The Future of Machine Intelligence

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The Future of Machine Intelligence 

Perspectives from Leading Practitioners
By David Beyer

Publisher: O'Reilly
Released: March 2016

Advances in both theory and practice are throwing the promise of machine learning into sharp relief. The field has the potential to transform a range of industries, from self-driving cars to intelligent business applications. Yet machine learning is so complex and wide-ranging that even its definition can change from one person to the next.

The series of interviews in this exclusive report unpack concepts and innovations that represent the frontiers of ever-smarter machines. You’ll get a rare glimpse into this exciting field through the eyes of some of its leading minds.

In these interviews, these ten practitioners and theoreticians cover the following topics:

Anima Anandkumar: high-dimensional problems and non-convex optimization
Yoshua Bengio: Natural Language Processing and deep learning
Brendan Frey: deep learning meets genomic medicine
Risto Miikkulainen: the startling creativity of evolutionary algorithms
Ben Recht: a synthesis of machine learning and control theory
Daniela Rus: the autonomous car as a driving partner
Gurjeet Singh: using topology to uncover the shape of your data
Ilya Sutskever: the promise of unsupervised learning and attention models
Oriol Vinyals: sequence-to-sequence machine learning
Reza Zadeh: the evolution of machine learning and the role of Spark

About the editor: David Beyer is an investor with Amplify Partners, an early-stage VC focused on the next generation of infrastructure IT, data, and information security companies. Part of the founding team at Patients Know Best, one of the world’s leading cloud-based Personal Health Record (PHR) companies, he was also the co-founder and CEO of Chartio.com, a pioneering provider of cloud-based data visualization and analytics.