Sramana Mitra: Do you have any thoughts on this problem that is being discussed nowadays? AI is a bit of a black box and all these biases that are creeping into AI are going to drive society in the next several decades. We don’t really have a very good understanding of what really the AI
Steve Scott: With the advent of GPU computing, deep neural nets started to become enabled to the point where you could get good enough performance so that you could really do useful things with them. GPU computing is the application of the processors that were designed for highly parallel tasks of painting triangles on the
Sramana Mitra: Can you give an example? Steve Scott: If you think about deep neural networks in particular, there’s training and there’s inference. Training is the learning part where you take a bunch of data and based on that, you train a model to be able to provide some function. Inference, of course, is using
Steve Scott: The way people have used Cray and other high-performance supercomputers is, you have a bunch of equations that present a model for the natural world whether that’s equation of airflow across an airplane wing or equations dictating the molecular dynamics involved in drug discovery. You iteratively solve these equations spread across these points
Steve takes us deep into the field of high performance computing and how AI is impacting it. Sramana Mitra: Let’s start by having you introduce yourself a little bit as well as Cray’s activities in the domain of AI currently. Steve Scott: I’m the Chief Technology Officer at Cray. I’ve been with Cray most of