Developing a system that deploys Edge-based AI is the goal for most developers (as opposed to Cloud-based AI), for a host of reasons. It removes latencies associated with sending data off-prem; it increases security because your data always remains on-prem; and it lets you control the complete design and implementation/deployment of the platform. Our experts in this session will show you how to do that and more.
This session is part of our “A.I. in 2025: Shifting from the Whiteboard to Implementation” webinar series. Registration/event page here.
Srinivas, CEO of Pantherun, brings a wealth of experience in cybersecurity, embedded product design, and high-throughput communication, with a career spanning over two decades in the semiconductor and tech industries. A computer science graduate,...
President of the Americas and Chief Commercial Officer, Daedalean
Yemaya Bordain, PhD, is the President of the Americas and Chief Commercial Officer at Switzerland-based Daedalean, a company creating certifiable AI-enhanced automation and autonomy for aviation. Based in the United States, she joined Daedalean in...
Monica Houston leads the AI / ML Applications Team for Tria Americas, where she focuses on enabling machine learning on Tria’s SOMs and developer kits. An avid maker and tinkerer, Monica founded the Seattle Arduino Meetup and was employee #2...