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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How close are we to automating scientific discovery? What do AI competition wins really tell us about progress toward AGI? OpenAI Chief Scientist Jakub Pachocki and researcher Szymon Sidor share inside stories—from gold medals at the International Math Olympiad to surprising leaps in reasoning—that reveal where AI is headed next.

1:20 – From high school in Poland to AI research leaders

4:50 – Explaining AGI: technical and everyday perspectives

6:30 – Automating scientific discovery with AI

7:50 – Breakthroughs in medicine, AI safety, and alignment

10:30 – Today is a decade in the making

14:30 – Benchmark saturation and its limits

16:50 – Why math competitions matter for AI

18:15 – How models reason without tools

21:45 – Recognizing when a model can’t solve a problem

23:30 – Storytime: AtCoder competition in Japan

26:50 – How reasoning breakthroughs really happen

28:55 – What’s next for scaling and long-horizon reasoning

30:30 – What AGI will look and feel like

36:25 – Balancing trust and personal value

34:00 – Advice to high school students in 2025

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AI is redefining how we learn — from personalized tutoring to entirely new teaching models. OpenAI’s Head of Education, Leah Belsky, joins host Andrew Mayne to discuss what this shift means for students, educators, and society. Special guests include college students Yabsera and Alaap, who share their perspectives on learning in the AI era.

00:22 – Leah’s path to OpenAI & the moonshot

01:40 – ChatGPT as a global learning platform—countries lean in

03:50 – Universities: equal access, trust, and adoption

05:12 – From AI detectors to better policy and practice

06:50 – Study Mode explained

09:51 – AI as a tutor that builds confidence

11:35 – Workforce skills graduates need

14:15 – The great brain rot debate

18:00 – A personal learning anecdote

19:30 – Meet the students

21:30 – First experiences with AI

25:25 – How professors are adapting

29:28 – Trying Study Mode

33:20 – ChatGPT vs. social media

41:43 – Cheating, challenges, and advice for students

49:24 – The future of learning with AI

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The future of work is arriving faster than expected. In this episode, OpenAI COO Brad Lightcap and Chief Economist Ronnie Chatterji join Andrew Mayne to discuss the impacts of AI on software, science, small business, education, and jobs.

00:00 Intro

01:00 Brad Lightcap on OpenAI’s deployment mission

02:00 Birth of ChatGPT: from playground to product

06:15 AI’s impact on work & productivity

08:55 Supercharging science with AI

09:55 Small teams with big leverage

13:10 What sectors are next?

17:05 Defining AI agents

20:30 Small business growth with AI agents

22:08 AI in emerging markets & agriculture

25:53 Return of the “Idea Guy”

28:20 Why EQ and soft skills matter

31:35 Education for the AI era

36:11 Partnering with Cal State & educators

39:14 From bans to buy-in in schools

42:00 Ronnie’s research: sectors, geography, communication

45:46 What should we tell our kids?

48:14 What history teaches us about disruption

52:04 Expanding participation in the economy

55:35 AI increases demand

59:19 Why OpenAI will grow after AGI

1:02:05 Favorite ChatGPT use cases

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Why was OpenAI surprised by ChatGPT’s success? What does it really mean to “reason” in an AI system? And what’s next for agentic coding and multimodal assistants? OpenAI Head of ChatGPT Nick Turley and Chief Research Officer Mark Chen unpack it all in a conversation that pulls back the curtain on the making of OpenAI’s most iconic product.

00:00 – Intro: Meet Nick Turley and Mark Chen

00:40 – Origin of the name "ChatGPT"

03:50 – ChatGPT’s viral takeoff

07:00 – Internal debate before launch

9:40 – Evolution of OpenAI’s launch approach

11:00 – The sycophancy incident and RLHF

14:45 – Balancing usefulness vs. neutrality in model behavior

20:00 – Memory and the future of personalization

22:50 – ImageGen’s breakthrough moment

29:00– Cultural shifts in safety and the freedom to explore

33:10 – Code, Codex, and the rise of agentic programming

37:45 - Coding with taste

41:45 – Internal adoption of Codex

43:40 – Skills that matter: curiosity, agency, adaptability

46:45 – OpenAI’s “Do Things” culture

51:30 – Adapting to an AI future

55:15 – The opportunities ahead: healthcare, research

01:01:00 – Async workflows and the superassistant

01:05:40 – Favorite ChatGPT tips

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