Subutai Ahmad : 2013 Plenary Session


Tuesday, April 16, 2013
Location: Fisher Conference Center, Arrillaga Alumni Center

"Automated Streaming Data Analysis: It's Not The Same Game"


We are witnessing an explosion of machine generated data. Every server, every building, every store, every device generates a continuous stream of information that is ever changing and potentially valuable. Most existing big data analytic systems require storing data for later batch analysis and manual modeling by a human expert. This is incredibly inefficient and cannot scale. Instead there is a growing need to rapidly create adaptive models that accept streaming data sources and can take instant action. These use cases impose hard constraints that the fields of Predictive Analytics and Machine Learning have not addressed. The systems must be highly automated, automatically adapt to changing statistics, deal with temporal data, and work well across a wide range of inputs.

In this talk I will go over these issues and their impact on adaptive systems. I will describe a new product, called Grok, designed for streaming analytics. Using Grok, you can deploy learning models on the fly, 100-1000X faster than legacy systems. The models require no human parameter tweaking and adapt continuously. I will describe example applications such as predictive maintenance, energy operations, server capacity planning and online advertising. As the number of data sources grow, and the velocity of data increases, automated learning systems such as Grok will play an increasingly important role in the future of machine learning and big data analytics.


Subutai Ahmad brings experience in real time systems, computer vision and machine learning. At Numenta Subutai oversees technology and product development. Prior to Numenta, Subutai served as VP Engineering at YesVideo, Inc. He helped grow YesVideo from a three-person start-up to a leader in automated digital media authoring. YesVideo's real time video analysis systems have been deployed internationally on a variety of platforms: large scale distributed clusters, retail minilabs, and set-top boxes. Subutai holds a Bachelor’s degree in Computer Science from Cornell University, and a PhD in Computer Science from the University of Illinois at Urbana-Champaign.