Jan 25, 2026

If You Can't See Inside, How Do You Know It's THINKING? [Dr. Jeff Beck]

Dr. Jeff Beck explores the philosophical and technical definitions of agency, arguing that the distinction between an agent and an object lies in computational sophistication, particularly the capacity for planning and counterfactual reasoning. The conversation provides a deep dive into Energy-Based Models (EBMs), Yann LeCun's JEPA for learning in latent space, and a pragmatic approach to AI safety centered on inverse reinforcement learning rather than fears of rogue superintelligence.

Jan 15, 2026

How to Make AI Forget

Ben Luria, CEO of Hirundo, discusses the critical need for machine unlearning, framing it as a form of "AI neuro-surgery" for enterprise AI. He explains how this technique directly modifies model weights to remove unwanted data and behaviors, addressing core risks that superficial solutions like guardrails cannot solve.

Jan 12, 2026

Structured Dissent Patterns for Agentic Production Reliability

This talk introduces 'structured dissent,' a multi-agent orchestration pattern where believer, skeptic, and neutral agents debate decisions to overcome the 'confidently wrong' failure mode of single-agent LLM systems, improving reliability for high-stakes tasks like cybersecurity analysis.

Dec 20, 2025

Are AI Benchmarks Telling The Full Story? [SPONSORED]

AI models are often benchmarked like Formula 1 cars, excelling on technical exams but failing the test of daily human experience. Researchers Andrew Gordon and Nora Petrova from Prolific critique the 'leaderboard illusion' of current ranking systems and introduce their HUMAINE leaderboard, a new framework that uses census-based sampling and the TrueSkill algorithm to measure how helpful, safe, and relatable models are to real people, not just tech enthusiasts.

Dec 16, 2025

The future of intelligence | Demis Hassabis (Co-founder and CEO of DeepMind)

Google DeepMind CEO Demis Hassabis discusses the path to AGI, focusing on the scientific frontiers of the next decade. He covers the importance of solving 'root node' problems like fusion energy, the challenge of 'jagged intelligence' in current models, and the promise of world models and simulations like Genie and SimA. The conversation also explores the balance between scientific rigor and commercial competition, and the profound societal and philosophical questions AGI will force us to confront.

Dec 11, 2025

The arrival of AGI | Shane Legg (co-founder of DeepMind)

Shane Legg, Chief AGI Scientist at Google DeepMind, outlines his framework for AGI, predicting 'minimal AGI' within years and 'full AGI' within a decade. He details a path to more reliable systems and introduces 'System 2 Safety' for building ethical AI. Legg issues an urgent call for society to prepare for the massive economic and structural transformations that advanced AI will inevitably bring.