Artificial Intelligence for Industry (AI4I) Forum

 Artificial Intelligence for Industry (AI4I) Forum 
May 22, 2019, 1:00 pm - 5:00 pm PDT

Event sponsored and organized by:
IEEE Circuits and Systems Society (CASS)
 Circuits and Systems Society – Santa Clara Valley Chapter (CASS-SCV)
Computer Society (CS)
Computational Intelligence Society (CIS)
Solid-State Circuits Society(SSCS)
Silicon Valley Engineering Council (SVEC)
(Register here)
Wednesday, May 22nd, 2019. 1 PM – 5 PM
1:00 – 1:30 PM Check-in / Networking & Refreshments
1:30 – 2:15 PM Prof. Kurt Keutzer (UC Berkeley)
2:15 – 3:00 PM Prof. Yung-Hsiang Lu (Purdue University)
3:30 – 4:15 PM Dr. Pradeep Dubey (Intel)
4:15 – 5:00 PM TBD
5:00 PM Adjourn
International Technological University, Main Auditorium 2711 N 1st St, San Jose, CA 95134 (between Montague & Trimble along N. 1st Street)
VT Light Rail access from downtown San Jose and Mountain View. In person attendance requested. Maximum capacity: 280. Please register to guaranty seating.
1:30 – 2:15 PM Prof. Kurt Keutzer (UC Berkeley)
TITLE: Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications
ABSTRACT: Deep Learning is arguably the most rapidly evolving research area in recent years. As a result it is not surprising that the design of state-of-the-art deep neural net models proceeds without much consideration of the latest hardware targets, and the design of neural net accelerators proceeds without much consideration of the characteristics of the latest deep neural net models. Nevertheless, we show that there are significant improvements available if deep neural net models and neural net accelerators are co-designed.
2:15 – 3:00 PM Prof. Yung-Hsiang Lu (Purdue University)
TITLE: Low-Power Computer Vision: Status, Challenges, and Opportunities
ABSTRACT: Energy efficiency plays a crucial role in making computer vision successful in battery-powered systems, including drones, mobile phones and autonomous robots. Since 2015, IEEE has been organizing annual competition on low-power computer vision to identify the most energy-efficient technologies for detecting objects in images. The scores are the ratio of accuracy and energy consumption. Over the four years, the winning solutions have improved the scores by a factor of 24. The speaker will describe this competition and summarize the winning solutions, including quantization and accuracy-energy tradeoffs. Based on technology trends, the speaker will identify the challenges and opportunities in enabling energy-efficient computer vision.
3:30 – 4:15 PM Dr. Pradeep Dubey (Intel)
TITLE: AI: What Makes it Hard and Fun!
ABSTRACT: The confluence of massive data with massive compute is unprecedented. This coupled with recent algorithmic breakthroughs, we are now at the cusp of a major transformation. This transformation has the potential to disrupt a long-held balance between humans and machine where all forms of number crunching is left to computers, and most forms of decision-making is left to us humans. This transformation is spurring a virtuous cycle of compute which will impact not just how we do computing, but what computing can do for us. In this talk, I will discuss some of the application-level opportunities and system-level challenges that lie at the heart of this intersection of traditional high-performance computing with emerging data-intensive computing.

4:15 – 5:00 PM TBD 000000000

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