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April 15-18, 2019
New York, NY
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Learning from multiagent emergent behaviors in a simulated environment

Danny Lange (Unity Technologies)
1:00pm–1:40pm Wednesday, April 17, 2019
Machine Learning, Models and Methods
 Location: Regent Parlor
Secondary topics:  Data and Data Networks, Models and Methods, Reinforcement Learning
Average rating: *****
(5.00, 7 ratings)
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Who is this presentation for?

  • Business leaders who need to understand how AI advancements may shape their organizations

Level

Intermediate

Prerequisite knowledge

  • Basic knowledge of machine learning and AI

What you'll learn

  • Understand how emergent behaviors in a multiagent simulated environment can improve efficiencies and best practices in the real world

Description

Traditionally, determining the most efficient designs and practices—whether for determining how store merchandise should be arranged or where people and machines should be laid out in a factory floor—has required vast amounts of data and human assessment. These efficient designs can be the difference between a thriving company and a struggling one. Recent advancements in multiagent reinforcement learning within virtual environments, such as DeepMind’s Capture the Flag or Open AI’s Learning to Compete and Cooperate, have led to a novel approach for tackling efficient design and practices.

Danny Lange explains how observing emergent behaviors of multiple AI agents in a simulated virtual environment can lead to the most optimal designs and real-world practices, all without introducing human bias or the need for vast amounts of data.

Photo of Danny Lange

Danny Lange

Unity Technologies

Danny Lange is the vice president of AI and machine learning at Unity, where he leads multiple initiatives around applied artificial intelligence. Previously, Danny led the efforts to build a highly scalable machine learning platform to support all parts of Uber’s business from the app to self-driving cars as the head of machine learning, provided internal teams with access to machine intelligence and launched an AWS product that offers machine learning as a cloud service to the public as the general manager of Amazon Machine Learning, led a product team focused on large-scale machine learning for big data as principal development manager at Microsoft, was CTO of General Magic, Inc., worked on General Motor’s OnStar Virtual Advisor—one of the largest deployments of an intelligent personal assistant until Siri—as the founder of his own company Vocomo Software, and was a computer scientist at IBM Research. He’s a member of ACM and IEEE Computer Society and has numerous patents to his credit. Danny holds an MS and PhD in computer science from the Technical University of Denmark.

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Picture of Danny Lange
Danny Lange | VICE PRESIDENT OF AI AND MACHINE LEARNING
04/19/2019 7:24am EDT

Link to my presentation: https://www.dropbox.com/s/6p2pjvweums8hr7/OReillyNYC2019.pdf?dl=0

Daniel Castillo | SOLUTIONS ARCHITECT
04/18/2019 1:42am EDT

when will the slides be put up?