Date: Thursday, August 20, 2020 Time: 2:00 PM Eastern Daylight Time Sponsor: RambusDuration: 30 MinutesRegister Today!SummaryRising demands of an expanding universe of AI/ML applications is driving exponential growth in the size and sophistication of neural networks. This is putting enormous pressure on computing systems and calls for new architectures and hardware solutions. In part three on an ongoing conversation on AI hardware design, Dr. Steven Woo, fellow and distinguished inventor at Rambus, and William Wong, senior content director and technology editor for Electronic Design, will discuss the latest developments on the frontier of AI/ML and implications for computing architectures supporting training and inference.SpeakersSteve Woo, Fellow and Distinguished Inventor, RambusSteven Woo is a Fellow and Distinguished Inventor at Rambus Inc., working in Rambus Labs on technology and business development efforts across the company. His current focus is on technology and memory systems for accelerators and modern computing infrastructures, including machine learning systems, data centers, and advanced computing systems. Since joining Rambus, Steve has worked in various roles leading architecture, technology, and performance analysis efforts, and in marketing, strategy, and product planning roles. Steve received PhD and MS degrees in Electrical Engineering from Stanford University, and Master of Engineering and BS Engineering degrees from Harvey Mudd College.William Wong, Senior Content Director, Electronic Design EditorBill Wong has been with Electronic Design for 20 years covering a range of topics from test and measurement to embedded systems. He has a Bachelor of Electrical Engineering from Georgia Tech and a Masters of Computer Science from Rutgers University. He has held a number of positions including a Member of the Technical Staff at RCA’s Sarnoff Research Center and Lab Director for PC Magazine.Register
Source: https://www.electronicdesign.com/resources/webcasts/webinar/21136965/evolving-architectures-for-aiml
