Intel developing 3D Athlete Tracking for Tokyo 2020 Olympics

Okay, so we're thrilled about our partnership with Alibaba, and as Chris said in that video, we've developed a novel technology concept called 3D Athlete Tracking. Unlike the way this is done today, there's no special suits, there's no special sensors here. What we're doing is taking the data from regular cameras. We're applying an AI algorithm, a bunch of compute power, and what you end up with is a super accurate digital model of the athlete's performance. And you can imagine that you could analyze that information in many different ways. It's gonna help the way the audience can experience the Olympic games, in sort of real time, but Also, we're finding that it's going to help the athletes themselves in the process of training for the Olympic Games. So we're working with a number of partners to bring this to life. We're working with Alibaba as you heard about. We're also working with some interesting new companies that I want to tell you about now. We're working with a company called Wrench. This is a computer vision and deep learning software engineering company. And what I'm gonna do is have the CEO of that company, Dr Paul Kruszewski, join me here and tell you a little bit about how we're working together to bring ideas like that to life. So Paul, would you join us please? [APPLAUSE] Good to see you. Thanks. Thanks for coming out. My pleasure. So tell us a little bit about Wrench? So Wrench AI is the world's fastest and most accurate human posed estimation platform which extracts 3D human motion and behavior data from standard video Our train model takes 23 skeletal tracking points from live video in real time which enables us to analyze video data that just wasn't possible before. That's great and I understand you've been using Cascade Lakes And using some of the AI algorithms that you have on that. Tell us about that. Yes, we've been working with some great intel engineers to see just what Zeon processors could do for Wrench AI. I'd like to show you what we've been able to accomplish so far. Uh-huh. What I'm showing Here are two systems running Wrench AI. On the one side is our standard GPU configuration, and on the other side is with the new Intel processors. John, if you can start the demo, we can see how the results stack up. So both systems are now tracking the human movement in the video, on the exact same video. With our current solution on a GPU we're inferencing around 90 frames a second. But on the Cascade Lake platform, optimized with Intel DL Boost, we're inferencing at 450 frames, which just blows my mind. [LAUGH] Now, if my math is right there, that's 5X faster. Is that right? It's 5X and we've only really started. So, there's this perception out there that you need GPUs and that's the only way to do AI. What has your experience been? That was our perception going into this project, felt exactly the same way as everyone else, but The results speak for themselves. It totally changed our mind. I don't think it's any more about CPU versus GPU. The results are fantastic and we're really excited to bring this Xeon Compute to our cloud system. That's awesome. Thank you so much, Paul. We're looking forward to it. A pleasure, thank you. Thanks, thanks a bunch.