The future of high-performance computing: are neuromorphic systems the answer?

Recording of the webinar that took place on 7 March 2022 at 4 p.m. GMT/5 p.m. CET/8 a.m. PST, exploring where the future of computing lies, brought to you by the IOP Publishing journal, Neuromorphic Computing and Engineering.

Titans of the tech field will go head to head to convince each other of where they believe the future of computing lies.

Neuromorphic Computing and Engineering editorial board members, Kwabena Boahen and Ralph Etienne-Cummings, will attempt to convince Yann LeCun and Bill Dally of the benefits of neuromorphic computing over mainstream neural computing.

We expect this webinar to be a friendly, but no-holds barred debate. Join us to see what side you are on.

About the speakers
Yann LeCun is chief AI scientist at Meta and professor at New York University. An ACM Turing Award laureate for his research on deep learning, Yann also researches computer vision, robotics and computational neuroscience. He does not think that neural computing needs to be neuromorphic to be effective.

Bill Dally is chief scientist at NVIDIA and a professor at Stanford University. With his Stanford team, Bill developed much of the technology that is found in most large parallel computers today and previously made significant advances at MIT and CalTech. He remains to be convinced of the need for neuromorphic computing.

Kwabena Boahen is the founder and director of Stanford’s Brains in Silicon lab. The lab develops silicon integrated circuits that emulate the way neurons compute and computational models that link neuronal biophysics to cognitive behaviour. This bridges neurobiology and medicine with electronics and computer science. Kwabena is a firm believer in the power of neuromorphic computing.

Ralph Etienne-Cummings directs the Computational Sensory-Motor Systems Laboratory at Johns Hopkins University. Ralph’s research spans a range of electrical and computer-engineering topics. Including, but not limited to, mixed-signal VSLI systems, computational sensors, computer vision, neuromorphic engineering, smart structures, mobile robotics and neuroprosthetic devices. His research has convinced him of the need for neuromorphic computing.

Regina Dittmann currently works at the Peter Grünberg Institute, Forschungszentrum Jülich. Since November 2012, Regina has been a professor at RWTH Aachen University, in the Department of Electrical Engineering and Information Technology. She is an expert in the growth and understanding of memristive materials and devices that make modern high-performance computing possible.

Leave a Reply

Your email address will not be published. Required fields are marked *