Every year, customers send and speak millions of messages to companies across multiple channels like email, web chat, phone, and social media. This number is growing rapidly, and the reality is that most messages from customers are left unread. Companies certainly do not currently send a helpful personalized response to every message. Most companies cannot route every message to an appropriate internal department. And in fact, most companies don’t even know the major new categories of feedback they are getting from customers.
Ben Vigoda demonstrates new advances in AI technology that enable companies to accurately read millions of complex customer messages and take action.
This new approach to machine learning, called idea learning, learns 100x faster and can understand complex thought. Idea learning is compositional, enabling developers to build more complex AI from simpler pretrained pieces and compose new probabilistic programs.
Benjamin Vigoda is the CEO of Gamalon Machine Intelligence. Previously, Ben was technical cofounder and CEO of Lyric Semiconductor (acquired by Analog Devices), a startup that created the first integrated circuits and processor architectures for statistical machine learning and signal processing whose products and technology are being deployed in leading smartphones and consumer electronics, medical devices, wireless base stations, and automobiles. 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. 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. Ben holds a PhD from MIT, where he developed circuits for implementing machine learning algorithms natively in hardware.
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