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Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Ballroom A
On-Device Intelligence
Vikas Chandra · Pete Warden · Ganesh Venkatesh · Yingyan Lin

AI has the potential to transform almost everything around us. It can change the way humans interact with the world by making the objects around them "smart" — capable of constantly learning, adapting, and providing proactive assistance. The beginnings of this trend can already be seen in the new capabilities coming to smartphones (speech assistant, camera night mode) as well as the new class of “smart” devices such as smart watches, smart thermostats, and so on. However, these “smart” devices run much of the computation on the cloud (or a remote host) — costing them transmission power and response latency as well as causing potential privacy concerns. This limits their ability to provide a compelling user experience and realize the true potential of an “AI everywhere” world.

This workshop seeks to accelerate the transition towards a truly “smart” world where the AI capabilities permeate to all devices and sensors. The workshop will focus on how to distribute the AI capabilities across the whole system stack and co-design of edge device capabilities and AI algorithms. It will bring together researchers and practitioners with diverse backgrounds to cover the whole stack from application domains such as computer vision and speech, to the AI and machine learning algorithms that enable them, to the SoC/chip architecture that run them, and finally to the circuits, sensors, and memory technologies needed to build these devices.

Schedule: https://research.fb.com/programs/on-device-intelligence-workshop/#Schedule

Workshop Schedule Highlights

Morning Session: Enabling new experiences on smart devices and agents
Keynote Speaker: Blaise Aguera y Arcas
Speaker Bio:
Blaise leads an organization at Google AI working on both basic research and new products. Among the team’s public contributions are MobileNets, Federated Learning, Coral, and many Android and Pixel AI features. They also founded the Artists and Machine Intelligence program, and collaborate extensively with academic researchers in a variety of fields. Until 2014 Blaise was a Distinguished Engineer at Microsoft, where he worked in a variety of roles, from inventor to strategist, and led teams with strengths in inter­ac­tion design, pro­to­typ­ing, machine vision, augmented reality, wearable com­put­ing and graphics. Blaise has given TED talks on Sead­ragon and Pho­to­synth (2007, 2012), Bing Maps (2010), and machine creativity (2016). In 2008, he was awarded MIT’s TR35 prize.

Afternoon Session: Model, Software and Hardware co-design and optimization
Keynote Speaker: Diana Marculescu
Speaker Bio:
Diana Marculescu is Department Chair, Cockrell Family Chair for Engineering Leadership #5, and Professor, Motorola Regents Chair in Electrical and Computer Engineering #2, at the University of Texas at Austin. Before joining UT Austin in December 2019, she was the David Edward Schramm Professor of Electrical and Computer Engineering, the Founding Director of the College of Engineering Center for Faculty Success (2015-2019) and has served as Associate Department Head for Academic Affairs in Electrical and Computer Engineering (2014-2018), all at Carnegie Mellon University. She received the Dipl.Ing. degree in computer science from the Polytechnic University of Bucharest, Bucharest, Romania (1991), and the Ph.D. degree in computer engineering from the University of Southern California, Los Angeles, CA (1998). Her research interests include energy- and reliability-aware computing, hardware aware machine learning, and computing for sustainability and natural science applications. Diana was a recipient of the National Science Foundation Faculty Career Award (2000-2004), the ACM SIGDA Technical Leadership Award (2003), the Carnegie Institute of Technology George Tallman Ladd Research Award (2004), and several best paper awards. She was an IEEE Circuits and Systems Society Distinguished Lecturer (2004-2005) and the Chair of the Association for Computing Machinery (ACM) Special Interest Group on Design Automation (2005-2009). Diana chaired several conferences and symposia in her area and is currently an Associate Editor for IEEE Transactions on Computers. She was selected as an ELATE Fellow (2013-2014), and is the recipient of an Australian Research Council Future Fellowship (2013-2017), the Marie R. Pistilli Women in EDA Achievement Award (2014), and the Barbara Lazarus Award from Carnegie Mellon University (2018). Diana is a Fellow of both ACM and IEEE.

Important Deadlines
- Submission deadline: Jan 15, 2020
- Paper decision notification: Jan 27, 2020
- Presentation/Poster for accepted submissions: Feb 28, 2020

Enabling new experiences on smart devices and agents (Morning Session)
Imitation Learning from Observation by Prof Peter Stone (Invited Talk)
Model, Software and Hardware Co-optimization (Afternoon Session)
How to Evaluate Deep Learning Accelerators by Prof. Vivienne Sze (Invited Talk)
AutoML for on-device vision by Minxing Tan (Google) (Invited Talk)
TFLite: deploying models on micro controllers by Nat Jeffries (Google) (Invited Talk)
Accepted Papers Poster Session (Poster)