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    Technology

    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.

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    Copyright: © Eye On A.I.

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    Latest Episodes:
    Episode 36 - Vittorio Sebastiano Apr 15, 2020
    Show notes

    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.


    Episode 35 - Irina Rish Mar 30, 2020
    Show notes

    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.

    Episode 34 - David Cox Mar 18, 2020
    Show notes

    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 is blending the two traditions in what they call neuro-symbolic AI in hopes to move AI forward.


    Episode 33 - Justin Gottschlich Mar 04, 2020
    Show notes

    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.


    Episode 32 - Casimir Wierzynski Feb 19, 2020
    Show notes

    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.


    Episode 31 - Terry Sejnowski Feb 05, 2020
    Show notes

    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.


    Episode 30 - The 3 Most Interesting Trends In AI Jan 07, 2020
    Show notes

    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.


    Episode 29 - Daphne Koller Dec 11, 2019
    Show notes

    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.


    Episode 28 - Aude Billard Nov 24, 2019
    Show notes

    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.


    Episode 27 - Eric Schmidt and Robert O. Work Nov 04, 2019
    Show notes

    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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