Future of Machine Intelligence

Today O’Reilly released a report on the Future of Machine Intellingence. The concluding chapter is an interview with Matroid. Interviewees in the report:

• Yoshua Bengio
• Benjamin Recht
• Ilya Sutskever
• Reza Zadeh
• Oriol Vinyals
• Risto Miikkulainen
• Daniela Rus
• Anima Anandkumar
• Brendan Frey
• Gurjeet Singh

From the report:

We kick off the series with Anima Anandkumar’s discussion of tensors and their application to machine learning problems in highdimensional space and non-convex optimization. Afterwards, Yoshua Bengio delves into the intersection of Natural Language Processing and deep learning, as well as unsupervised learning and reasoning.

Brendan Frey talks about the application of deep learning to genomic medicine, using models that faithfully encode biological theory. Risto Miikkulainen sees biology in another light, relating examples of evolutionary algorithms and their startling creativity. Shifting from the biological to the mechanical, Ben Recht explores notions of robustness through a novel synthesis of machine intelli‐ gence and control theory. In a similar vein, Daniela Rus outlines a brief history of robotics as a prelude to her work on self-driving cars and other autonomous agents. Gurjeet Singh subsequently brings the topology of machine learning to life.

Ilya Sutskever recounts the mysteries of unsupervised learning and the promise of attention models. Oriol Vinyals then turns to deep learning vis-a-vis sequence to sequence models and imagines computers that generate their own algorithms. To conclude, Reza Zadeh reflects on the history and evolution of machine learning as a field and the role Apache Spark will play in its future.

Thanks to David Beyer for compiling this report.