The more AI can do, the more we need to ask what it should and shouldn’t do. In this episode, OpenAI researcher Jason Wolfe joins host Andrew Mayne to talk about the Model Spec, the public framework that defines intended model behavior. They discuss how the Model Spec works in practice, including how the chain of command handles conflicts between instructions, and how OpenAI evolves it based on feedback, real-world use, and new model capabilities.

Chapters

00:00 Introduction

01:10 What is the Model Spec?

03:55 How does the Model Spec work in practice?

06:26 Transparency: Where to read the Model Spec & give feedback

07:51 How did the Model Spec originate?

10:02 How does the spec translate into model behavior?

11:26 What is the hierarchy / chain of command?

13:35 Handling edge cases like Santa Claus

17:41 How does the Model Spec evolve over time?

19:59 What happens when models disagree with the spec?

22:05 How do smaller models follow the spec?

23:16 Is chain-of-thought useful for alignment?

24:16 Model Spec vs Anthropic’s Constitution

26:28 What surprised you most?

26:56 How do you define the scope of the spec?

27:44 What is the future of the Model Spec?

31:16 How should developers think about the spec?

34:44 Asimov’s laws vs Model Spec

37:16 Could AI write a Human Spec?

Hosted on Acast. See acast.com/privacy for more information.

Healthcare systems around the world are under strain, and both patients and clinicians are feeling the impact. OpenAI's Head of Health Dr. Nate Gross and Karan Singhal, who leads Health AI Research, discuss how AI can help address the biggest challenges. They cover how OpenAI is training models to handle sensitive health questions in collaboration with physicians, and how that foundation is unlocking a new generation of tools for patients, clinicians, and healthcare systems.

Chapters

00:00:38 – Origins of Nate and Karan’s interest in AI and healthcare

00:05:01 – Strategy for building AI tools for clinicians

00:06:57 – How AI models are trained for health use cases

00:10:15 – How OpenAI is able to score well on health evals

00:14:21 – Key challenges deploying AI in healthcare

00:21:05 – Collaboration with hospitals and healthcare systems

00:23:05 – Practical everyday uses of AI health assistants

00:26:43 – Biggest “wow” moment during development

00:28:46 – Feedback from clinicians and early users

Hosted on Acast. See acast.com/privacy for more information.

How should advertising work in an AI product? Asad Awan, one of the ad leads at OpenAI, walks through how the company is approaching this decision and why it’s testing ads in ChatGPT at all. He explains how ads are built to stay separate from the model response, keep conversations with ChatGPT private from advertisers, and give people control over their experience.

Chapters

00:00:29 — Mission and principles

00:04:01 — Separation between ads and answers

00:07:31 — Who will see ads

00:08:52 — Internal input and decision-making process

00:11:06 — Controls and how ads will work

00:15:53 — Guardrails for sensitive conversations

00:17:33 — Skepticism about ads

00:20:26 — Helping small businesses

00:24:13 — Future of ads

Hosted on Acast. See acast.com/privacy for more information.