Charlie Kawasaki, PacStar
gtc-dc 2019
We’ll show how GPU-accelerated technologies that use AI, machine learning, and video processing have the potential to save lives by improving outcomes and reducing costs of humanitarian and disaster relief operations. However, machine learning and AI architectures haven’t been widely adapted to address the constraints of edge use cases. In-field operations are challenging for communications specialists at the tactical edge due to constraints on the size, weight, and power of equipment. Networks are frequently disconnected, intermittent, and subject to limited bandwidth. We’ll present specific use cases, requirements, and business opportunities for AI, machine learning, and video applications at the edge. Attendees will learn how to deploy their GPU-optimized softwares into network edge markets.