Natural Language Processing podcasts

Stanford linguist and computer scientist Chris Manning discusses what linguistics contributed to machine learning and why pragmatics and dialogue remain open problems for language models. The conversation examines early abstraction of verb categories in small transformers, how distributed representations shape learning, and whether language alone can support meaningful representations. It also considers language in world models, diffusion language models, and representation finetuning (ReFT), which steers frozen models through their hidden states. The final discussion asks where knowledge resides and whether concepts occupy linear subspaces.

Hosted by Ravid Shwartz Ziv, Allen Roush

Alex Smola discusses the development of voice agents, audiovisual systems and AI avatars. Topics include audio tokenization, inference cost, conversational latency, visual context and how artificial systems might learn from interaction while responding appropriately to human emotion.

Hosted by Sam Charrington

Google DeepMind research director Brendan O'Donoghue examines discrete diffusion as an alternative to autoregressive text generation. He discusses sample diversity, reinforcement learning, latency and potential on-device or robotics applications. The episode also addresses the costs of serving diffusion models, hardware trade-offs between computation and memory bandwidth, and practical limits on progress toward more capable AI. Hosted by Ravid Shwartz Ziv and Allen Roush. Watch the full conversation on the publisher’s YouTube channel.

Hosted by Ravid Shwartz Ziv, Allen Roush

Pleias co-founder Pierre-Carl Langlais describes language models built from documented open and public-domain sources alongside synthetic data. The conversation examines the SYNTH dataset, gaps in common web crawls, preservation of source material and ethical choices beyond copyright status. It also covers compact deployed models, benchmark incentives, reasoning-trace access and competing approaches to national AI development. Hosted by Ravid Shwartz Ziv and Allen Roush. Watch the full conversation on the publisher’s YouTube channel.

Hosted by Ravid Shwartz Ziv, Allen Roush

Alex Bowcut draws lessons from building an AI system for tax-law research. He explains why retrieval still matters with long-context models, how chunking and combined retrieval methods affect results, and why reliable citations and feedback from domain experts are central to evaluating a specialized application.

Hosted by Sam Charrington

Michael Riegler discusses current uses of AI and language models, possible future developments and the concerns accompanying their spread. Conversation in Norwegian.

Cory Shain discusses efforts to map language processing in individual brains with greater precision. Combining measurements from different recording methods, the research aims to explain how people understand and produce language and to inform future technologies for restoring communication.

Hosted by Nicholas Weiler