Artificial Intelligence, a Podcast Approach

What if you could simply tell a recommendation system what you want instead of relying on likes, dislikes, and watch history? Kyle Polich talks with Fuyuan Lyu about the DPR framework, which combines large language models and traditional recommender systems to give users direct c ...  Show more

How can researchers audit recommendation systems when the algorithms are hidden from view? Hieu Le joins Kyle Polich to discuss Auto-Like, a reinforcement learning framework that systematically explores how platforms like TikTok personalize content feeds. The conversation covers ...  Show more

In this episode of the SuperDataScience Podcast, I chat with the President and Editor at KDNuggets, Gregory Piatetsky-Shapiro. You will hear about the recent advancements in Data Science, learn how Reinforcement Learning can greatly improve AI capabilities, and learn about the no ...  Show more

A special interview from the Padverb Podcast, in which I discuss my research on language in the brain and thoughts on AI. The discussion covers topics such as backpropagation, how humans acquire language and concepts, how artificial neural networks differ from biological neural n ...  Show more

Could you spot a deepfake? We’re entering a new world where generative AI is challenging our sense of what’s real and what’s fiction. In our first episode, Bilawal and Sam Gregory, a human rights activist and technologist, discuss how to protect our sense of reality.This is an ep ...  Show more

Synthetic voice technologies are increasingly passing as human. But today’s voice assistants are still a far cry from the hyper-intelligent thinking machines we’ve been musing about for decades. In this episode, we explore how machines learn to communicate—and what it means for t ...  Show more