The Future of Machine Intelligence

Perspectives from Leading Practitioners

The Future of Machine Intelligence

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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

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David Beyer

David is an investor with Amplify Partners, an early-stage VC focused on the next generation of infrastructure IT, data and information security companies. He began his career in technology as the co-founder and CEO of, a pioneering provider of cloud-based data visualization and analytics. He was subsequently part of the founding team at Patients Know Best, one of the world's leading cloud-based Personal Health Record (PHR) companies.