Yoshua Bengio: The Past, Present, and Future of Deep Learning

Yoshua Bengio: The Past, Present, and Future of Deep Learning

Author: Daniel Bashir November 21, 2022 Duration: 1:14:09

Happy episode 50! This week’s episode is being released on Monday to avoid Thanksgiving.

Have suggestions for future podcast guests (or other feedback)? Let us know here!

In episode 50 of The Gradient Podcast, Daniel Bashir speaks to Professor Yoshua Bengio.

Professor Bengio is a Full Professor at the Université de Montréal as well as Founder and Scientific Director of the MILA-Quebec AI Institute and the IVADO institute. Best known for his work in pioneering deep learning, Bengio was one of three awardees of the 2018 A.M. Turing Award along with Geoffrey Hinton and Yann LeCun. He is also the awardee of the prestigious Killam prize and, as of this year, the computer scientist with the highest h-index in the world.

Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter

Outline:

* (00:00) Intro

* (02:20) Journey into Deep Learning, PDP and Hinton

* (06:45) “Inspired by biology”

* (08:30) “Gradient Based Learning Applied to Document Recognition” and working with Yann LeCun

* (10:00) What Bengio learned from LeCun (and Larry Jackel) about being a research advisor

* (13:00) “Learning Long-Term Dependencies with Gradient Descent is Difficult,” why people don’t understand this paper well enough

* (18:15) Bengio’s work on word embeddings and the curse of dimensionality, “A Neural Probabilistic Language Model”

* (23:00) Adding more structure / inductive biases to LMs

* (24:00) The rise of deep learning and Bengio’s experience, “you have to be careful with inductive biases”

* (31:30) Bengio’s “Bayesian posture” in response to recent developments

* (40:00) Higher level cognition, Global Workspace Theory

* (45:00) Causality, actions as mediating distribution change

* (49:30) GFlowNets and RL

* (53:30) GFlowNets and actions that are not well-defined, combining with System II and modular, abstract ideas

* (56:50) GFlowNets and evolutionary methods

* (1:00:45) Bengio on Cartesian dualism

* (1:09:30) “When you are famous, it is hard to work on hard problems” (Richard Hamming) and Bengio’s response

* (1:11:10) Family background, art and its role in Bengio’s life

* (1:14:20) Outro

Links:

* Professor Bengio’s Homepage

* Papers

* Gradient-based learning applied to document recognition

* Learning Long-Term Dependencies with Gradient Descent is Difficult

* The Consciousness Prior

* Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation



Get full access to The Gradient at thegradientpub.substack.com/subscribe

Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
Author: Language: English Episodes: 100

The Gradient: Perspectives on AI
Podcast Episodes
Stevan Harnad: AI's Symbol Grounding Problem [not-audio_url] [/not-audio_url]

Duration: 1:58:21
In episode 88 of The Gradient Podcast, Daniel Bashir speaks to Professor Stevan Harnad.Stevan Harnad is professor of psychology and cognitive science at Université du Québec à Montréal, adjunct professor of cognitive sci…
Terry Winograd: AI, HCI, Language, and Cognition [not-audio_url] [/not-audio_url]

Duration: 1:33:21
In episode 87 of The Gradient Podcast, Daniel Bashir speaks to Professor Terry Winograd. Professor Winograd is Professor Emeritus of Computer Science at Stanford University. His research focuses on human-computer interac…
Gil Strang: Linear Algebra and Deep Learning [not-audio_url] [/not-audio_url]

Duration: 1:00:36
In episode 86 of The Gradient Podcast, Daniel Bashir speaks to Professor Gil Strang. Professor Strang is one of the world’s foremost mathematics educators and a mathematician with contributions to finite element theory,…
Anant Agarwal: AI for Education [not-audio_url] [/not-audio_url]

Duration: 47:40
In episode 85 of The Gradient Podcast, Andrey Kurenkov speaks to Anant AgarwalAnant Agarwal is the chief platform officer of 2U, and founder of edX. Anant taught the first edX course on circuits and electronics from MIT,…
Peli Grietzer: A Mathematized Philosophy of Literature [not-audio_url] [/not-audio_url]

Duration: 2:33:33
In episode 83 of The Gradient Podcast, Daniel Bashir speaks to Peli Grietzer. Peli is a scholar whose work borrows mathematical ideas from machine learning theory to think through “ambient” and ineffable phenomena like m…
Ryan Drapeau: Battling Fraud with ML at Stripe [not-audio_url] [/not-audio_url]

Duration: 1:06:31
In episode 82 of The Gradient Podcast, Daniel Bashir speaks to Ryan Drapeau.Ryan is a Staff Software Engineer at Stripe and technical lead for Stripe’s Payment Fraud organization, which uses machine learning to help prev…
Shiv Rao: Enabling Better Patient Care with AI [not-audio_url] [/not-audio_url]

Duration: 1:00:51
In episode 81 of The Gradient Podcast, Daniel Bashir speaks to Shiv Rao.Shiv Rao, MD is the co-founder and CEO of Abridge, a healthcare conversation company that uses cutting-edge NLP and generative AI to bring context a…
Hugo Larochelle: Deep Learning as Science [not-audio_url] [/not-audio_url]

Duration: 1:48:28
In episode 80 of The Gradient Podcast, Daniel Bashir speaks to Professor Hugo Larochelle. Professor Larochelle leads the Montreal Google DeepMind team and is adjunct professor at Université de Montréal and a Canada CIFAR…
Jeremie Harris: Realistic Alignment and AI Policy [not-audio_url] [/not-audio_url]

Duration: 1:30:35
In episode 79 of The Gradient Podcast, Daniel Bashir speaks to Jeremie Harris.Jeremie is co-founder of Gladstone AI, author of the book Quantum Physics Made Me Do It, and co-host of the Last Week in AI Podcast. Jeremy pr…