OpenAI's Dr. Nate Gross and Karan Singhal detail their strategy for applying AI in healthcare, focusing on the rigorous, physician-led process for training models on sensitive health data. They discuss the challenges of deployment in siloed systems and how AI is evolving from a Q&A tool into an integrated assistant for patients and a critical safety net for clinicians.
Notion's Co-Founder, Simon Last, discusses their evolution from a writing assistant to a platform for custom AI agents. He covers the technical hurdles of semantic indexing, the internal shift toward using coding agents to build Notion, and the fundamental transition from a tool where humans do the work to one where humans manage a swarm of agents.
A deep dive into the 2026 IBM X-Force Threat Intelligence Index, exploring the shift to exploiting public-facing applications, the rise of AI agent-related threats, critical AI infrastructure flaws, and the need for a more human-centric approach to threat intelligence.
Princeton Professor Tom Griffiths discusses his book "The Laws of Thought," exploring the mathematical models that govern both biological and artificial intelligence. He details the fundamental differences between human and machine cognition, rooted in their vastly different constraints, and explains how concepts like inductive bias, probability, and curiosity can bridge the gap between cognitive science and modern AI.
Large language models are transforming search from a static, stateless process into a dynamic, agent-based reasoning system. This talk explores the practical patterns—like query rewriting, hybrid retrieval, and agent-based reranking—for building and deploying these 'agentic search' systems at scale, covering the architectural principles, production challenges, and the future trajectory where search itself may dissolve into understanding.
Mefta Sadat from Loblaw Digital discusses Alfred, an agentic orchestration layer designed to run AI shopping agents reliably in production. He covers the architecture built with LangGraph and GCP, the role of the Model Context Protocol (MCP) in simplifying API interaction, and practical MLOps strategies for observability, cost management, and ensuring reliability.