Ethan Mollick, author of "Co-Intelligence", discusses the necessity for US firms to reignite their experimental approach to management to successfully adopt AI. He introduces his "Leadership, Lab, and Crowd" framework for fostering internal innovation and cautions against over-reliance on external consultants and opaque vendor solutions, urging companies to empower their "secret cyborgs" to drive productivity.
Poetic, a startup by ex-DeepMind researchers, has significantly advanced performance on the ARC-AGI benchmark by applying a recursive self-improvement system to Gemini 3. Co-founder Ian Fisher discusses how their approach of automating prompt and system engineering provides a substantial performance boost without needing access to model weights, and explores its potential as a path toward AGI.
Explore the significant security risks posed by Agentic AI and quantum computing, from data breaches of sensitive information to the breakdown of modern cryptography. Learn proactive strategies for governing AI and preparing for a quantum-safe future.
Jason Martin of Permiso Security discusses the exponential rise of AI agents in enterprises and the urgent security challenges they present. He covers the concept of Non-Human Identity (NHI), applying Zero Trust principles to ephemeral and over-permissioned agents, and outlines key attack vectors like prompt injection and data poisoning, while also exploring the potential of defensive AI to enhance security operations.
Laura Deming, co-founder and CEO of Until, discusses the ambitious goal of making reversible cryopreservation a reality. She outlines the company's vision, starting with preserving human organs to revolutionize transplantation and progressing towards whole-body medical hibernation, allowing patients to "pause" biological time and await future cures. The conversation delves into the core scientific challenges, reframing cryopreservation as an engineering problem of heat transfer and managing ice formation, and explores why this promising field has been historically underfunded.
Amey Shukla from the University of Connecticut presents a novel system for biometric key derivation that closes the long-standing gap between the theory and practice of device-level authentication. The talk introduces a practical fuzzy extractor system, "Zeta then Lock," which, combined with an integrated machine learning feature extractor, achieves 105 bits of entropy with a 92% true accept rate for iris biometrics, overcoming the "more errors than entropy" problem that plagued previous designs.