September 26-27, 2016
New York, NY

Bayesian program learning for the enterprise

Benjamin Vigoda (Gamalon)
4:35pm–5:15pm Tuesday, 09/27/2016
Implementing AI
Location: 3D09 Level: Non-technical
Average rating: ****.
(4.80, 5 ratings)

What you'll learn

  • Understand how Bayesian program learning and probabilistic programming works
  • Discover a variety of emerging software packages for Bayesian program learning and probabilistic programming
  • Description

    Benjamin Vigoda explains how Bayesian program learning can do things that other machine-learning approaches can’t and why it’s especially suited to enterprise data challenges.

    Topics include:

    • An overview of Bayesian program learning and probabilistic programming
    • What it’s good for and how it differs from other forms of AI and ML
    • How to implement it
    • Available (and soon-to-be available) tools
    Photo of Benjamin Vigoda

    Benjamin Vigoda


    Benjamin Vigoda is the CEO of Gamalon Machine Intelligence. Previously, Ben was technical cofounder and CEO of Lyric Semiconductor, a startup that created the first integrated circuits and processor architectures for statistical machine learning and signal processing. The company was named one of the “50 most innovative companies” by Technology Review and was featured in the Wall Street Journal, New York Times, EE Times, Scientific American, Wired, and other media. Lyric was successfully acquired by Analog Devices, and Lyric’s products and technology are being deployed in leading smartphones and consumer electronics, medical devices, wireless base stations, and automobiles. Ben also cofounded Design That Matters, a not-for-profit that for the past decade has helped solve engineering and design problems in underserved communities and has saved thousands of infant lives by developing low-cost, easy-to-use medical technology such as infant incubators, UV therapy, pulse oximeters, and IV drip systems that have been fielded in 20 countries. He has won entrepreneurship competitions at MIT and Harvard and fellowships from Intel and the Kavli Foundation/National Academy of Sciences and has held research appointments at MIT, HP, Mitsubishi, and the Santa Fe Institute. Ben has authored over 120 patents and academic publications. He currently serves on the DARPA Information Science and Technology (ISAT) steering committee. Ben holds a PhD from MIT, where he developed circuits for implementing machine learning algorithms natively in hardware.

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    David Arsenault
    10/12/2016 7:51pm EDT

    please post your slides. thank you.