Machine learning is now driving AI, and the first word in Machine Learning is machine. Thus, we need even faster computers to enhance AI, but the slowing of Moore’s Law means conventional machines are barely improving. In order to expand the impact of AI in the cloud and on the edge, we are forced to design machines specifically for AI.
Google is a leader on this new architectural path, with the first of three generations of TPUs deployed in the cloud since 2015.
Machines for the edge also need to be tailored for AI. I’ll describe RISC-V, an architecture developed at the University of California, Berkeley designed to be easy to tailor on the edge that may become as popular for open source hardware as Linux is for open source software. I’ll also explain the role of the new RISC-V International Open Source (RIOS) Lab—based jointly in Berkeley and Shenzehn—in improving and expanding the RISC-V ecosystem.
Professor Emeritus, Professor in the Graduate School, UC Berkeley
David Patterson is the Pardee Professor of Computer Science, Emeritus at the University of California at Berkeley, which he joined after graduating from UCLA in 1976.Dave's research style is to identify critical questions for the IT industry and gather inter-disciplinary groups of... Read More →
Wednesday September 30, 2020 12:00pm - 12:30pm PDT
Virtual
