The Gradient: Perspectives on AI

The Gradient: Perspectives on AI

Author: Daniel Bashir Language: English Episodes: 100
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.
Episodes
Joanna Bryson: The Problems of Cognition [not-audio_url] [/not-audio_url]

Duration: 1:13:05
In episode 68 of The Gradient Podcast, Daniel Bashir speaks to Professor Joanna Bryson.Professor Bryson is Professor of Ethics and Technology at the Hertie School, where her research focuses on the impact of technology o…
Daniel Situnayake: AI on the Edge [not-audio_url] [/not-audio_url]

Duration: 1:58:07
In episode 67 of The Gradient Podcast, Daniel Bashir speaks to Daniel Situnayake. Daniel is head of Machine Learning at Edge Impulse. He is co-author of the O’Reilly books "AI at the Edge" and "TinyML". Previously, he’s…
Soumith Chintala: PyTorch [not-audio_url] [/not-audio_url]

Duration: 1:08:20
In episode 66 of The Gradient Podcast, Daniel Bashir speaks to Soumith Chintala.Soumith is a Research Engineer at Meta AI Research in NYC. He is the co-creator and lead of Pytorch, and maintains a number of other open-so…
Sewon Min: The Science of Natural Language [not-audio_url] [/not-audio_url]

Duration: 1:42:44
In episode 65 of The Gradient Podcast, Daniel Bashir speaks to Sewon Min.Sewon is a fifth-year PhD student in the NLP group at the University of Washington, advised by Hannaneh Hajishirzi and Luke Zettlemoyer. She is a p…
Richard Socher: Re-Imagining Search [not-audio_url] [/not-audio_url]

Duration: 1:37:49
In episode 64 of The Gradient Podcast, Daniel Bashir speaks to Richard Socher.Richard is founder and CEO of you.com, a new search engine that lets you personalize your search workflow and eschews tracking and invasive ad…
Joe Edelman: Meaning-Aligned AI [not-audio_url] [/not-audio_url]

Duration: 1:06:23
In episode 63 of The Gradient Podcast, Daniel Bashir speaks to Joe Edelman.Joe developed the meaning-based organizational metrics at Couchsurfing.com, then co-founded the Center for Humane Technology with Tristan Harris,…
Ed Grefenstette: Language, Semantics, Cohere [not-audio_url] [/not-audio_url]

Duration: 1:14:16
In episode 62 of The Gradient Podcast, Daniel Bashir speaks to Ed Grefenstette.Ed is Head of Machine Learning at Cohere and an Honorary Professor at University College London. He previously held research scientist positi…
Ken Liu: What Science Fiction Can Teach Us [not-audio_url] [/not-audio_url]

Duration: 2:02:40
In episode 61 of The Gradient Podcast, Daniel Bashir speaks to Ken Liu.Ken is an author of speculative fiction. A winner of the Nebula, Hugo, and World Fantasy awards, he is the author of silkpunk epic fantasy series Dan…
Hattie Zhou: Lottery Tickets and Algorithmic Reasoning in LLMs [not-audio_url] [/not-audio_url]

Duration: 1:42:59
In episode 60 of The Gradient Podcast, Daniel Bashir speaks to Hattie Zhou.Hattie is a PhD student at the Université de Montréal and Mila. Her research focuses on understanding how and why neural networks work, based on…