Over the past decade, deep neural networks have proven they can solve a wide range of visual perception problems. Semiconductor companies have invested billions of dollars in developing edge AI processors for deep learning. And thousands of companies have invested in visual AI solutions. Yet, in most industries, visual AI solutions are not widely deployed at scale. Edge AI is mandatory in many applications, due to privacy, reliability, cost, and processing latency concerns. These applications require edge AI processor solutions that support smarter and more efficient SOTA AI algorithms, maintain GPU-like AI accuracy, are easy to use, and deliver high performance with low power consumption. So far, edge AI processors and tools have not satisfied these requirements. This has limited the wider adoption of edge AI. In this talk, we will share DEEPX’s vision of enabling edge AI everywhere and its strategy for enabling this. We will share key innovations that DEEPX has implemented to deliver extreme performance, with GPU-like AI accuracy and flexibility, at price and power consumption levels that will enable edge AI solutions to be deployed at scale across all industries.