Existing deep learning technologies require large labeled training sets, which take time and money to create. Ben Vigoda introduces a new approach to deep learning called idea learning, which focuses on teaching machines concepts rather than the pattern matching approach utilized by traditional machine learning techniques. By communicating ideas using probabilistic programming techniques, machine learning systems become more flexible, transparent, and auditable.
Ben explains how idea learning can be applied to enterprise datasets and how companies can use it to improve customer experience, resulting in higher revenue and customer retention.
Ben will also have an exciting announcement to share.
Benjamin Vigoda is the CEO of Gamalon. 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, and a cofounder of 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. Lyric Semiconductor 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 has won entrepreneurship competitions at MIT and Harvard and fellowships from Intel and the Kavli Foundation and 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’s serving 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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