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

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OpenAI CFO Sarah Friar and Khosla Ventures founder Vinod Khosla argue the greatest challenges in AI right now are keeping up with demand and making sure more people get the benefit. They unpack what's driving big investments in compute and why this moment is different from other technology cycles — with meaningful advances in health, agents, and robotics still ahead.

Chapters

00:00:00 — What’s the AI story of 2026?

00:07:28 — AI in healthcare

00:12:01 — Scaling compute to match revenue

00:18:05 — Difference between now and dot-com bubble

00:27:41 — Ads in ChatGPT

00:30:05 — Will consumers have more than one AI subscription?

00:36:41 — Winning in enterprise

00:39:44 — How can startups succeed?

00:44:05 — Robotics and beyond

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What does it mean for an AI model to have "personality"? Researcher Christina Kim and product manager Laurentia Romaniuk talk about how OpenAI set out to build a model that delivers on both IQ and EQ, while giving people more flexibility in how ChatGPT responds. They break down what goes into model behavior and why it's an important, but still imperfect blend of art and science.

Chapters:

- 00:00:43 — GPT-5.1 goals and the shift to reasoning models

- 00:02:18 — Differences between GPT-5 and GPT-5.1

- 00:04:55 — Unpacking the model switcher

- 00:07:24 — Understanding user feedback

- 00:08:27 — Measuring progress on emotional intelligence

- 00:10:02 — What is model personality?

- 00:14:25 — Model steerability, bias, and uncertainty

- 00:21:59 — Advantages of memory in ChatGPT

- 00:25:27 — Looking ahead and advice for getting the most out of models

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AI is beginning to change how science gets done. Head of OpenAI for Science Kevin Weil and OpenAI research scientist Alex Lupsasca talk about the early signs of acceleration researchers are seeing with GPT-5—from surfacing literature across fields and languages, to speeding up complex calculations, to designing follow-up experiments. They unpack what’s possible today, what doesn’t work yet, and why the next few years could reshape the trajectory of scientific progress across physics, math, biology and beyond.

Chapters

- 00:00:40 — OpenAI for Science mission

- 00:06:00 — Literature search and intersections across fields

- 00:11:19 — A fusion physicist shows what GPT-5 can do

- 00:15:08 — GPT-5 Pro and black hole symmetries

- 00:19:02 — Getting the most out of the models

- 00:24:33 — OpenAI’s new research paper (https://openai.com/index/accelerating-science-gpt-5/)

- 00:29:59 — Looking ahead to the next 5 years

- 00:32:05 — Will predictions outpace experiments?

- 00:36:43 — The pace of model improvement

- 00:40:31 — What do scientific benchmarks look like?

- 00:44:16 — Fusion and the promise of abundant energy

- 00:48:07 — Closing: Science 2.0 moment

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How will the internet feel when your browser can actually help do things for you? OpenAI’s Ben Goodger and Darin Fisher, whose past work shaped some of the most popular modern browsers, dive into the making of ChatGPT Atlas. They explore how AI changes what a browser can be, from tabs you can talk to, to agents that take over tedious tasks. Learn more about the decisions they made along the way and what’s coming next.

- 00:00:45 What is Atlas?

- 00:03:34 The state of browsers and AI on the web

- 00:13:55 Under the hood: why browsers are hard (OWL, rendering)

- 00:22:00 Building with AI: Codex, cross-language, Swift on Windows

- 00:33:39 Search in Atlas: one box plus model response

- 00:41:28 Favorite features: scrolling tabs and tab search

- 00:45:23 Side Chat in action: summarize, shop, build forms

- 00:46:59 Real-world wins with Agent (cloud bill, medical results)

- 00:52:45 Why Chromium? Compatibility and extensions

- 01:07:57 Five-year vision: an agentic web and reduced toil

- 01:13:11 Power tips and closing remarks

Learn more about OWL

https://openai.com/index/building-chatgpt-atlas/

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Sam Altman and Greg Brockman from OpenAI sit down with Broadcom’s Hock Tan and Charlie Kawwas to discuss their new partnership—and what it means for the future of AI. From custom silicon to global-scale infrastructure, they share how compute innovation is shaping the road to AGI.

00:00 Announcing the partnership

03:06 The scale of AI infrastructure

06:03 Collaboration and innovation in chip design

08:49 Historical context and future vision

12:10 Role of compute in AI development

15:01 Optimizing for specific workloads

18:02 Journey towards AGI

21:00 Future of AI and compute capacity

23:50 Wrap-up and future projects

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The OpenAI Podcast is live for the first time. Host Andrew Mayne sits down with startups Cursor, Abridge, SchoolAI, and Jam.dev—each reimagining how AI can transform their industries. From healthcare and education to coding and collaboration, we explore how these builders are putting AI to work in the real world.

00:23 Caleb Hicks (SchoolAI)

14:14 Dani Grant (Jam.dev)

26:20 Zach Lipton (Abridge)

44:38 Lee Robinson (Cursor)

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What happens when AI becomes a true coding collaborator? OpenAI co-founder Greg Brockman and Codex engineering lead Thibault Sottiaux talk about the evolution of Codex—from the first glimpses of AI writing code, to today’s GPT-5 Codex agents that can work for hours on complex refactorings. They discuss building “harnesses,” the rise of agentic coding, code review breakthroughs, and how AI may transform software development in the years ahead.

1:15 – The first sparks of AI coding with GPT-3

2:20 – Why coding became OpenAI’s deepest focus area

4:00 – What a “harness” is and why it matters for agents

5:30 – Lessons from GitHub Copilot and latency tradeoffs

8:20 – From terminal prototypes to agentic software engineers

19:30 – agents.md and the future of collaborative coding

22:55 – Refactoring, code review, and breakthrough use cases

29:45 – Launching GPT-5 Codex and the road to multi-agent systems

35:00 – Security and the 2030 outlook

43:00 – Compute scarcity

46:30 – Should you still learn to code in the AI era?

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