In March, an AI event was held at the Computer History Museum entitled --ASICs Unlock Deep Learning Innovation.-- Along with Samsung, Amkor Technology and Northwest Logic, eSilicon explored how these companies form an ecosystem to develop deep learning chips for the next generation of AI applications. There was also a keynote presentation on deep learning from Ty Garibay, CTO of Arteris IP. Over 100 people showed up, including myself, for an afternoon and evening of deep learning exploration and some good food, wine and beer as well. The audience spanned chip companies, major OEMs, emerging deep learning startups and research folks from both a hardware and data science/algorithm point of view.

A lot of the press we see on AI tends to be of the big iron variety recognition algorithms for Facebook images, Google TensorFlow and IBM Watson systems. But AI is already on edge-nodes such as smartphones and home automation hubs, for functions like voice-recognition, facial recognition and natural language understanding. Qualcomm believes there are good reasons for functions like this not only to stay on the edge but to continue to evolve there. I talked with Gary Brotman, director of product management at QTI to understand what s driving this trend. Part of the reason is availability.