McGill AI Podcast

McGill AI Podcast

By Ramatoulaye Balde, Danyl SatanovskyiScience
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McGill AI Podcast episodes

  • Blake Richards: Parallels Between the Brain & AI

    Professor Blake Richards is a leading researcher at the intersection of neuroscience and AI. He is an assistant professor at McGill, a Canada CIFAR AI Chair, and a core faculty member at Mila. His research explores the general principles of learning and memory in neural networks and tries to understand how real and artificial brains can optimise behaviour.


    44 min
  • Episode 2: Blake Richards

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    HECTIC FIRST WEEK OF SCHOOL? REFRESH YOURSELF WITH MCGILL AI PODCAST’S EPISODE 2 WITH BLAKE RICHARDS, NOW AVAILABLE ON ALL PLATFORMS! 🥶🥶

    Professor Blake Richards is a prominent researcher whose work bridges the gap between neuroscience and artificial intelligence. He is an Associate Professor at McGill University, holding appointments in both the School of Computer Science and the Department of Neurology and Neurosurgery. Additionally, he serves as a Core Faculty Member at Mila (the Quebec Artificial Intelligence Institute) and is a Research Scientist Manager with the Paradigms of Intelligence team at Google.

    44 min
  • David Rolnick: AI for Climate Change

    Professor David Rolnick is an assistant professor at McGill, Canada CIFAR AI Chair, Mila researcher and a member of MIT Technology Review’s 35 Innovators Under 35. He joins the podcast to talk about how machine learning can be applied to tackling climate change, deep learning theory, AI in the public sector, ethics and advice for students.

    1 hr 3 min
  • Episode 1: David Rolnick

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    Professor David Rolnick!
    Professor Rolnick is an Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and at Mila. He also serves as the co-founder and chair of Climate Change AI and the scientific co-director of Sustainability in the Digital Age.

    “Certainly, this kind of thinking is not being taught to people sufficiently well. It’s not being taught to people at the level of how can you shape your algorithms to make them have the desired effect to be as beneficial as possible for society. It’s also not being taught to people in terms of you choosing the problems that you work on, and choosing not to work on certain problems at all. Certain things should not have AI.”

    59 min

About McGill AI Podcast

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There are very few places in the world like Montreal and McGill which have such a concentration of talent in the field of AI/ML. MAIS primarily serves to build a community with a shared passion for…