- How well is this new need met using current CPU and memory architectures?
- How is the evolving ecosystem for Artificial Intelligence frameworks and Cloud-based AI services impacting device architectures?
- How can the semiconductor community capitalize on opportunities to re-define the semiconductor content?
Smart applications and services drive Artificial Intelligence implementation and machine learning, but the current cloud-centric execution model doesn’t scale: latency, always-on bandwidth requirements and privacy concerns suggest a hybrid architecture. Vendors of many kinds of devices (connected home hubs to smart phones) are planning product roadmaps to implement device-based machine learning, on-board data analytics and monetizeable AI services. Attendees of this session will learn where new semiconductor opportunities lie and how to go after this new market.