Summary of Facebook's Race To Dominate AI

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Pouring time and money into cutting-edge research only to share it openly on the web may seem counterintuitive to many, but Facebook believes it’s how it will beat Google, Apple, Microsoft, and others in the race to “dominate”  artificial intelligence (AI). In this timely article, technology journalist Daniel Terdiman delves deep inside the unique structure of Facebook research and development, which features open-sourcing as a component and strives to balance long-term research with a fast turnaround on products that serve the company’s bottom line. getAbstract recommends this article to R&D trend-watchers and those interested in AI technology.

About the Author

Daniel Terdiman is a Fast Company technology journalist. He has worked at CNET and Ventu reBeat and has written for Wired, The New York Times, Time, and many other publications.



When it comes to a serious commitment to “dominate” artificial intelligence (AI), Facebook arrived late at the party – years behind companies like Google, Apple and Microsoft. Today, Facebook’s two research sectors, headed by Yann LeCun and Joaquin Candela, respectively, have clear-cut goals.  Facebook’s “Artificial Intelligence Research” (FAIR) program works on long-term ideas; the “Applied Machine Learning” (AML) division aims to incorporate AI technology into Facebook’s existing products as quickly as possible.

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