The surge in Edge AI applications has propelled the need for architectures that balance performance, power efficiency, and flexibility. Architectural choices play a pivotal role in determining the success of AI processing at the edge, with trade-offs often necessary to meet the unique demands of diverse workloads. There are… Read More
Always-sensing cameras are a relatively new method for users to interact with their smartphones, home appliances, and other consumer devices. Like always-listening audio-based Siri and Alexa, always-sensing cameras enable a seamless, more natural user experience. However, always-sensing camera subsystems require specialized… Read More
Neural network models are advancing rapidly and becoming more complex. Application developers using these new models need faster AI inference but typically can’t afford more power, space, or cooling. Researchers have put forth various strategies in efforts to wring out more performance from AI inference architectures,… Read More
Often, AI inference brings to mind more complex applications hungry for more processing power. At the other end of the spectrum, applications like home appliances and doorbell cameras can offer limited AI-enabled features but must be narrowly scoped to keep costs to a minimum. New area-optimized AI inference technology from… Read More
