
David Duvenaud
Assistant Professor at the University of Toronto. His research focuses on Neural Ordinary Differential Equations and scalable training of stochastic differential equations.
Top 3 podcasts with David Duvenaud
Ranked by the Snipd community

21 snips
Jun 6, 2025 • 1h 56min
David Duvenaud - What are Humans Even Good For in Five Years? [Early Experience of AGI - Episode 1]
David Duvenaud, an Assistant Professor at the University of Toronto and co-author of the Gradual Disempowerment paper, dives into the profound effects of artificial general intelligence on our lives. He explores the unsettling reality of AI surpassing human capabilities, raising questions about trust and agency. Duvenaud discusses emotional dilemmas in parent-child relationships and the ethical challenges in AI development. His insights prompt a reevaluation of work dynamics, personal values, and the future of human relationships as we integrate technology into our lives.

15 snips
Apr 18, 2025 • 2h 8min
Top AI Professor Has 85% P(Doom) — David Duvenaud, Fmr. Anthropic Safety Team Lead
David Duvenaud, a Computer Science professor at the University of Toronto and former AI safety lead at Anthropic, shares gripping insights into AI's existential threats. He discusses his high probability of doom regarding AI risks and the necessity for unified governance to mitigate these challenges. The conversation delves into his experiences with AI alignment, the complexities of productivity in academia, and the pressing need for brave voices in the AI safety community. Duvenaud also reflects on the ethical dilemmas tech leaders face in balancing innovation and responsibility.

Mar 1, 2025 • 21min
38.8 - David Duvenaud on Sabotage Evaluations and the Post-AGI Future
In this discussion, David Duvenaud, a University of Toronto professor specializing in probabilistic deep learning and AI safety at Anthropic, dives into the challenges of assessing whether AI models could sabotage human decisions. He shares insights on the complexities of sabotage evaluations and strategies needed for effective oversight. The conversation shifts to the societal impacts of a post-AGI world, reflecting on potential job implications and the delicate balance between AI advancement and prioritizing human values.