What does it actually take to build a mind? Cognitive scientist Danielle Perszyk sits down with world-class researchers, academics, and industry pioneers to explore the science of intelligence — from its evolutionary and cultural origins to the frontiers of AI. Challenging simplistic narratives about the race to superintelligence, each conversation unpacks how humans think, learn, and collaborate, and what that means for the machines we're building.
A system that succeeds once is a demo. A system that succeeds every time is a breakthrough. Dr. Danielle Perszyk sits down with AI researcher Deniz Birlikci from Amazon's AGI Lab to explore how reinforcement learning (RL) is transforming AI agents from impressive demos into dependable tools that work consistently in real-world environments.
Danielle and Deniz discuss why reliability, not accuracy, is the true bottleneck for web agents, the critical role of a robust verification system, failure models that RL attempts to fix, and the extraordinary complexity of orchestrating live browsers with perception and actuation stacks. Discover how RL is building the foundation for agents that can handle complex workflows reliably alongside humans.
