Large language models

Episode 15 - Inside the Model Spec

Episode 15 - Inside the Model Spec

OpenAI researcher Jason Wolfe explains the Model Spec, the public framework defining intended model behavior. This summary covers its core principles like the 'chain of command,' how it handles complex edge cases, its evolution through public feedback, and its future role in an increasingly autonomous AI landscape.

Will machines ever be intelligent?

Will machines ever be intelligent?

Doug Burger, Nicolò Fusi, and Subutai Ahmad explore the intelligence of AI, contrasting transformer-based LLMs with the human brain's distributed, continuously learning architecture. They delve into differences in efficiency, representation, and sensory-motor grounding, debating what intelligence truly means and how future AI might bridge the gap.

Building AI for better healthcare — the OpenAI Podcast Ep. 14

Building AI for better healthcare — the OpenAI Podcast Ep. 14

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.

From Coder to Manager: Navigating the Shift to Agentic Engineering with Notion Co-Founder Simon Last

From Coder to Manager: Navigating the Shift to Agentic Engineering with Notion Co-Founder Simon Last

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.

Exploits of public-facing apps are surging. Why?

Exploits of public-facing apps are surging. Why?

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.

The Laws of Thought: The Math of Minds and Machines, with Prof. Tom Griffiths

The Laws of Thought: The Math of Minds and Machines, with Prof. Tom Griffiths

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.