The Killer App for Machine Learning: In Conversation with Pedro Domingos, Head of Machine Learning, D.E. Shaw

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The Killer App for Machine Learning: In Conversation with Pedro Domingos, H

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Best-selling author, Professor of Computer Science at the University of Washington, recent recipient of the prestigious IJCAI John McCarthy Award for excellence in artificial intelligence research (among other awards) and Head of the Machine Learning Research group at D.E. Shaw: Pedro Domingos has one of the most incredible resumes in the world of AI, and we were thrilled to host him for a fireside chat at our most recent Data Driven NYC.
We covered a bunch of things, including why finance is a killer app for machine learning, his much-lauded book, ‘The Master Algorithm’ and what’s truly scary about AI (hint: not the Terminator).
Also finance is incredibly important – “the brain of the economy” – and Pedro wanted his work in machine learning to have impact.
Pedro’s book “The Master Algorithm” takes readers on a journey through the five dominant paradigms of machine learning research on a quest for the master algorithm.
Some of the most prominent supporters of the master algorithm theory have different candidates for which algorithm could be the master – Rich Sutton (for reinforcement learning) and Geoffrey Hinton (for artificial neural networks).
“I hear quite a bit about the inaccurate comparison between humans and machines – we have millions of years of transferred learning through DNA, billions of neuron connections compared to a few for deep learning… – if we only had a few we would be declared brain dead, yet we make this connection?”
– Pedro alluded to this several times in our talk: many of the comparisons people make between humans and AIs are inaccurate in many different ways.
Having said that if you look at the number of connections that the state of the art machine learning systems for some of these problems have, they’re more than many animals – they have many hundreds of millions or billions of connections

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