The Latest Breakthrough for Natural Language Processing

A Breakthrough for Natural Language

Presented By Ben Vigoda
Ben Vigoda
Ben Vigoda
CEO at Gamalon, Inc.

Ben is the CEO and Founder of Gamalon, Inc. which is pioneering next-generation machine learning and AI technology. He was co-founder and CEO of Lyric, the first microprocessor architectures for statistical machine learning, growing out of Ben's Ph.D. at MIT. Acquired by Analog Devices, Lyric’s technology is widely used in smartphones, cars, telecommunications, and medical devices. With over 120 patents and academic publications, and his work has been featured in the Wall Street Journal, New York Times, Forbes, BusinessWeek, Scientific American, Wired, and other media. Ben co-founded Design That Matters, an NGO that has saved thousands of infant lives by innovating low-cost, easy-to-use incubators, UV therapy, and other medical devices.

Presentation Description

Imagine if we could analyze millions or billions of customer surveys, chat, mobile, social, reviews, support tickets, transcribed voice, and other text sources to understand the bulk of what people are saying, but also respond in a highly personalized way to each unique individual?

Natural language is valuable, but it is complex. With a 1,000 word vocabulary, a 15-word sentence can easily express more than 1e30 (a 1 with 30 zeros) different ideas. Today’s natural language processing is trained to bucket a sentence into one of a few thousand categories. Which also means it only has a few thousand categories of things it can say back to you.

When we simply classify text, we do not really understand it. Getting from 3,000 ideas to 1e30 ideas requires a break-through. This is why today’s AI chatbots feel like talking to a robot. It is also what limits our ability to do data science on a text.

With more than $33 million in funding, including one of the largest machine learning R&D contracts from DARPA over the past four years, Gamalon has developed a platform where models are Turing complete, compositional, transferrable; variables carry uncertainty; back-prop is just the tip of the iceberg; and people meaningfully interact with hidden layers in a model.

The result is Idea Learning, which lets you talk like you are talking to a person. In fact, in the next couple of years, a Gamalon system will be able to carry on a long coherent conversation with another Gamalon system. Today you can use Gamalon’s platform to convert millions or billions of sentences or paragraphs into structured, faceted, JSON that you can use for all sorts of new data science on a text.

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A Breakthrough for Natural Language
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