinforcement learning could win: energy optimization at data centers. Jim Gao convinced his bosses at the Google data center team to let him work with the DeepMind team to try. The initial pilot resulted in a 40% energy savings and led he and his co-founders to start Phaidra to turn this technology into a product.
Jim discusses the challenges of AI readiness in industrial settings and how we have to build on top of the control systems of the 70s and 80s to achieve the promise of the Fourth Industrial Revolution. He believes this new world of self-learning systems and self-improving infrastructure is a key factor in addressing global climate change.
Hosted by: Sonya Huang and Pat Grady, Sequoia Capital
00:00:00 - Introduction
00:01:50 - What is Phaidra
00:02:20 - “Reinforcement learning plus data centers equals awesome?”
00:05:35 - The three key ingredients for applied reinforcement learning
00:07:19 - The email to Mustafa
00:11:35 - Industrial control systems
00:14:40 - The results at Google
00:17:50 - AI creativity
00:21:33 - The AI readiness journey
00:27:04 - Self-improving infrastructure
00:30:45 - The results of Phaidra’s customers
00:33:50 - Other real world applications of RL
00:37:20 - AI load balancing on the grid
00:41:05 - The intersection of transformers and RL
00:43:51 - Lightning round
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