Presented By
O’Reilly + Intel AI
Put AI to Work
April 15-18, 2019
New York, NY
Discover opportunities for applied AI
Organizations that successfully apply AI innovate and compete more effectively. How is AI transforming your business?
Be a part of the program—apply to speak by October 16.

Schedule: Reinforcement Learning sessions

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1:45pm5:15pm Tuesday, April 16, 2019
Location: Beekman
Robert Nishihara (UC Berkeley), Philipp Moritz (UC Berkeley), Ion Stoica (UC Berkeley)
Ray is a general purpose framework for programming your cluster. We will lead a deep dive into Ray, walking you through its API and system architecture and sharing application examples, including several state-of-the-art AI algorithms. Read more.
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1:00pm1:40pm Wednesday, April 17, 2019
Implementing AI
Location: Rendezvous
Jian Chang (Alibaba Group), Sanjian Chen (Alibaba Group)
Time series database (TSDB) is of great use for data management in IoT, finance, etc. Performance is always a major optimization point for TSDB. Recently, we introduced neural networks and reinforcement learning to perform mode selection for compression algorithm. Experimental results show one can improve average compression ratio by 20%-120%, comparing with other well-known compression format. Read more.
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1:00pm1:40pm Wednesday, April 17, 2019
Machine Learning, Models and Methods
Location: Regent Parlor
Danny Lange (Unity Technologies)
Join this session to learn how to create artificially intelligent agents that act in the physical world (through sense perception and some mechanism to take physical actions, such as driving a car). Understand how observing emergent behaviors of multiple AI agents in a simulated virtual environment can lead to the most optimal designs and real-world practices. Read more.
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4:05pm4:45pm Wednesday, April 17, 2019
Interacting with AI
Location: Regent Parlor
Kevin He (DEEPMOTION, INC.)
Digital character interaction is hard to fake–whether it’s between two characters, between users and characters, or between a character and its environment. Nevertheless, interaction is central to building immersive XR experiences, robotic simulation, and user-driven entertainment. Kevin He will discuss using physical simulation and deep learning to create interactive character technology. Read more.
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4:55pm5:35pm Wednesday, April 17, 2019
Interacting with AI
Location: Regent Parlor
Paris Buttfield-Addison (Secret Lab Pty. Ltd.), Mars Geldard (University of Tasmania), Tim Nugent (lonely.coffee)
Learn how to use Unity to train, explore, and manipulate intelligent agents that learn. Train a quadruped to walk. Then train it to explore, fetch, and manipulate the world. Games are great places to explore AI. They’re wonderful contained problem spaces. Learn how to use them, even though you’re not a game developer. Read more.
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2:40pm3:20pm Thursday, April 18, 2019
Case Studies, Machine Learning
Location: Sutton South
Alina Matyukhina (Canadian Institute for Cybersecurity)
Machine learning models are often susceptible to adversarial deception of their input at test time, which is leading to a poorer performance. In this session we will investigate the feasibility of deception in source code attribution techniques in real world environment. This session will present attack scenarios on users identity in open-source projects and discuss possible protection methods. Read more.
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4:55pm5:35pm Thursday, April 18, 2019
Models and Methods
Location: Rendezvous
Matthew Reyes (Independent Researcher and Consultant)
This talk considers optimizing preference towards a product on a social network. The model for consumer decision-making is based on the notion of random utility. The contributions of the model are stochastic decisions that will be learned from data, and the inclusion of marketing under the control of individual companies. These contributions enable a reinforcement learning based approach. Read more.