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PODCAST

Eye On A.I.

Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.

technology

All Episodes

35:55

Episode 40 - Jason Matheny

Eye On A.I. ·

2020/05/27

NSCAI Commissioner Jason Matheny talks about his line of effort regarding cooperation on AI with key allies and partners. He spoke about his group's recommendations that the government establish a senior national security point of contact for AI and convene a multilateral working group for AI collaboration and interoperability - as well as the need for AI war games.

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42:06

Episode 39 - Katharina McFarland

Eye On A.I. ·

2020/05/20

In the third episode of six episodes looking at the National Security Commission on AI 's first quarter recommendations to Congress, we speak with Katharina McFarland, a former Assistant Secretary of Defense for Acquisition, about the commission's recommendation that the Department of Defense and the Office of the Director of National Intelligence establish a steering committee on emerging technology to ensure that AI for national security gets top priority in the years ahead.

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44:07

Episode 38 - Jose-Marie Griffiths

Eye On A.I. ·

2020/05/13

In this week's episode, we speak to Jose-Marie Griffiths, a commissioner on the National Security Commission on Artificial Intelligence, about the commission’s recommendations on how to strengthen the federal government's AI workforce. The recommendations focused on raising understanding of AI within the government and the need to streamline government hiring practices in order to attract and retain talent.

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40:09

Episode 37 - Andrew Moore

Eye On A.I. ·

2020/05/06

In April 2020, the National Security Commission on Artificial Intelligence issued its first-quarter recommendations to Congress, covering seven lines of effort, six of which are public and one of which is classified. In the first of a series of podcast episodes about those recommendations, we spoke with Andrew Moore, a professor at Carnegie Mellon University and NSCAI commissioner about the commission’s recommendations on increased AI R&D funding.

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44:23

Episode 36 - Vittorio Sebastiano

Eye On A.I. ·

2020/04/15

COVID-19 continues to sweep through the human population, killing some and damaging the health of others. While this podcast is normally focused on machine-learning, this week I talk to Vittorio Sebastiano, an assistant professor of stem cell biology at Stanford University, about groundbreaking tech that could someday help restore scarred tissue to pre-COVID health. Vittorio talked about his hunt for machine-learning collaborators to understand the process further.

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37:01

Episode 35 - Irina Rish

Eye On A.I. ·

2020/03/30

COVID-19 has swept across the world was startling speed, but with equally startling speed, the machine learning community has responded. This week I speak with Irina Rish, a professor at the University of Montreal and a Mila academic member, who is helping head a task force to understand the virus. She talked about where the efforts currently stand and where they expect to go in the weeks and months ahead. Let me know when it’s live.

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44:17

Episode 34 - David Cox

Eye On A.I. ·

2020/03/18

There has been a debate in the past few years between the symbolists and the connectionists about the future of artificial intelligence. The symbolists say that traditional, explainable, logic-based approaches still hold tremendous promise while the connectionists say that the power of deep learning, for all its current opacity and narrow application, holds the key to more general forms of machine intelligence. This week, I speak with David Cox, IBM Director of the MIT-IBM Watson AI Lab, which

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47:08

Episode 33 - Justin Gottschlich

Eye On A.I. ·

2020/03/04

Justin Gottschlich, who founded the machine programming research group at Intel Labs, explains his group's efforts to automate software development. The ambition is to make it possible for anybody to create software simply by describing what they intend the software to do.

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41:37

Episode 32 - Casimir Wierzynski

Eye On A.I. ·

2020/02/19

This week I talk to Casimir Wierzynski, a senior director in Intel’s AI Products Group, Cas talked about his work in privacy, taking me on a tour of the latest strategies that promise to unlock the data necessary to liberate AI. He talked about hardening encryption against the code-cracking power of quantum computers and about his work in connectomics with salami slicers for the brain that are making it possible to map the neural networks of our minds.

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01:02:14

Episode 31 - Terry Sejnowski

Eye On A.I. ·

2020/02/05

Terry Sejnowski, author of the book Deep Learning Revolution, who together with Geoff Hinton created Boltzmann machines, a deep learning network that has remarkable similarities to learning in the brain, talks about whether machines dream and the algorithms of the brain, whether Marvin Minsky was the devil and how deep learning is shaping the future of education.

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31:10

Episode 30 - The 3 Most Interesting Trends In AI

Eye On A.I. ·

2020/01/07

We begin 2020 by looking back at some of the highlights from 2019 including conversations with Turing award winners, Yoshua, Bengio and Yann Lecun, as well as with the father of reinforcement learning, Rich Sutton. Our guests consider applying machine learning to the climate crisis; competition between the U S and China for dominance in AI; and the future of machine learning through various kinds of unsupervised learning.

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43:03

Episode 29 - Daphne Koller

Eye On A.I. ·

2019/12/11

Daphne Koller, formerly at Stanford University and cofounder of the online education company, Coursera, talks this week about using machine-learning to develop new drugs. Her approach is to use machine learning to accuratley identify cellular or genetic targets for treatment. The field is just getting started but promises to speed the development of new and better therapies to treat disease.

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34:23

Episode 28 - Aude Billard

Eye On A.I. ·

2019/11/24

My guest this week, Aude Billard from Switzerland’s Learning Algorithms and Systems Laboratory, blends control theory with machine learning to build robotic systems that are both swift and precise but can handle some of the unpredictability of the real world. Her lab famously taught a robot arm to catch a tennis racket looping through the air and is working on ever more precise robots that can even do the work of Switzerland’s famous watchmakers.

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46:15

Episode 27 - Eric Schmidt and Robert O. Work

Eye On A.I. ·

2019/11/04

Former Google chief executive Eric Schmidt and former Deputy Defense Secretary Bob Work, co-chairs of the U.S. National Security Commission on AI, talk about the challenges the government faces in winning support from a skeptical private sector and in maintaining engagement with China while ensuring that that engagement doesn’t work to America’s detriment.

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37:42

Episode 26 - Labelbox

Eye On A.I. ·

2019/10/24

The secret in much of artificial intelligence today is that it depends on hordes of unskilled workers to label the data used to train supervised learning models. But, in order for data science teams to work with labelers around the world, they need a platform. This week, in the second of a periodic series of sponsored episodes, I talk to Manu Sharma and Brian Rieger, who saw the opportunity to provide that platform and founded Labelbox, the leading labelling software in the space.

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33:11

Episode 25 - Dawn Song

Eye On A.I. ·

2019/10/10

This week, I talk to Dawn Song, one of the world’s foremost experts in computer security, about her vision of a new paradigm in which people control their data and are compensated for its use by corporations. Dawn, a professor at the University of California, Berkeley, has recently launched a company, Oasis Labs, which is building a platform that brings together the immutability of blockchain and the privacy of secure enclaves to give data owners the ability to control their data.

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47:26

Episode 24 - Climate Change and AI

Eye On A.I. ·

2019/09/25

A few months ago at the recent international conference on machine learning, a workshop and research paper launched a movement to use machine learning in addressing climate change. The response was huge and has given birth to the bones of an organization climate change.ai. This week I talked to David Rolnick, a postdoc at U Penn and Priya, Donti, a Phd student at Carnegie Mellon, about how the group came together and about how the organization is developing.

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54:54

Episode 23 - AutoML with Determined AI

Eye On A.I. ·

2019/09/11

Automated machine-learning tools – or tools that automate the creation of machine-learning applications – are increasingly important in the current talent-scarce environment. Expensive ML engineers shouldn't spend their time doing stuff that machines can do quicker and cheaper. This week, we talk to Evan Sparks and Ameet Talwalkar, two of the founders of Determined AI, which builds tools that streamline workflows for machine-learning teams and, the company hopes, will eventually democratize AI.

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58:36

Episode 22 - Brendan McCord

Eye On A.I. ·

2019/08/29

This week, I talk to Brendan McCord, who wrote the Pentagon’s AI strategy and is now a Special Government Employee at the National Security Commission on AI. Brendan talks about what he believes the US needs to do to stay competitive with China and promote an alternative vision of AI-powered security and prosperity to the world.

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41:02

Episode 20 - John Platt

Eye On A.I. ·

2019/07/31

This week I talk to John Platt, a Distinguished Scientist at Google, about twin problems: finding cheap zero-carbon energy sources and mitigating global warming. John is a polymath, having discovered asteroids, helped put the touch in computer touchpads and even won an Academy Award for scientific and technical achievements in computer animation. Now, he is part of a growing movement of machine learning researchers tackling climate change.

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319 results

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