Ultra-fast AI Inference at the Edge

The age of edge AI inferencing is becoming a commercial reality. Using calibrated and trained models in optimized hardware can shift the inferencing workload from the datacenter to the edge, allowing near real-time object tracking and image recognition in portable devices, robots, drones, and more. By optimizing a deterministic hardware pipeline solution, lower latency and lower power can make the difference in the ability to detect an obstacle or a threat in time to take the appropriate action or to identify defective product moving through an assembly line.

Frank is the CTO of Gigantor Technologies. He is an articulate and inspiring technical and business leader with over 40 years of innovating new products, technologies, and growing successful product lines in the semiconductor industry. Through his company, Kolvenier Solutions, he has helped multiple startup companies with their strategy and technology. He is also a long-time advisor for Silicon Catalyst. As a corporate executive, Frank ran profitable businesses and R&D teams for Microsemi, Zarlink, AMD and more. Starting his career as a circuit designer for Texas Instruments, he is still an engineer at heart. He holds 18 patents and is a published author.