Dan Faggella joins the podcast to discuss whether humanity should eventually create AGI, how AI will change power dynamics between institutions, what drives AI progress, and which industries are implementing AI successfully.
Dan Faggella joins the podcast to discuss whether humanity should eventually create AGI, how AI will change power dynamics between institutions, what drives AI progress, and which industries are implementing AI successfully. Find out more about Dan at https://danfaggella.com Timestamps: 00:00 Value differences in AI 12:07 Should we eventually create AGI? 28:22 What is a worthy successor? 43:19 AI changing power dynamics 59:00 Open source AI 01:05:07 What drives AI progress? 01:16:36 What limits AI progress? 01:26:31 Which industries are using AI?
Peter Wildeford discusses methods for forecasting AI progress and why he sees AI as neither a bubble nor a normal technology, covering economic effects, national security, cyber capabilities, robotics, export controls, and prediction markets.
Inria researcher Carina Prunkl discusses why AI evaluation struggles to keep pace with general-purpose systems, including jagged capabilities, missed real-world behavior, misuse risks, de-skilling, red teaming, and layered safeguards.
Li-Lian Ang from Blue Dot Impact discusses how to build a workforce to defend against AI-driven risks, including engineered pandemics, cyber attacks, job disempowerment, and concentrated power, using a defense-in-depth framework for uncertain AI progress.
