tinyML's Role in Enabling Computer Vision at the Edge – Thought Leaders

Computer vision has great potential to improve our everyday lives – and there are many applications and uses for it. All of these applications use intelligent video analytics, driven by AI and Machine Learning (ML), to watch video, use intelligence to make decisions, and then take action. However, like many AI-driven applications, computer vision needs bursts of computing power, memory, and energy to do its complex analysis and make decisions. While this is fine in a data center with a lot of computer power, it can prevent the move of AI to the edge. Specifically, small devices that are located far from corporate data centers and operate on small batteries need a new breed of AI that is smaller, faster and "lighter" than traditional approaches.