The Future of Machine Intelligence

by David Beyer

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

78 pages, ebook

Published February 1, 2016

Reviews

[Abhaga · Rating 2 out of 5]

The book contains short interviews from the 10 leading practitioners of Deep Learning. An interesting snapshot of the kind of things the people at the cutting edge are looking at. It is not a beginners guide or even something that will provide crisp insights. It is the crystal ball gazing, muddy hazy world of cutting edge research. Some of it will pan out, most will not.

[Vinayak Hegde · Rating 3 out of 5]

A variety of perspectives for machine learning and artificial intelligence from different backgrounds and their applications to robotics, genomics and other fields. The short book follows an interview format with 10 practitioners and academicians who work with ML and AI.

[Kate O'Neill · Rating 4 out of 5]

It's a few years old now, but it's still a nice enough survey of expert perspectives on the state of the machine intelligence field as of ~2016 to be worth the quick read. Some useful insights about human perception vs neural networks or deep learning.

[Jeff · Rating 4 out of 5]

We're all going to be obsolete, aren't we. Interesting stuff.

[Robert · Rating 4 out of 5]

While some of the topics covered were over my head, I really enjoyed the format of the interviews and feel like I quickly learned a lot about several leading academic and commercial efforts in machine learning.