Off-Line, Off-Policy RL for Real-World Decision Making at Facebook - #448

Off-Line, Off-Policy RL for Real-World Decision Making at Facebook - #448

Today we’re joined by Jason Gauci, a Software Engineering Manager at Facebook AI. In our conversation with Jason, we explore their Reinforcement Learning platform, Re-Agent (Horizon). We discuss the role of decision making and game theory in the platform and the types of decisions they’re using Re-Agent to make, from ranking and recommendations to their eCommerce marketplace. Jason also walks us through the differences between online/offline and on/off policy model training, and where Re-Agent sits in this spectrum. Finally, we discuss the concept of counterfactual causality, and how they ensure safety in the results of their models. The complete show notes for this episode can be found at twimlai.com/go/448.

Jaksot(779)

Can We Train an AI to Understand Body Language? with Hanbyul Joo - TWIML Talk #180

Can We Train an AI to Understand Body Language? with Hanbyul Joo - TWIML Talk #180

In this episode, we’re joined by Hanbyul Joo, a PhD student at CMU. Han is working on what is called the “Panoptic Studio,” a multi-dimension motion capture studio used to capture human body behavio...

13 Syys 201851min

Biological Particle Identification and Tracking with Jay Newby - TWiML Talk #179

Biological Particle Identification and Tracking with Jay Newby - TWiML Talk #179

In today’s episode we’re joined by Jay Newby, Assistant Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. Jay joins us to discuss his work applying d...

10 Syys 201845min

AI for Content Creation with Debajyoti Ray - TWiML Talk #178

AI for Content Creation with Debajyoti Ray - TWiML Talk #178

In today’s episode we’re joined by Debajyoti Ray, Founder and CEO of RivetAI, a startup producing AI-powered tools for storytellers and filmmakers. Deb and I discuss some of what he’s learned in the ...

6 Syys 201855min

Deep Reinforcement Learning Primer and Research Frontiers with Kamyar Azizzadenesheli - TWiML Talk #177

Deep Reinforcement Learning Primer and Research Frontiers with Kamyar Azizzadenesheli - TWiML Talk #177

Today we’re joined by Kamyar Azizzadenesheli, PhD student at the University of California, Irvine, who joins us to review the core elements of RL, along with a pair of his RL-related papers: “Efficien...

30 Elo 20181h 34min

OpenAI Five with Christy Dennison - TWiML Talk #176

OpenAI Five with Christy Dennison - TWiML Talk #176

Today we’re joined by Christy Dennison, Machine Learning Engineer at OpenAI, who has been working on OpenAI’s efforts to build an AI-powered agent to play the DOTA 2 video game. In our conversation we...

27 Elo 201848min

How ML Keeps Shelves Stocked at Home Depot with Pat Woowong - TWiML Talk #175

How ML Keeps Shelves Stocked at Home Depot with Pat Woowong - TWiML Talk #175

Today we’re joined by Pat Woowong, principal engineer in the applied machine intelligence group at The Home Depot. We discuss a project that Pat recently presented at the Google Cloud Next conferenc...

23 Elo 201845min

Contextual Modeling for Language and Vision with Nasrin Mostafazadeh - TWiML Talk #174

Contextual Modeling for Language and Vision with Nasrin Mostafazadeh - TWiML Talk #174

Today we’re joined by Nasrin Mostafazadeh, Senior AI Research Scientist at New York-based Elemental Cognition. Our conversation focuses on Nasrin’s work in event-centric contextual modeling in langua...

20 Elo 201849min

ML for Understanding Satellite Imagery at Scale with Kyle Story - TWiML Talk #173

ML for Understanding Satellite Imagery at Scale with Kyle Story - TWiML Talk #173

Today we’re joined by Kyle Story, computer vision engineer at Descartes Labs. Kyle and I caught up after his recent talk at the Google Cloud Next Conference titled “How Computers See the Earth: A Mac...

16 Elo 201856min

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