6:30PM: Networking, Pizza, and Beverages
7:00PM: Subutai Ahmad, Big Data IoT Presentation
We are witnessing an explosion in the amount of data generated. Every server, every building, and every connected Thing generates a continuous stream of information. Intelligent analysis has the potential for unlocking the tremendous value hidden in this data deluge. Unfortunately traditional machine learning techniques often require batch analysis and manual expert modeling. This is highly inefficient and just cannot scale. Instead, there is a need to rapidly create models that are designed for streaming data. The techniques need to be highly automated and must adapt to continuously changing conditions.
In this talk I will go over these issues and their impact on the analysis of streaming data. I will describe our product, Grok, designed for streaming analytics. Using Grok, you can deploy learning models on the fly[masked]X faster than legacy systems. The models require no human parameter tweaking and adapt continuously. I will describe example use cases such as temporal anomaly detection, predictive modeling, and optimizing resources. As the Internet of Things proliferates and number of data sources grow, 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 Grok Subutai oversees technology and product development. Prior to Grok, 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.