Optimizing edge-computing systems with next-generation capabilities and functionalities requires using sensor data where it happens in real-time, whether it's audio, video, pressure, temperature, or humidity, among others. Wearables, trackers, drones, camera systems out in the field, and other systems that monitor, like agriculture or animal tracking. 

For AI to migrate properly into edge environments, we need milliwatt-level, always-on sensing that doesn't force developers to choose between battery life and sophisticated edge performance.

We talked with Mark Goranson, CEO of EMASS, about the company’s flagship ECS-DoT chip. It offers high-performance AI processing for vision, audio, and sensor data directly on-device, maximizing energy efficiency through its RISC-V architecture and non-volatile memory. This always-on intelligence solution is optimized for power- and space-constrained applications where power, latency, and size matter most. 

Built on an event-driven architecture, it operates only when meaningful data is detected, enabling continuous sensing and inference at sub-1-mW power. With less than 10-ms response times and integrated multimodal processing for audio, vision, and sensor data, it delivers high-performance AI without the energy cost of traditional edge solutions.