Today’s AI platforms are deployed as standalone systems, isolated from the rest of the enterprise. Data scientist develop sophisticated ML/AI models and throw them over the wall to data engineers that struggle with how to collect, maintain and manage volumes of data at ultra-low latencies with little or no context of the underlying technical or business challenge models are designed to solve. My talk will address the key customer requirements to deploy AI- and machine learning-based software for industrial organizations, enabling them to integrate complex data across multiple distributed sources and provide valuable insights to operational professionals required to take the first steps from automation to autonomous systems which we call Adaptive Control.

Anthony Hill is Founder and CEO of Adapdix, a company founded in 2014 with the vision to build a first of its kind edge-optimized data management platform to improve service performance through operationalizing AI/ML. Adapdix’ EdgeOps has become the first low-latency platform deployed at large scale. Previously, he led teams at HPE and Nokia. He holds an MBA from Harvard Business School.