Natural Language ML for A/B Testing Chat, Email, And Assistant Conversations To Continuously Improve ROI
Natural Language ML for A/B Testing Chat, Email, And Assistant Conversations To Continuously Improve ROI

Abstract: 

Here’s a very important thing that we can’t do machine learning technology: train one model to recognize cats, train a second model to recognize dogs, and then combine them into a single model that recognizes both cats and dogs, and never says that what it sees is both a cat and a dog.

Here’s an even more difficult thing that today’s machine learning cannot do: learn what a paw looks like, learn what a whisker looks like, learn what a tail looks like, and so forth, see one image of a cat, and learn the concept of a cat without any further supervision, come up with its own name for cats, and recognize cats really well after that.

Why can’t we take pre-trained machine learning models and combine them together to make a more sophisticated model that can understand more complicated concepts in data? We need machine learning to be compositional. And to do that, we need a new set of core design principles.

Ben Vigoda will present a compositional machine learning system, demonstrate its power on real world data applications, and envision a future marketplace for pre-trained model components.

Bio: 

Ben is the CEO and Founder of Gamalon. He was previously the co-founder and CEO of Lyric Semiconductor, the first microprocessor architectures for statistical machine learning, growing out of Ben’s PhD at MIT. Lyric was acquired by Analog Devices, and Lyric’s technology is deployed in leading smartphones and consumer electronics, medical devices, wireless base stations, and automobiles. He has authored over 120 patents and academic publications, and his work has been featured in the Wall Street Journal, New York Times, EE Times, Scientific American, Wired, TechCrunch, and other media.

Ben has been an Intel Student Fellow, Kavli Foundation/National Academy of Sciences Fellow, served on the DARPA Information Science and Technology (ISAT) steering committee, and has held research appointments at MIT, Hewlett Packard, Mitsubishi, and the Santa Fe Institute. He also co-founded 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.

Open Data Science

 

 

 

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