Brad Lightcap and Ronnie Chatterji on jobs, growth, and the AI economy — the OpenAI Podcast Ep. 3

1. 0:00 – 2:00

   Intro

   1. AMAndrew Mayne0:00

      Hello, I'm Andrew Mayne, and this is the OpenAI Podcast. There's a lot of conversation and debate about the future of AI when it comes to labor and work. To talk about this, my guests are Brad Lightcap, who's the Chief Operating Officer of OpenAI, and Ronnie Chatterji, who is the Chief Economist. We're gonna find out the kind of research OpenAI is doing, the conversations they've been having, and hopefully get a glimpse of where they think the future is headed. [upbeat music]

   2. BLBrad Lightcap0:27

      We had a lot of people coming back to us and saying, "Yeah, you know, actually, this is, I think, one of the best things that has maybe ever happened to this, this industry." AI is a tool that lets people do things that they had no ability to do otherwise.

   3. RCRonnie Chatterji0:40

      They have the world's smartest brain at their fingertips to solve hard problems.

   4. AMAndrew Mayne0:45

      So, Brad, you're the Chief Operating Officer, you're the Chief Economist. Explain what your roles are.

   5. BLBrad Lightcap0:49

      My role probably boils down mostly to [clears throat] what we call deployment. So zooming out, OpenAI is a research and deployment company, and when we think about our mission, what we really think about is not only building AI and doing the research that underpins the building of AI, but how do you actually take it out into the world and have people use it, and have it be beneficial, uh, for people, have it be safe for people? Uh, how is it used in one country versus another country, one industry versus another industry? So I spend a lot of time trying to figure that out, uh, which means working with customers, working with partners, uh, spending a lot of time with our users, and just kind of studying kind of how people-- uh, what people want from OpenAI and our products, how people actually use the technology, and then as the technology changes, how that pattern of use changes.

   6. AMAndrew Mayne1:33

      It, it seems like 'cause OpenAI started primarily as a research org and wasn't even sure if they were gonna do product or even put things that were sort of public-facing, and so how much has this changed rapidly for you?

   7. BLBrad Lightcap1:44

      It's changed really quickly. I think ChatGPT, uh, in November '22, was kind of the pivotal moment, and it was the first time that we really saw AI used at scale.

   8. AMAndrew Mayne1:54

      Mm-hmm.

   9. BLBrad Lightcap1:55

      Uh, and I think, you know, what we kind of... A- and it's interesting, almost, the, the story of how

2. 2:00 – 6:15

   Birth of ChatGPT: from playground to product

   1. BLBrad Lightcap2:00

      we actually learned that a- and, and how we made the decision to do ChatGPT, um, which was we had previously built an API for developers, and we had a thing, uh, you'll remember, Andrew, in our API, uh, that was, uh, the playground-

   2. AMAndrew Mayne2:14

      Yeah

   3. BLBrad Lightcap2:14

      ... where you could basically try prompts out and see how the model would complete the prompt, and this was back in the days of, like, the models just being purely completions-based-

   4. AMAndrew Mayne2:22

      Mm

   5. BLBrad Lightcap2:22

      ... where they take an input, and they kind of continue the text on, uh, predicting the next word, uh, and the next token in the sequence. And people were trying to, like, hack the playground, uh, to figure out how to get it to talk to them, and they almost-- you could tell people kind of wanted this conversational interface. And so we kind of learned from that, and we built ChatGPT as the first version of a conversational interface, where we taught the model how to instruction-follow to be more responsive to what people wanted to talk about. Uh, and that, you know, very much surprised us and became, I think, the kind of dominant paradigm of what we call the first era of AI, which was these kind of chatbots, uh, that, you know, really were good enough to, to, uh, to be engaging for people and be helpful for people.

   6. AMAndrew Mayne3:04

      Yeah, it seems like-- 'cause at the time, we kept thinking that, like, GPT-4 would be finally when it was really useful, and ChatGPT was built on top of GPT-3.5. And it, it seemed it, like, certainly changing the interface was helpful, but we thought we needed a faster, more smarter model, but it was actually the interface was such a big unlock, and that was... I had the problem whenever I would do demos of GPT-3, it would be this blank canvas. I'd go, "Now you do something," and people would be like: "I, I, I don't know what to do." But once you put it into the chat interface, they go, "Oh, well, I'll ask it a question. I'll ask if we do this," and that was such a big un- big unlock. But then, the pace after that, like you said, was in- was insane because ChatGPT exceeded beyond any expectation here. I think there was an expectation it would kind of level off, but it didn't, and then pretty soon, there was this awareness. I think people thought AI was something in the future, and now it came into the present, and now we're bringing in an economist to come help map this out and figure this out. So what is your role?

   7. RCRonnie Chatterji4:04

      As you say, I mean, the future has arrived more quickly than any of us could've imagined, and so I joined at a time when we were deploying intelligence at scale, uh, into the economy, into society, and my job is to help people understand what the impacts of that are gonna be on businesses, their jobs, uh, their relationships, uh, the way government does policy, and develop forecasts to help people understand, um, how to make investments with their time, um, and overall with their resources. And so, as an economist, it's an amazing time to join because I think we're at a beginning of a real transformation, um, in the economy, and it's something that I think people need to be prepared for. So the biggest job I have at, at OpenAI is developing indicators to kind of tell us where the economy's going and communicating that to people all over the world. 'Cause this is gonna be bigger than just the United States and what we do here, but something that's actually gonna transform people's lives around the world.

   8. AMAndrew Mayne4:55

      Okay, so in my experience, and limited experience, of understanding, like, when corporations employ economists, often it's to figure out, let's say, the prices of products or things like that to make kind of predictions, but here, your job isn't just internal, so it's external. So are you-- how are you sharing this, and what is OpenAI doing to help people understand where things are headed or where we think they are?

   9. RCRonnie Chatterji5:13

      You're right. I mean, there's a tradition of, you know, economists joining companies, and in tech specifically. Um, this job was, was designed a little bit differently, and I think it reflects that this company really has research roots, and I think people really want it to be a job that, yes, thought about pricing, and A/B tests, and analyzing data from the platform, but maybe more importantly, also thought about: How is this gonna change the world? And doing research, rigorous research, just as rigorous, uh, but in a different way, as our AI researchers do, in terms of what's gonna happen, and how can we tell people about it? How do we get people ready for this? And so a big part of my job is external. You know, since I started, I've been in, um, London, and Brussels, and Delhi, and Washington. Uh, we'll eventually go to Sacramento [chuckles] and Sydney, and every place in between.

   10. AMAndrew Mayne5:57

       Wow!

   11. RCRonnie Chatterji5:57

       But it's so interesting to see the conversation and the vibes across those different markets and how people are thinking about this and the different use cases. So I have to say, as much as we go out and do that work, I learn as much-

   12. AMAndrew Mayne6:06

       Mm-hmm

   13. RCRonnie Chatterji6:06

       ... in those interactions [chuckles] as I probably teach, but a big part of my job is external and getting sort of people ready for what's happening right now.

   14. AMAndrew Mayne6:13

       Well, uh, there's a lot of anxiety

3. 6:15 – 8:55

   AI’s impact on work & productivity

   1. AMAndrew Mayne6:15

      because I think w-... OpenAI was caught off guard by the success of ChatGPT, and the rate of adoption, and the places it's being used. And I think, uh, every technology, you know, every disruptive technology, people, there's a fear of change, and change is inevitable. But there is the fear of how it's gonna change work, you know, how much it's gonna change labor and employment. And how much does OpenAI think about that, and how much of what you do is sort of like thinking about helping people adapt to that, et cetera?

   2. BLBrad Lightcap6:43

      Yeah, I mean, I, I would say, uh, it's, it's something that we, we look at a lot. I think Ronnie probably looks at it through one lens. I, I kinda somewhat look at it through the lens of what are the things that we need to build to accelerate the opportunity that AI has-

   3. AMAndrew Mayne6:56

      Mm

   4. BLBrad Lightcap6:56

      ... to be impactful in a kind of an economic and, an outcome-oriented context. Um, and that could be at a micro level. It could be an individual person, for example, uh, trying to better understand, uh, their medical care.

   5. AMAndrew Mayne7:08

      Mm.

   6. BLBrad Lightcap7:08

      Uh, it could be at a macro level, at a firm level. It could be a company that's trying to think about how to accelerate software engineering and pull forward projects from next year into this year. So all of these things actually... I mean, you know, Ronnie probably does the interesting kind of studies on these things and takes a much more scientific vent- vantage point. We take a very product-led vantage point, though, on it-

   7. AMAndrew Mayne7:26

      Mm

   8. BLBrad Lightcap7:26

      ... which is how do we actually go build the tools that are representative of the things that people actually want from the systems? And so, you know, software engineering is the, is the, is the thing that I think right now is super interesting, is the systems we're building are progressing at a just an, an insane rate in terms of their capabilities in software engineering. Um, you've seen rise of tools like Cursor and Windsurf, and others. Um, and we think there's a huge opportunity there to help software engineers and k- kind of entirely change the toolset of software engineers, uh, to, to make them, you know, not 10 times- uh, 10, 10% more productive, but maybe 5 or 10 times more productive. Uh, and then Ronnie gets to study the impact of that, uh, you know, on an economic level.

   9. RCRonnie Chatterji8:04

      It's, it's amazing, and I think about it exactly this way. It's almost a handoff from what Brad is leading on the product side. Okay, now our software engineers have these amazing tools, intelligence at their fingertips to be more productive. You know, we might, across the world, write like a few billion lines of code in a day, and now you could multiply that by 10x.

   10. BLBrad Lightcap8:23

       Mm.

   11. RCRonnie Chatterji8:23

       What could we build? What could they build if you can write that much more code and that much more sort of even better code, potentially, than you could on your own? That, to me, is a huge economic opportunity, and so yeah, my job is to pick it up from that angle, understand how a software engineer's job is changing, how she might be using these tools to do things she couldn't do before, and how the organization that she works in is also gonna benefit from that, creating more productivity and ultimately value for the economy. So I, I, I see that as a super interesting challenge. Um, the other thing I'd say is like scientific research is one I get really excited about.

   12. BLBrad Lightcap8:53

       Mm.

   13. RCRonnie Chatterji8:53

       So I think taking Brad's analogy,

4. 8:55 – 9:55

   Supercharging science with AI

   1. RCRonnie Chatterji8:55

      it's like we wanna put amazing intelligence in the hands of scientific researchers. Why does that matter? Because, you know, science drives growth, it drives economic growth, and so if we can accelerate science, accelerate discovery, we're gonna have more economic growth and more good things for everybody. And so I always think about if I can study how science is changing with our-- with the use of our products, then it'll be a useful contribution, uh, in terms of economics, but also just the world.

   2. AMAndrew Mayne9:16

      Yeah, I wanna, I wanna touch on that a second, but what... In the software space, I think you've seen-- there's been a-- I've seen a lot of people have a concern because all of a sudden, companies are saying, "Oh, we don't need as many developers now." But I, I, I would say the broader picture is we're never gonna be done writing software. There is always gonna be more need for software than there is right now, and I think the challenge is that some of the bigger companies are getting a bit disrupted or internally, but we need to think about where the smaller companies, the more agile ones, are gonna come in and where they're gonna come from, because I think small teams can do a lot more. And has that been something you've observed, where, you know, let's say some companies are saying, "Okay, we can do more with this tool,"

5. 9:55 – 13:10

   Small teams with big leverage

   1. AMAndrew Mayne9:55

      and but we're seeing smaller companies come forth with new solutions?

   2. BLBrad Lightcap9:59

      Yeah, for sure, and I think that is the trend line of AI. Fundamentally is the, the world is rate limited by talent, by people.

   3. AMAndrew Mayne10:07

      Mm.

   4. BLBrad Lightcap10:07

      Um, real, you know, economic growth in, in the world rounds to zero in most places, and why is that, right? It's because it's really hard for the average company, whether it's a small business, a large business, you know, a financial services company, an insurance broker, a hospital, to find people that can actually produce better tools, better systems, uh, and ultimately better outcomes for customers. Uh, and if you go ask kind of any company, you go ask any company in Silicon Valley, you know, where, uh, if, if they need to hire more engineers [chuckles] the answer is almost always yes.

   5. AMAndrew Mayne10:40

      Mm.

   6. BLBrad Lightcap10:40

      And this is, this is the mecca of engi- you know, of software engineering. Um, now imagine what the rest of the world looks like. And so just taking software engineering as an example, we see it as not only incredibly, uh, you know, there being an incredible opportunity to inflect outcomes for those comp- you know, for companies large and small, but we see it really as incumbent on OpenAI to be able to build the toolsets, the models, all the, you know, the safeguards, uh, all of the, the compliance schemas and all that, to be able to actually serve these, these tools in the places that they need to be. Um, and it's, it's interesting, kind of the, the polarity of it. I think, you know, on, on the one hand, you've got this toolset that is going to be incredibly enabling of people who have no sophistication on the subject matter. So you've got companies now building tools that are enabling people to build software who've never written a code-

   7. AMAndrew Mayne11:29

      Mm

   8. BLBrad Lightcap11:29

      ... a line of code in their life. [chuckles] And on the other hand, you've got these tools that are incredibly sophisticated and taking, you know, level 10 engineers and making them 50%, 2X more productive. Uh, and it's a remarkable thing that you can get both of those effects.

   9. AMAndrew Mayne11:43

      Uh, something I thought was interesting was using the, the Moderna case example, where they deployed ChatGPT Enterprise, and one of the things that happened internally was you had people developing their own GPTs. And sometimes people go: Well, what's happened to GPTs externally? But I think that's been an interesting thing, is internally, somebody who may not have thought about how to build an agent or something like that, who may not be technically inclined, is able to do that. And has that been a common trend with other companies that are now just building on top of the platform?

   10. BLBrad Lightcap12:10

       Yeah, I mean, I, I think that is fundamentally kinda how this is gonna work. I think AI, at its core and its essence, is a tool that kind of lets people do things that they had no business or ability to do otherwise. And there's gonna be-... kind of crazy outcomes that come from that.

   11. AMAndrew Mayne12:25

       Mm-hmm.

   12. BLBrad Lightcap12:25

       I think it's kind of somewhat unpredictable, and if you kind of look in the long arc of history of what makes for these kind of disruptive platform shifts, to me, the thing that is kind of demarcating of that is when you now have people who actually have the capability to go off and do some- something at either a, a much higher level of productivity or something that's parallel to the, the core thing they're doing that they couldn't do before, where they were kind of rate-limited or gated on someone else being able to-- having to do that thing for them. Uh, and so that's-- GPTs are a good example of how you now have someone who can configure what could be a fairly complex workflow, right? And it's on us to continue to build a product that enables even more complex workflows over time as the models get really good. Uh, and that's, that's a remarkable thing.

   13. AMAndrew Mayne13:06

       What sectors do you see being impacted next?

6. 13:10 – 17:05

   What sectors are next?

   1. RCRonnie Chatterji13:10

      I, you know, I think that we're just scratching the surface when it comes to scientific research, areas like drug discovery, material sciences.

   2. AMAndrew Mayne13:17

      Mm-hmm.

   3. RCRonnie Chatterji13:17

      I think the next couple of years, um, you're gonna see massive discoveries in those spaces for the reasons that Brad is talking about. When I think about science, I, I think about a, a endless corridor, uh, with doors on either side, and scientists, researchers in companies have to make decisions about where they're gonna explore, and that, that's a rate-limiting sort of situation, to, to Brad's point. You can't explore every door. But what our tools can help you do is actually look behind all those doors and take a peek and figure out where you want to spend the time working on the hardest problems. And I think if we can accelerate science, um, in that way, you're gonna see massive discoveries coming out of private sector labs, national laboratories, like many of the ones we're already working with, um, and the public sector. And so I expect those areas in research to really be transformed over the next several years. I think you'll see a lot of different discoveries that we wouldn't have thought possible happening more quickly. Um, I think another area is gonna be on sort of professional services. Like, we both, uh, work a lot, I know a lot, um, of folks who are in this industries, either whether it's private equity, investment banking, consulting. So much of the work there that people are doing, um, we can augment that work by... You know, I think about the way I use, uh, our tools to create slide decks or prepare for a presentation. I can now focus on the higher value and higher margin things that are important for my job now that I can use our tools to do some of these things that I was gonna have to do myself. And so I see professional services as a key area where a lot of consultants, bankers, and private equity executives are gonna be able to use this in a big way.

   4. AMAndrew Mayne14:40

      Mm-hmm.

   5. RCRonnie Chatterji14:40

      So those are two areas I see, finance, um, and science-driven discovery companies being really revolutionized by our tools.

   6. BLBrad Lightcap14:46

      And I would say it's not just the-- on the science side, at least, it's not just the depth of any individual step of the work. So certainly, like-

   7. AMAndrew Mayne14:53

      Yeah

   8. BLBrad Lightcap14:53

      ... you can now do this, you know, more multifaceted exploration for any given thing, but it's the breadth across the, the span of the work that these models can reason over. So having these systems able to understand, if, you know, if you look at kind of how a drug gets developed, for example, there's like, you know, some number of insanely complex, discrete steps in that process that all require kind of handoff at various points to a lot of different people, who all have to kind of gather context from the person before them and kind of prepare context for the person that comes after them. And you can actually schematically break it down. Um, and to have models basically woven across that entire workflow, not only are you enabling the scientist to go deeper, but you're actually enabling the people who work with and around the scientist to actually kind of accelerate the, the end product, uh, you know, ultimately to a better outcome and, and ultimately faster.

   9. AMAndrew Mayne15:40

      One of the, uh, one of the limitations I've seen... So one of the companies I've worked with, they're doing drug discovery, and the models are great at suggesting things, but it still comes down to the clinical trial and the lab bench and things like that. And hopefully, we'll find ways to accelerate that. But what are some of the other limitations, either to what these things can do, or bottlenecks for us seeing sort of the benefits?

   10. RCRonnie Chatterji16:02

       I think human judgment, decision-making is gonna be really important. Uh, I actually think it might be more important.

   11. AMAndrew Mayne16:07

       Hmm.

   12. RCRonnie Chatterji16:07

       You know, what we're finding in a lot of research, and I'll, I'll-- one of my colleagues at, um, in this is David Deming at Harvard, he has this research that shows that people who are great at leading teams, let's say someone like Brad at the top of the company, they're also the same people who are great leading agents. And I think that a lot of the skills that let people be-- make great judgments, lead teams, they're gonna be even more important and at a higher premium in this economy. And so I feel a situation like this, where, uh, firms are using it in drug discovery, you're still gonna need the judgment of experts. You're gonna need refinements on the experiments, and you're gonna need help in terms of scaling. I also think there's other institutional changes, though, that might accelerate science. Clinical trials come from an old world of how we used to test, uh, drugs for safety and efficacy. Those are really important. But everything from the sample sizes to how you enroll people, I mean, our tools could be hugely-

   13. AMAndrew Mayne16:52

       Mm-hmm

   14. RCRonnie Chatterji16:52

       ... um, helpful in those areas. So I feel like you're gonna see it in drug discovery, but you're also gonna see it in every part of the value chain for, let's say, a pharma or biotech company, that might ultimately not just increase the rate of discovery, but the rate of commercialization and scale. That's my hope.

   15. AMAndrew Mayne17:04

       You just

7. 17:05 – 22:08

   Defining AI agents

   1. AMAndrew Mayne17:05

      mentioned agents, and I think it's a word that's kind of like the word of the year.

   2. RCRonnie Chatterji17:08

      Yeah.

   3. AMAndrew Mayne17:08

      People hear it-

   4. RCRonnie Chatterji17:08

      Yeah

   5. AMAndrew Mayne17:08

      ... and sort of there's all sorts of definitions of it. Do you want to take a stab at that and kind of see how you guys see that playing out?

   6. BLBrad Lightcap17:14

      I mean, I'll, I'll probably get, uh, you know, yelled at by someone at OpenAI-

   7. AMAndrew Mayne17:17

      No, it will not be controversial at all

   8. BLBrad Lightcap17:19

      ... whose, whose definition [chuckles]

   9. AMAndrew Mayne17:21

      Everybody will agree. [chuckles]

   10. BLBrad Lightcap17:21

       Um, I mean, for me, agents, uh, have-- I have a very high bar. Uh, it has to be a s-- it has to be a, a system that can be reliably handed complex work, that it can take on autonomously, um, uh, you know, and, and, and, and execute at a high level of proficiency, uh, where it hasn't seen that work before. And that last part is a critical piece, is y- these aren't just things that are trained to copy. They have to be th- things that kind of implicitly leverage the reasoning ability of the model to solve new problems. Um, and this is gonna be important in a lot of domains. And so people use the word agent, I think there's maybe an enterprise productivity context of it, there's maybe a science, uh, you know, kind of context of it, there's a, uh, a software engineering context of it.

   11. AMAndrew Mayne18:04

       Mm-hmm.

   12. BLBrad Lightcap18:04

       But the kind of common thread for me is, um, it has to be something that you can actually hand something to, you almost work in tandem with, kind of like a teammate, and, you know, that teammate could be a scientist, it could be a software engineer, it could be a, a data scientist.

   13. AMAndrew Mayne18:16

       Could you give me, like, a hypothetical example of, like, a kind of task?

   14. BLBrad Lightcap18:19

       Yeah, I mean, I, I think software engineering is, is, has, has an obvious set-

   15. AMAndrew Mayne18:22

       Mm-hmm

   16. BLBrad Lightcap18:22

       ... which is, you know, uh, you, you could ask, ask it to basically go off and, a- and actually write code for you. Um, and, you know, and then kind of similarly, go do the QA, go do, uh, uh, all the unit testing, go, um, you know, automate kind of meaningful parts of this process of the, you know, of code writing. Um, and, you know, in a different context, I would say it's-... uh, you know, it's working with, uh, agents that can make your, uh, your sales teams more efficient. So slotting into parts of your sales funnel where you have a volume problem, where it's like, "Okay, I've got, you know, a hundred thousand inbound leads for a thing, but I've got five people to look at them." Can you actually have an agent that can ingest those leads and, and understand those leads, process them, qualify them, move them through your funnel, recommend, you know, who should talk to who, recommend all the follow-up steps, uh, and ultimately kinda drive a lead toward a s- uh, a conversion? Um, so th- th- it's a, it's a generalizable concept that kind of maps into any number of areas.

   17. AMAndrew Mayne19:17

       Do you see this like, like where I might email an agent or something and say, "Okay, I need to..." And just treat it like I would another employee?

   18. BLBrad Lightcap19:25

       Yeah, I think that's kind of the, the interesting part of it, is that, you know, in some sense, um, th- there's the, the, the kind of the input mechanisms, uh, will be specific, I think, to the f- the, the, the user, right?

   19. AMAndrew Mayne19:37

       Mm-hmm.

   20. BLBrad Lightcap19:37

       It's if you are a software engineer, you may want that agent living in your IDE. Uh, if you're a scientist, you may want it living in the software you use that you do experiment, design, and execution with. Um, if you're, you know, uh, uh, doing, you know, user operations or customer support, you may want it sitting in your inbox because that's where your work happens.

   21. AMAndrew Mayne19:56

       Mm.

   22. BLBrad Lightcap19:56

       And so how do you build product that, uh, is intelligence underneath but is accessible into kind of any number of surfaces and can be, uh, you know, without the con- without, without compromising the, um, the reliability and the, uh, the power of the system, is actually a hard product problem.

   23. AMAndrew Mayne20:11

       I have friends that are, uh, pretty ChatGPT-focused, you know, power users, and I've heard comments from before of, like, wanting to sort of do more with it, and even small business owners, too. The idea that if they could have, like, a virtual ChatGPT agent or something like that. Is that something that you see in a near-term horizon that, you know, I'd be able to, like, get it take care of a lot of the little work that there's just not enough hands to do?

   24. RCRonnie Chatterji20:39

       I think it's a, I mean, it's a really amazing near-term application in my view. You know, when you think about the limits around the world of growing the economy, one of the biggest ones is small business.

   25. AMAndrew Mayne20:48

       Mm-hmm.

   26. RCRonnie Chatterji20:48

       Um, there's what they call in economics, a missing middle in so many countries, where you have a bunch of small businesses, and you have a few large businesses, but the small businesses don't grow large. And that was a big benefit of the US economy, that our small businesses and entrepreneurs can actually grow and scale. In most places around the world, that's not true. Why is that not true? Because they often don't have the, the mentorship, the coaching, the support, the advice to actually know what to do to grow their business. Now, imagine you democratize, uh, an AI agent that understands the basics of how to grow a restaurant business or an e-commerce business, and that's relatively easy to do in terms of instantiating that kind of intelligence into an agent. And then, a small business owner could leverage that advice and decide, "Oh, maybe I should change a menu item or hire a sales rep or do something different with my strategy that could help me grow." And I think for small business owners around the world, uh, including the United States, tremendous opportunity to get sort of small business advice, evidence-based advice from agents. It's something I'm very interested in-

   27. AMAndrew Mayne21:42

       Mm-hmm

   28. RCRonnie Chatterji21:42

       ... and I know a bunch of folks around the world are working on.

   29. AMAndrew Mayne21:44

       So, uh, I wanna, I wanna a- a- address that, one, the evidence-based approach in a second, but tell us more about what you're seeing from, like, developing economies. 'Cause I know that's a big area of concern. It's one of the fears is that there's a lot of kind of like, kind of lower level of knowledge work that's done in developing economies, and the fear is that AI is gonna take that away. But you just brought up the fact that there are these-

   30. RCRonnie Chatterji22:05

       Right
8. 22:08 – 25:53

   AI in emerging markets & agriculture

   1. RCRonnie Chatterji22:08

      I think there's a lot of opportunities we should be talking about as well. I, I know that when I work in emerging markets, there's a lot of human scaling problems. It's related to what the rate-limiting factors that Brad talked about with Silicon Valley hiring engineers. One of the biggest returns on investment in Africa is agricultural extension support. What that means is helping a farmer figure out what kinds of seeds he should be using-

   2. AMAndrew Mayne22:31

      Mm

   3. RCRonnie Chatterji22:31

      ... what kind of fertilizer he should be using, uh, what kind of farming techniques he should do to get the most out of his land. 'Cause a lot of people are small scale, subsistence farmers. If we can increase productivity for that farmer, ten, 20, 30%, it is life-changing, and we have people who are trained up to do that, but there's not enough of them.

   4. AMAndrew Mayne22:45

      Mm-hmm.

   5. RCRonnie Chatterji22:46

      And when these extension support services are offered, there's always someone, probably 10, who don't get the service for every one person who does. Now, imagine that we could have intelligence provided to those 10 who never got that service to begin with, and I think when you think about agricultural extension support scaling with our tools, it's a huge opportunity to improve lives of people, um, in sort of lower-income countries and emerging markets, particularly in agriculture. I'd say the small business one is another example. You know, we know from the United States, one of the best ways to move up the income and wealth ladder is start a business. That should be true in other places, too, but there's so many limits to scaling, and often it is hiring the right person or getting the right advice. And so those are two opportunities I think, uh, if we can do this right, are gonna make a huge impact, uh, for the positive in the poorest parts of the world.

   6. AMAndrew Mayne23:29

      My mother-in-law is in India, and she has a candy company, and she uses ChatGPT a lot to help her plan menus and recipes and write stuff, and it's been an interesting sort of unlock because now I've seen-- I think she really did was- would have quite quality before, but now it let her basically spend more time on other things.

   7. RCRonnie Chatterji23:47

      Yeah.

   8. AMAndrew Mayne23:48

      And so it's, it's, it's interesting 'cause, like, you've seen, like, in African development, where cellular was a bigger change than anybody predicted. It was... You took a country like Kenya, which maybe, like, 5% of the population had phones, and it was all controlled by the government or something. Then once cellular came through, then you had people were able to, like, figure out how to go to market. You got all sorts of commerce stuff, things.

   9. RCRonnie Chatterji24:07

      That's right.

   10. AMAndrew Mayne24:07

       And what, what changes are you seeing right now with ChatGPT or like technologies?

   11. RCRonnie Chatterji24:12

       I mean, to your point, and first, if, if your mother-in-law's running an Indian sweet company, I got three little interns in my household who'd love to join.

   12. AMAndrew Mayne24:18

       Yeah. [chuckles]

   13. RCRonnie Chatterji24:18

       So just let us know if there's a job opening. But, uh, [chuckles] this is where the disruption is, like, both exciting, uh, and, and I also understand it induces anxiety, but you're exactly right. When you look at the Kenyan experiment, uh, when they leapfrogged a generation of technology, when new innovations came out, we're now doing something fairly radical, which is putting intelligence in individuals' hands, right? When they have a ChatGPT account or subscription, they have the world's smartest brain at their fingertips to solve hard problems. It's not intermediated by a, a government or a big business. It's, it's something they can use to solve problems, and I'm really optimistic about the problems people are gonna choose to solve. One of the coolest things about this organization is we don't really tell you what problems to solve. Like, that was one of the most interesting things, I think, here is, like, when you think about how people are using ChatGPT, it's a wide, diverse set of uses, much less how they're building on the API, right, with our developers.

   14. AMAndrew Mayne25:05

       Mm-hmm.

   15. RCRonnie Chatterji25:05

       And so people will choose to solve the problems that are most relevant to them.... and that's gonna be incredibly, um, sort of transformed- transformed for their lives, but also disruptive because, right, they're gonna be able to have that power that they didn't have before. And I think when I think about it as an economist, those are the kinds of transitions I wanna study, I wanna understand, I wanna make easier for individuals, organizations, and society. And I think the level that you're talking about happened in Kenya and other parts of the world, this is a much bigger transition-

   16. AMAndrew Mayne25:31

       Mm

   17. RCRonnie Chatterji25:31

       ... that we're on the verge of. So it's something that my team spends a lot of time thinking about when we look at data, not just looking at the US and Europe, but looking at other parts of the world.

   18. AMAndrew Mayne25:39

       You mentioned before in working with agents, how having sort of, I guess, managerial skills or the ability to delegate is important. Could you expand on that? And also maybe, like, what other skills might be important that people need to be thinking about that they want to develop?

9. 25:53 – 28:20

   Return of the “Idea Guy”

   1. BLBrad Lightcap25:53

      AI is interesting because it really is kind of a reflection of your, your will, right, and your desire, and I think, um, you- it, it- sky's the limit, kind of in terms of what it can do for you, right? If you wake up one day and you decide you wanna start a business, uh, that just got meaningfully easier. If you wake up one day and you decide you wanna build, uh, a piece of software, right, that got meaningfully easier. And so there's an incredible level of agency, I think, that's required to extract the most out of AI. I think as we think about kind of where the product moves, um, our job is to try and lower the bar so that there's- you don't, uh... y- you can basically simplify the kind of, the, the path from idea in your brain to, uh, to outcome. Um, and, you know, there's interesting ways in a meta sense, the models can actually help, help do that. But, uh, I think that, you know, the, the- that's probably to me, the kind of really important, important thing is, um, that, that agency is gonna matter a lot. There's gonna, there's gonna be, uh... You're gonna see the, the rewards accrue to people who, uh, are, um... You know, Sam said it the other day, is like the, the return of the idea guy in some sense.

   2. AMAndrew Mayne26:59

      Mm.

   3. BLBrad Lightcap27:00

      Um, it's, it's the people that I think can, you know, not only figure out what it is that they want, uh, and, you know, what the- what good looks like, uh, but then can kind of figure out how to activate, um, the systems to be able to work on their behalf. And there's gonna be people that do that incredibly well. And I... You know, one of my kind of personal bars for, uh, for how impactful our work ends up being, um, is will you see the rise of companies that are one to five, ten people that are doing a billion dollars in revenue, right? That's kind of the ultimate agency outcome if you think about it. It's like you have a, a s- a very small set of people capable of commanding, you know, what could be this very large-scale enterprise, um, you know, mostly because they are opinionated about things like sales, marketing, product, software engineering, uh, and so on. Um, and I think that's gonna be a really cool, cool thing to see.

   4. AMAndrew Mayne27:49

      Marc Benioff had said something along the lines of that they weren't gonna be hiring any more software engineers, which, uh, maybe they overhired too, I don't know, but then that they were gonna be in- increasing the number of salespeople. And I think that often people hear the word sales, and they think somebody who calls you up randomly or cold calls, but sales is actually, a big part of it is people who are networked, who know a lot of other people, and I think that's what he was talking about, was what was gonna be really valuable to the growth were humans with human connections. And is this something you've seen data to back this up or to see this as a high-growth area?

10. 28:20 – 31:35

    Why EQ and soft skills matter

    1. RCRonnie Chatterji28:20

       Yeah, a lot of the research, um, coming out on this is showing that EQ matters a lot.

    2. AMAndrew Mayne28:25

       Mm.

    3. RCRonnie Chatterji28:25

       You know, a lot of people think in this world is getting more and more technologically sophisticated, all of a sudden, the, the soft skills, the social skills, being able to connect with people would be less valuable. It's actually the opposite.

    4. AMAndrew Mayne28:33

       Yeah.

    5. RCRonnie Chatterji28:34

       Once you make these, um, abilities and these capabilities democratized to be able to write code, for example, then some of the other things actually start to matter more in the market. And so I'm not surprised at all that salespeople who have, you know, deep technical knowledge, and we have many here in, in Brad's org and across the organization, are gonna be at a premium ar- around, um, around the world. 'Cause those are people who are gonna be able to connect the dots, use their EQ, plus their technical expertise to solve problems. And I feel like, uh, when you're thinking about what skills, uh, we want in the economy, that's gonna be a key part of it, as well as critical thinking and decision-making. We're still gonna need people to identify those problems to chase after, right? And that's where Brad talked about the agency, combined with the ability to target the right problem, is gonna be at such a premium. I expect that to be really important.

    6. AMAndrew Mayne29:16

       I've seen in tech, I think there's this overindexing on IQ and horsepower, and, uh, I'm a big believer that I think these systems are gonna be able to do just about any cognitive task we can think about. But you, you brought up EQ, we think is a really important one. I don't think that enough attention gets paid to that because I, I know some small companies that scaled really big, and they built great products. I can't get anybody on the phone.

    7. RCRonnie Chatterji29:37

       [chuckles]

    8. AMAndrew Mayne29:37

       I can't talk to anybody because they're just focusing purely on the technical component enough, where they exist in the network of people and everything else like that. And what are ways that somebody right now who wants to be, you know, find themselves in a, you know, very aligned position with the future, how do they build these skills? How do they work towards that? And how do organizations find people or foster that?

    9. RCRonnie Chatterji30:00

       I mean, I think it starts, uh, in schools. Like, you know, one of the really exciting things about the moment we're at is, um, education's gonna change. And I know that also creates a lot of excitement and anxiety, but I think so many things that we're learning in school... I have younger kids, and so in elementary school grades, um, they're gonna be even more relevant. You know, what are you teaching people when they come into pre-K or kindergarten? You're teaching them how to be a human, and I can't think of a better set of skills to learn now- [chuckles]

    10. AMAndrew Mayne30:24

        Yeah

    11. RCRonnie Chatterji30:24

        ... than how to be a human, 'cause that's gonna be sort of how you become a better complement for this amazing intelligence. You know, as an economist, you think about two constructs: substitution, which creates a lot of the anxiety, but also complements. If humans can become complements to intelligence and leverage it with agency, that is gonna be the unlock. And I feel like a lot of schooling in the early stages, even now, and it'll be more so as we go forward, is teaching those kind of soft skills and how to be a human. Later on, critical thinking, financial numeracy with numbers, still gonna be really important. I mean, my kids have calculators, but I still wanna teach them how to do multiplication tables.

    12. AMAndrew Mayne30:55

        Mm.

    13. RCRonnie Chatterji30:55

        Dictation software works really well. I still teach them how to write. You'll need those skills, and you'll need a sense of some other kind of higher order cognitive skills, resilience, grit, things that they're gonna need to adjust to these changes in the market. So when a CEO says, "Look, we're looking for more of something like this instead of that," um, students in the future are gonna be able to prepare to pivot in the right way and have that baseline skill. That's kind of how I think about people preparing. I think education will play a big role. I think work experience at great organizations can play a role, too. Those are the two areas.

    14. AMAndrew Mayne31:22

        I've been advising some students, and I don't wanna name the college, but it's in-... the Bay Area. It's a pretty good college. Uh, they have a pretty good CS, computer science program. Do you know how many days they spent

11. 31:35 – 36:11

    Education for the AI era

    1. AMAndrew Mayne31:35

       in the last semester learning how to use tools like Windsurf or Cursor?

    2. RCRonnie Chatterji31:40

       I, uh, tell us, I-

    3. AMAndrew Mayne31:42

       Zero.

    4. RCRonnie Chatterji31:42

       Oh, gosh [chuckles]

    5. AMAndrew Mayne31:43

       Zero. None. None of their professors have taught them anything about how to use AI coding agents yet.

    6. BLBrad Lightcap31:47

       They're probably all using it in the background.

    7. RCRonnie Chatterji31:48

       Yeah. [chuckles]

    8. AMAndrew Mayne31:48

       Oh, yeah, they are.

    9. RCRonnie Chatterji31:49

       Yeah.

    10. AMAndrew Mayne31:49

        And, and I'm also tell the ones that aren't, I strongly encourage them to do that, and I think that was, that was sort of for me, a surprising thing to find out that at that level, they're about to be put out in the workforce, and they're not even getting a day... And I understand, you want them to understand the fundamentals, you want them to understand that, but you know, they're gonna be applying for jobs. I help them put together projects and stuff so they can get jobs from places. But what is OpenAI see its role in policy, both from education and policymakers and stuff, and trying to advise or influence?

    11. BLBrad Lightcap32:19

        It's a good question. I think, you know, there, there's no question that we're headed toward a, a, an overhaul, I think, of kind of how the education system works. I think that will be a positive overhaul. I mean, you know, at the most kind of reduced level, right? What, what is it that we're building? You've got this thing now that is this, uh, kind of personal tutor of every person on Earth, right? It- and as it gets better, it will start to understand you better. It'll understand, understand your rate of learning better. It'll understand how you like consuming information, right? Do you-- are you more visual? Um, are you more quantitative? Uh, do you need things explained certain ways? Um, we've had... With the amount of feedback we get from people, for example, even with, uh, with children who are dyslexic, trying to learn-

    12. AMAndrew Mayne32:58

        Mm-hmm

    13. BLBrad Lightcap32:58

        ... and the impediment that that creates in the learning process, and ways that AI can unblock, uh, you know, learning for those, for that population, um, it's consistent. And so, uh, I think that, you know, the, the entire kind of way that we think about education and what education is in the country will, will have to adapt. I think it'll be good, though. I think it will force, in some ways, our systems to think about, you know, what are the ways that people will use these tools in the future? I think, uh, we... You know, the, the example you gave is in some ways surprising, but in some ways not. Um, I think the, the people adapt faster than the institutions. Um, but the question here will be, you know, how do we work with policymakers and with the institutions themselves to try and help the institutions adapt? I think the ones that do, though, will have this incredible accelerant. I think that you will see, uh, the outcomes, uh, among students, um, and the, the ways that they think about, uh, you know, what this tool can do in the classroom, uh, will, will just fundamentally change, uh, for the better. Um, and it will also then free up teachers, free up students to spend more time on things that are going to be the kind of high leverage skills of the future that Ronnie mentioned. So, um, things like decision making, uh, things like critical thinking, uh, you know, tool-based problem-solving. Um, how do you, you know, how do you kind of develop agency, uh, and conviction early in children? I think that that type of thing is going to be, you know, super important, as opposed to a curriculum that today is, you know, reinforces things like memorization, uh, regurgitation, uh, and so on.

    14. RCRonnie Chatterji34:30

        Yeah, and I also say, I mean, I'm pretty optimistic that we can make these changes in the education system, and I think it's gonna come from teachers and students, the way Brad's talking about. Like in the early '60s, uh, President Kennedy said we were gonna put a man on the moon, and if you look at what we actually had in terms of national assets at that time, and like the scientific capabilities, um, that was pretty far off goal. But during that decade, we dramatically increased the number of people doing PhDs in sciences-

    15. BLBrad Lightcap34:53

        Mm

    16. RCRonnie Chatterji34:53

        ... and engineering as people geared up for this challenge. And so I do think there's a really strong role for leadership across sectors to kind of sound the clarion call and say, "Look, this is where we're gonna go." And I, when I think about OpenAI, I think about we have a-- we have the best information about where the technology is going. That's an important role to play, to let people understand, here's what we're building. And other people in society, education leaders, government leaders, business leaders, and other sectors will be able to see it from their perspective. But if we put that, that call out there, I think you're gonna see a lot of dynamic, dynamic changes across... And, you know, Brad and I are both, uh, loyal Dukeies, of course.

    17. AMAndrew Mayne35:24

        [chuckles]

    18. RCRonnie Chatterji35:24

        And at Duke, I expect the curriculum in computer science, uh, and in economics, to be really different five years from now-

    19. AMAndrew Mayne35:30

        Mm

    20. RCRonnie Chatterji35:30

        ... in a lot of positive ways, and I expect a lot of experimentation, you know? Beyond whether you can use ChatGPT to study or, uh, how you regulate in the classroom. As a professor, really important points. I don't wanna downplay that.

    21. AMAndrew Mayne35:40

        Mm.

    22. RCRonnie Chatterji35:40

        But more important is, how are you gonna use this stuff to do new stuff, topics in your curriculum, help students who maybe can't learn from a graph but could learn from an oral presentation or, you know, teach students the same thing, though in three different ways, so everyone in the class gets it. There's so much amazing stuff that can happen. I do think it'll happen, and I think we have a history here in the United States, and you'll see this around the world as well, but I know the US the best, where we've actually responded pretty dynamically to some of these big challenges.

    23. AMAndrew Mayne36:04

        Can you talk a bit about OpenAI's engagement with educators and policymakers, specifically about what you are doing

12. 36:11 – 39:14

    Partnering with Cal State & educators

    1. AMAndrew Mayne36:11

       to facilitate?

    2. RCRonnie Chatterji36:12

       I can start with the example of Cal State University.

    3. AMAndrew Mayne36:14

       Mm.

    4. RCRonnie Chatterji36:14

       So, uh, you know, for those of you from California, spent a lot of time here, Cal State is like, you know, just the ultimate unlock for students who are first generation, whose parents, um, maybe they've come from another country, or they haven't attended higher education. Those are the kids that Cal State, uh, specializes in, and those are the, those are the students that Cal State has traditionally, for its long, illustrious history, taken to the next level. And so we're proud to, you know, to work with them, and, you know, this is something that comes from- from what Brad is talking about, the, the research and the deployment. Someone like me picks it up and says, "Okay, now that we're working with this great institution, how are we gonna maximize the outcomes for students when they go for that first interview? Can we prepare them with the skills they need to, to do well? Um, can we track their career outcomes over time and say, 'You know what? Having access to this intelligence made a huge difference'"? And so that engagement has led me to work with administrators at CSU, uh, researchers, and once we get everything in order, students, um, ultimately, to make sure we're gonna make a big difference. And so for me, it's been a great interaction, and it's been facilitated by the deployment we've done with CSU. So that's an education example.

    5. BLBrad Lightcap37:15

       I mean, education's been, for us, the fastest growing segment that uses ChatGPT and other OpenAI tools. So, um, it surprised us a little bit, I think, in some ways. Uh, you know, we knew early on when we launched ChatGPT, that it had a resonance with students, and it was, um, it was clearly applicable to the way that people wanted to learn.... um, engage with information, engage with knowledge, test their own learning ability and, and skill set. Uh, and what-- funny side story is we-- when we-- right after we launched ChatGPT, we launched it in November of '22, we had basically the kind of remainder of that school year, um, where I think there was a lot of upheaval, I would say-

    6. AMAndrew Mayne37:52

       Yeah

    7. BLBrad Lightcap37:52

       ... in that sector, and you probably remember this.

    8. AMAndrew Mayne37:54

       Yeah.

    9. BLBrad Lightcap37:54

       Um, and for a while, we all looked at each other here, and we're like: Man, we, you know, I don't know what this is gonna ultimately lead to for us-

    10. AMAndrew Mayne38:00

        Yeah

    11. BLBrad Lightcap38:00

        ... but, you know, and, and is all this stuff ultimately gonna get banned? Something over the summer of '23, as the school year changed over, I don't know what it was that went around, but y- when, when everyone came back in the fall, the level of enthusiasm, and I think the level of forward-lookingness of the, of the leadership in kind of the broader American educational system, uh, had changed, and it was, uh, they-- we had a lot of people coming back to us and saying: "Yeah, you know, actually, this is, I think, one of the best things that has maybe ever happened to this, this industry. It's meaningfully changed how my students are learning. Uh, we're starting to develop perspective on how people are really using this. And not only do we have that perspective, I actually wanna extend and develop that perspective so that I can figure out how to better use this in my classroom, work it into my curriculum, challenge students in new ways," right? "Figure out ways that, um, we can actually have it surface gaps and vulnerabilities in certain student populations that maybe aren't getting the attention they need." So all that work now kind of has culminated in work that we're doing internally with an EDU team here at OpenAI to try and work more with the sector. Uh, you know, Ronnie mentioned the Cal State example is just one of many examples of-

    12. AMAndrew Mayne39:05

        Mm-hmm

    13. BLBrad Lightcap39:06

        ... of ways that we're, we're trying to, to, to engage, and so part of it is product building, part of it is, is engagement, part of it's policy, but we are gonna take kind of a whole of company approach

13. 39:14 – 42:00

    From bans to buy-in in schools

    1. BLBrad Lightcap39:14

       to it.

    2. AMAndrew Mayne39:14

       I remember, uh, I won't name the school system, but they famously had banned it. They're like: "Oh, we're banning this to use in the school system." And then I'd heard anecdotally that a number of teachers within had been using it and having really positive outcomes for many of the reasons you pointed out. You know, I helped do a study when I was here, and one of the number one feedback we got was, from students, was it doesn't judge you. ChatGPT doesn't judge you, and it was a great way if you're feeling you're going behind or whatever, to go ask questions and get up to speed. And then we saw that some of the teachers were getting really good results in the classroom and then went to the school system and said: "Listen, no, we, we need this. This is something we've been sorely lacking." And there was a kind of a famous reversal on that, and that was, I think, like... That happened faster than I expected. And would you say that you're seeing probably a faster adoption than you'd been expecting, or was I just not with it?

    3. RCRonnie Chatterji40:04

       Uh, I've been seeing it. I mean, I think you're right. There was that transformation sometime in 2023, where people realized, "Wow, we can unlock a lot of value here for students and for professors." And maybe what happened over that summer, I don't know, maybe it happened for me, one of the biggest barriers to innovation for new faculty members, let's say, at a university, is developing a new curriculum. So someone says: "Look, hey, this topic's hot. Why don't you develop a whole class on it?" Professors wanna help their students. They wanna introduce some new material, but there's a huge cost as it puts together against your research, your other teacher responsibilities. But all of a sudden, I can use the tools in ChatGPT to develop that syllabus. I can make a great entrepreneurship in AI syllabus now much more quickly than I could before. It can help me decide how to-- decide what classes I'm gonna teach, uh, the slides I might use, the readings I might assign, even discussion questions for my students. When you lower the barriers to creating new content, it becomes even more exciting for a professor to try something new or a teacher in the K-12 context. So I feel actually that now as faculty and teachers are unlocking that, you're seeing a lot more adoption. I think the other thing is that, um, at the end of the day, introducing students to new ideas they wouldn't have had anyway or otherwise is such an amazing thing. Any teacher, right, sees that, and there's a spark, and that's gonna make them wanna find a way to use those tools. We definitely need, you know, rules and policies they'll set up at the school level. That's really important. When and how students use these tools, that's, that's gonna be key, and I imagine those will be worked out, and there'll be variation across different educational institutions. But, uh, but I have no doubt that it's gonna be a huge part of education, uh, given how valuable it is.

    4. AMAndrew Mayne41:28

       We talked about this a little bit, uh, before we started recording, which is there has been years and years, you know, centuries of speculation of what happens when you have intelligent systems. Well, how is that gonna disrupt the world, whatever? And now we're in the place we're actually starting to see this happen, and we realize that I think a lot of it was fanfic, and it was just so scenarios, and the scenario is playing out, and it's very different. And I think your approach has been you're very evidence-based. It's the idea that you prefer research over theory.

    5. RCRonnie Chatterji41:53

       Mm-hmm.

    6. AMAndrew Mayne41:53

       And where are you directing your research right now for impact and guidance for policy?

14. 42:00 – 45:46

    Ronnie’s research: sectors, geography, communication

    1. RCRonnie Chatterji42:00

       For my work, at least on the economic research part, that narrow piece of it, I've been thinking about a couple things. One is, which sectors are gonna be affected first? I think what I can do to help the organization, but also the world, is if I can identify that sectors like healthcare and education might, uh, be transformed more quickly, let's say-

    2. AMAndrew Mayne42:17

       Mm

    3. RCRonnie Chatterji42:17

       ... than retail and finance, that's a really important insight to provide to the world. Because if people are in those sectors and thinking about their jobs and what they can do, it both unlocks opportunity on the enterprise side, but also helps people plan their careers and make their investments. So one of my big goals is to figure out which sectors are gonna be influenced first and by how much. The next thing I've been thinking a lot about is which countries, which geographies are gonna be most affected? I also think that's really helpful. When I look at previous technological transformations where people were left behind, a lot of the impacts were geographically concentrated-

    4. AMAndrew Mayne42:47

       Mm

    5. RCRonnie Chatterji42:47

       ... let's say, for in big manufacturing hubs in the Upper Midwest and the United States during the last transition. And when you look at that disruption and the scarring that happened over many decades afterwards, I realized that if we can develop good indicators of where, in terms of geography, these effects are gonna be most pronounced, that's gonna be really, really helpful. So my team spends a lot of time on that as well. And the last piece is communicating it. You know-

    6. AMAndrew Mayne43:07

       Mm-hmm

    7. RCRonnie Chatterji43:07

       ... a lot of economists, or if I was in academia, that's sort of the last piece, the piece you, like, tack on there and say: "Okay, well, you know, somebody besides my mother is gonna read my paper with its, you know, thirty-three appendices." In this job, especially given the privilege that I have to be close to the researchers who are changing the world, I gotta be able to translate that for, for real people. So those are the three aspects, I think, sort of where, uh, geographically, which industries, and explain to the world how that's coming, and that's kind of where the evidence base that I at least wanna develop is coming from.

    8. AMAndrew Mayne43:34

       It, it seems like a big unlock that kind of went unnoticed was when ChatGPT went to... from you had to have a credit card, you had to have, you know, your-... log in and all that, to now you just go to openai.com, and you can just use it, which just increased accessibility around the world. And, you know, I think it's in iPhones now, and seeing that kind of roll out there, which I think was a really good democratization of it, was the idea that it went from, you know, only a certain part of the world was gonna be able have access to it, to now anybody in, you know, unrestricted countries, you know, are able to use that, which I think is great. I think that's, that's-- it's very cool. You mentioned, though, research into sectors are gonna be affected. What have you found out so far?

    9. RCRonnie Chatterji44:15

       So far, I think the sectors that are less regulated, where there's less, let's say, sort of red tape, rules of the road that need to be followed, um, those are the sectors that are gonna change the quickest, right?

    10. AMAndrew Mayne44:24

        Mm-hmm.

    11. RCRonnie Chatterji44:25

        And so in some sense, like healthcare, for very good reasons, we have sort of HIPAA protecting-

    12. AMAndrew Mayne44:29

        Mm

    13. RCRonnie Chatterji44:29

        ... patient privacy. We have rules on how care is delivered. These are really important parts of the US healthcare system, and they are similar around the world. Those are sectors that are gonna be harder to change, right?

    14. AMAndrew Mayne44:37

        Mm.

    15. RCRonnie Chatterji44:37

        And they're gonna be slower to adopt new technological tools, and that's not just true for AI. It's true for previous, uh, incarnations of technology. IT moved slower into healthcare and education than it did to other sectors. So I think where you have sort of high levels of regulation and compliance requirements, you'll see slower adoptions and those jobs changing slower as a result. Doesn't mean we can't unlock a lot of productivity in healthcare delivery and education. Um, in education, we're seeing this on the student side and teachers, but overall, like implementation, I think you'll see it move faster in sectors where the regulations aren't as sort of significant as they are in those two sectors. That's, that's key. I think the other thing you'll see is where the workforce is gonna embrace it. Brad made a good point earlier. It's like this happened with enterprise software. People brought tools to work, like new storage solutions, and then their CTO was like: "Hey, what are you doing there?" Right? And then eventually they're like: "Wait, this thing you're bringing is actually... the whole company should adopt it."

    16. AMAndrew Mayne45:26

        Mm.

    17. RCRonnie Chatterji45:26

        In sectors where you have highly skilled workers who are bringing these tools to work, using things like ChatGPT, building on our API, those sectors are gonna transform more quickly, and that's why I think places like finance, right, sort of research, drug discovery-type organizations, that's places where I think you're gonna have those people bringing it to work to solve problems. I expect those sectors to move pretty fast.

    18. AMAndrew Mayne45:44

        What career advice are you giving your children?

15. 45:46 – 48:14

    What should we tell our kids?

    1. RCRonnie Chatterji45:46

       [chuckles] That's the hardest question. Um, and what I tell my kids is, when I was growing up, I was the son of immigrants, right? So, like, if your parents are from a certain part of the world, the advice you might get would be, "There's only two choices," right? There's, like, "Be a doctor or be an engineer, and if you're really creative, you can be a biomedical engineer." Okay, so there's, like, a narrow set of choices.

    2. AMAndrew Mayne46:05

       Mm.

    3. RCRonnie Chatterji46:05

       Why would parents give those advice to their kids? It's because it's like they would predict these are gonna be the stable professions. But during the course of that generation, healthcare changed a ton, right? We had managed care. A lot of physicians worked for hospitals. The job is so different than the generation that was giving that advice thought it would be. Engineering, I mean, Brad talked about this earlier, has changed dramatically.

    4. AMAndrew Mayne46:23

       Mm-hmm.

    5. RCRonnie Chatterji46:24

       We never had full precision and full predictability to say, "Your kid should do this." In fact, many of the jobs we have today, we didn't even have names for them in nineteen forty.

    6. AMAndrew Mayne46:33

       Mm.

    7. RCRonnie Chatterji46:33

       So first, I have a dose of humility, which is like, it was never easy to tell our kids what to do or guaranteed they would listen. For my kids, though, I reflect back on what we talked about, which is you've gotta learn how to be a critical thinker and identify problems, develop a point of view to have the agency Brad's talking about. You have to have the neuroplasticity, resilience, flexibility to be able to adapt because the world is gonna change a lot. If you think about what's happening in AI, changes to our climate, changes to geopolitics, you're gonna have to adapt a lot. And the last piece, I do think that the EQ and the financial numeracy will be really, really important as they navigate their careers. In terms of predicting what their job title is gonna be, I don't think I have any more information than my parents did, and, and I think they're gonna be okay.

    8. AMAndrew Mayne47:10

       It's an interesting note that, like, the title may change, or excuse me, the title may stay the same, but the, the work may change, right?

    9. RCRonnie Chatterji47:16

       Mm.

    10. AMAndrew Mayne47:16

        One of my favorite anecdotes was Dan Bricklin, the guy who created VisiCalc. He had, uh, in the nineteen seventies, he was a high-level programmer, extremely capable, and programming was changing a lot then, and you're moving into object-oriented programming and libraries and stuff, and he thought that programming jobs were gonna become more scarce. And so he actually left to go get his MBA, and it was while staring at the back- the blackboards with all the figures, he's like: "Why doesn't somebody make, like, an electronic spreadsheet?" And then he invented VisiCalc.

    11. RCRonnie Chatterji47:43

        Awesome.

    12. AMAndrew Mayne47:43

        And it was just funny, though, to read how he thought that programming job was ending in the nineteen seventies, and I kinda think that it is changing a lot now. But you mentioned about how if you're somebody who's running, you know, an AI software tool, you're kind of managing a project. It's project management, and having the technical skills is certainly critical, and I've heard this a lot, like, "Why bother learning to code?" And I'm like, you know, do I want an airline pilot that doesn't know aerodynamics?

    13. RCRonnie Chatterji48:09

        Mm.

    14. AMAndrew Mayne48:09

        You know, what are other skills you think are still gonna be mattering, you know, in the future?

16. 48:14 – 52:04

    What history teaches us about disruption

    1. BLBrad Lightcap48:14

       Well, I think the direction of travel of technology is toward-- always toward individual empowerment. I think if you look at trend-like, trend-wise, every kind of past technological revolution and every, uh, every past phase change, it, it always, uh, drives toward the individual and what the individual is capable of.

    2. AMAndrew Mayne48:32

       Mm.

    3. BLBrad Lightcap48:32

       So, you know, nineteen hundreds, you had forty percent of the US economy working in agriculture. Today, it's two percent, right? And we produce some multiple, uh, more, you know, eco- uh, uh, agricultural output than we did in nineteen hundred. Uh, and you can run a large farm with a small fraction of the number of people it would have taken to run a large farm in nineteen hundred. And so now what happens when that-- you know, you get that same phenomenon kind of applied wi- widely across the economy and in, in sectors where historically we haven't had that phenomenon, right? But, um... And I think that there are a lot of places that would benefit from a phenomenon like that. Um, and that's not to say that there's a, you know, it's an argument for job displacement, for example, but, um, uh, I think that the argument here is toward, uh, you know, higher economic output, kinda per unit of input. Um, and that fundamentally is what drives economic growth. Um, but people are resilient. They find other places to, to, to, to, to go work.... um, and when you create the kind of local level, the micro level empowerment, you tend to create, you know, have the second and third or- third order effects of, of other jobs that get created that, that we couldn't have foreseen, uh, you know, uh, in, in retrospect. And so, um, you know, it would be weird to tell someone in 1900, for example, that there are people today whose entire job, uh, is to make content for a small little device, uh, that people consume, you know, many, many hours a day, and that those people can make a, a, a perfectly kind of viable economic living. Um, a- a- it would seem like a-- It would seem like something that was almost kind of unimaginable that, you know, would exist, but it does. Um, and so there will be that se- kind of second set of changes and second and third order impacts. Um, but I think that, you know, I, I always kind of come back to, uh, the, the, the, the kind of individual empowerment point of, um, the, the direction of travel being toward, uh, more people being able to do a lot more with a lot less. Um, and then, you know, their labor, uh, and, and their ideas and their creativity creating kind of the downstream opportunity for, for people that, um, you know, twenty years ago would've been doing a different job.

    4. AMAndrew Mayne50:28

       The example I use is, in ancient Mesopotamia, ninety-eight percent of people were in agriculture, and all of a sudden somebody invents the plow. And if you're thinking, "Well, we're all farmers, we're doomed," that may have been a mindset, but the reality was that led us to inventing education and healthcare and actually governments and all these things. And I think that that's, to your point, like, that's the thing I think we sort of forget, is that we've had huge, huge upheavals, like literally taking... going from ninety-eight percent and, you know, in agriculture, to all of a sudden where they go. And, and, you know, if we thought back in the year 1800 and said, "Hey, uh, we're gonna get rid of almost all farm jobs," people would be thinking, "Well, what are we gonna do? There- there's gonna be massive problems." And we realize that, like you said, we created all these new kinds of roles, entire sectors of the economy and stuff, and it's, it's always hard to predict, though. It's always hard to predict where that's gonna be, 'cause we just imagine the future as sort of the present, but with, like, shinier clothes and robots-

    5. BLBrad Lightcap51:25

       Right

    6. AMAndrew Mayne51:25

       ... and flying cars, and-

    7. RCRonnie Chatterji51:28

       A- and part of-- I think this is part of the job of research and, and organizations that are close to, to technology, produce the information to help people make the best decisions.

    8. AMAndrew Mayne51:34

       Mm.

    9. RCRonnie Chatterji51:35

       You know, Brad talked, talked about agency. Agency requires sort of an individual characteristic, right? But it also will require information about what the market looks like, where technology's going, and so I feel that as a big responsibility in what I'm doing here. You know, our mission is to benefit all humanity, and to do that, I wanna make sure people have the information they need, to the best of my ability, right? We can't predict with perfect fidelity-

    10. AMAndrew Mayne51:54

        Mm

    11. RCRonnie Chatterji51:54

        ... what the world's gonna be. And I can't tell my own kids, much less anyone else's kids. But if I can give good information based on research, that'll help people make better decisions, and I, and I do think ultimately find a place where they can flourish.

17. 52:04 – 55:35

    Expanding participation in the economy

    1. BLBrad Lightcap52:04

       We should also keep in mind there's a lot of people who can't participate in the economy the way that they would like because of extenuating circumstances in their life-

    2. RCRonnie Chatterji52:11

       Mm-hmm

    3. BLBrad Lightcap52:11

       ... um, that are, you know, born in part of things like lack of access to healthcare, lack of access to education. I mean, we talked a little bit earlier about what are the impacts that we might see in parts of the developing world, where access to those resources is scarce. You know, there's the direct impact that we have of how do you make s- make it easier for someone to scale a small business? That's gonna be a clear, present, and I think very positive set of things that, you know, that happen. There's a kind of second and third order, almost hidden impact that we also, I think, you know, Ronnie has the challenge of having to figure out how to measure this.

    4. RCRonnie Chatterji52:42

       Yeah.

    5. BLBrad Lightcap52:42

       But what happens when you enable people to better manage healthcare, right? Or better manage the healthcare of someone who is dependent on them, you know, a, a, a sibling or, you know, a parent or something like that. What happens when you raise the education level, you know, and, and the educational outcome levels by two percent-

    6. RCRonnie Chatterji52:57

       Mm-hmm

    7. BLBrad Lightcap52:57

       ... right? And what is the kind of second and third order effect of that as a downstream i- impact on, on the economy and on, you know, on, on, on, uh, people's ability to participate in the economy? So, uh, y- you know, there's, there's kind of the direct way to look at this. I think there's also the indirect way to look at this, and, uh, that's right. You know, I just defer to, to, to Ronnie on-

    8. RCRonnie Chatterji53:14

       Yeah

    9. BLBrad Lightcap53:14

       ... on whatever he can measure.

    10. RCRonnie Chatterji53:15

        I think, uh, I, I think this is a really good point, though, Brad, and something I've been thinking it's hard to measure but important here is coaching, mentoring-

    11. BLBrad Lightcap53:21

        Mm

    12. RCRonnie Chatterji53:22

        ... counseling. When he talked about people who can't fully participate in the economy, my mind immediately went to, there's so many people who have so much to offer, but maybe, uh, they're neurodiverse, or maybe they need a coach or someone to help them get to the next level, or a level of counseling and behavioral health, which we don't have broad access to in many cases.

    13. BLBrad Lightcap53:38

        Mm.

    14. RCRonnie Chatterji53:38

        It's expensive, and depending if you live in a part of the country or the world where you don't have access to that, you're sort of sidelined. And, you know, economists will use the technical term of labor force participation. What it really means is you're sidelined.

    15. BLBrad Lightcap53:48

        Mm.

    16. RCRonnie Chatterji53:48

        You, you can't participate. But if we can help people, uh, compared to having no help now, some help, um, we could help them participate in the economy more fully, and that can unlock a lot of potential. I do think any equation, any cost-benefit analysis, any sort of, uh, sort of reckoning about what's gonna happen to the economy, needs to also consider people who aren't participating the way they could now, getting enabled. I think, I think that's a really important point, and we'll try to measure it, but even now, I think it should be thought about, um, in that way.

    17. AMAndrew Mayne54:15

        I think we, in, in developed economies, sometimes have a habit of forgetting the things we have that other people don't have. Like, if you want legal help, you hire a lawyer, but if you're living in a substance-level, you know, economy, like, that's hard. You can't do that. You know, financial planning-

    18. BLBrad Lightcap54:33

        Mm

    19. AMAndrew Mayne54:33

        ... everybody would benefit. I mean, the people who benefit most from financial planning are people who haven't had access to financial education, and I think that's an exciting area, and I think that certainly, the, we're going to start seeing those effects eventually, when you start to see what happens when you unlock so many of the people around the world by just the circumstances of where they were born and had access to, didn't have access to that information or expertise, and I think that's gonna be very cool to see how AI makes that possible. We've seen just through ChatGPT alone, how people are able to use it as educational tutors, helping translations, and helping small businesses, helping people who have to work in communication, et cetera, and that's been a benefit. And I think that we've seen in some situations where you have a tool, let's say translation, people often think like, "Oh, that's gonna decrease the need for translators," but actually can increase it, because all of a sudden, a company that never did business overseas now can, one, send out query letters, et cetera, now find themselves dealing with an entirely different country and economy, and that's increased the demand for a human skill. Do you think this is gonna be happening in other places? Do you think this is gonna be just a big where-- area of opportunity, or is it just gonna be

18. 55:35 – 59:19

    AI increases demand

    1. AMAndrew Mayne55:35

       minimal?

    2. BLBrad Lightcap55:35

       ... uh, look, what we actually see in our, in our data at, at OpenAI is when we cut the price of our models, which is really cutting the price of intelligence, we see a disproportionate increase in demand for that model. And so, uh, and we see that with ChatGPT too. When we make better intelligence available and more of it available, uh, people use it more, right? And we don't see the upper bound yet on h- kind of how intelligence and demand correlate. It seems like there's just this relationship that the more we can make really great intelligence available more cheaply, the more consumption there will be around that, that thing. And so if you think about kind of how that plays out in an economic context, uh, you know, what happens when you've got... You know, if you can cut the price of good legal advice, for example, by a factor of a hundred, um, you know, do you see a corresponding thousand X increase in the demand for legal services? Same in healthcare, same in education, same in software engineering, same in any other thing. Uh, and I don't think we've, we've quite come to terms with what that means.

    3. RCRonnie Chatterji56:32

       Mm-hmm.

    4. BLBrad Lightcap56:32

       Um, and if you think about, you know, thousand X demand increases kind of across every segment, um, that's a lot of strain, right? That's a lot of demand in, in, in the economy, which is a good thing. But, you know, I think there's-- and ultimately, people are gonna have to kind of like organize themselves to figure out how to serve, uh, all of that need and, and, and, and be there to serve those, you know, that demand and, and those, and those needs. Um, which means that you need people who are gonna come up with ideas, take initiative, go start things, go create things, right? Um, and so that's the dynamism, I think, of the economy that's underappreciated when we talk about what the impact of AI will be. Uh, and it's the thing that we see at a very, you know, at a micro level now at OpenAI, but, um, I think, you know, w- we should look at as, uh, as we make intelligence... You know, Sam has a phrase I love, "Too cheap to meter."

    5. RCRonnie Chatterji57:18

       Mm-hmm.

    6. BLBrad Lightcap57:18

       Um, what does it really mean for, uh, the world's ability to, uh, to create output? Um, and then, you know, ultimately, I think that the downstream impact of, of that we'll find is that it actually had an incredibly enhancing effect, uh, on, on, on jobs, on productivity. Uh, and, you know, that's, that's the positive future I think we're, we're excited about.

    7. RCRonnie Chatterji57:37

       And as an economist, I'll just say this could be really exciting for people in those professions in the following way: when you sort of make intelligence too cheap to meter, and that intelligence is providing, let's say, legal advice or financial management advice or advice on real estate, all of a sudden, you get a bunch of new people accessing that, that never could access it before, right? So it's opening up the market, number one. And then once those people sort of start making decisions, right, buying a property, right, making a transaction, um, engaging with legal services, they're gonna have higher and higher level needs, right? And all of a sudden, the business that they're running is more complex, or they have two properties to manage. And then there's a bunch of people who are trained in those fields who never served this market before, but now they're gonna come to them with more complex questions. And if that accelerates, that could create tremendous opportunities in those fields. It will be about deciding which part of the market to focus on, what kinds of skills you want to leverage. But I think for real estate agents and insurance brokers and financial advisors, there's a potential for this to actually onboard a tremendous number of people who never would have accessed their services to begin with. That's the excitement of reducing the cost of intelligence dramatically, which is what's happening.

    8. BLBrad Lightcap58:37

       Yeah.

    9. AMAndrew Mayne58:38

       I would say an example that's, I think, kind of very close to home here, is that every time there's a new model or some new technology from OpenAI, you'll get some pundit will go, "Well, how come they're still hiring?" And I think I, I, I'm a growth mentality person. I'm like: Well, of course, they're hiring because... And I want to get a, to get a, a sanity check on this. My prediction I've told people is more people are going to work for OpenAI after AGI than work before it. That it's not like all of a sudden, "Great, we've got a new tool." You don't need people doing these roles before. The roles change, but you're going to want more people. Do you think-- would you agree about my assessment of the trajectory of OpenAI, more people here after AGI?

19. 59:19 – 1:02:05

    Why OpenAI will grow after AGI

    1. BLBrad Lightcap59:19

       I think it will be more people after AGI. I think I kind of go back to what I said earlier of how do you, you know, the, the kind of demarcator of, uh, of the impact of AI being about kind of more output-

    2. AMAndrew Mayne59:29

       Mm

    3. BLBrad Lightcap59:29

       ... per person, right? And so you now have... You know, you get this kind of scale down basically in kind of how large of a firm or company can be run by some number of people. So, you know, a large enterprise had to be run by 100,000 people before. Maybe that number comes down to 50,000, eventually 20,000, you know, 5,000, 1,000-

    4. AMAndrew Mayne59:48

       Mm

    5. BLBrad Lightcap59:48

       ... you know, 100, and so on and so forth. Um, and maybe it's, you know, it's an even steeper falloff than that. Um, and so I, I suspect and hope OpenAI will be kind of no different in that, you know, especially given what we do.

    6. AMAndrew Mayne59:59

       Mm.

    7. BLBrad Lightcap59:59

       Uh, and so, you know, I, I think, but I think going back to also the point I made around what do we see as the second and third order impacts of the deflationary aspect of intelligence, right? Is it in-- it creates significant and disproportionate demand for the service.

    8. AMAndrew Mayne1:00:14

       Mm.

    9. BLBrad Lightcap1:00:14

       And so what does that mean for us? It means we need more people that can help work with more users across more use cases. It means we need more people helping policymakers think about the problem. It means we need a chief economist. Uh, you know, if you'd asked me three years ago-

    10. AMAndrew Mayne1:00:28

        Yeah

    11. BLBrad Lightcap1:00:28

        ... if we would've needed a chief economist, I would've, I would've said, "I don't-- maybe in 2030." [chuckles] Um, but here we are. And so, uh, you know, I think that that's, uh... I think it will be more people, but, um, uh, and, and I think it is kind of somewhat consequence of both of the trends I just mentioned.

    12. AMAndrew Mayne1:00:42

        I am helping out a friend who's working on, uh, training models and stuff to help with, uh, cancer nutrition, and we were talking to somebody from OpenAI yesterday, and they said, "Would it be helpful to talk to the health team?" I'm like, "You have a health team?" They said, "Yeah, we do." I'm like, "Well, great." And then, you know, having a conversation with them, and that was a thing like, wow, this is... What a great area of expansion, and I think that, I, I hope that other companies are sort of thinking about how these tools really are augment and amplify and create opportunities for growth. Because I think that if you have good talent, you want to keep that talent and find more talent, not find a way to not need talent. I think that'll put them at a disadvantage if they're, you know, not being forward-thinking about that.

    13. BLBrad Lightcap1:01:21

        Yeah, I mean, if you can get incredible leverage on every marginal person, you know, 10x, 100x leverage that you could get, you know, 10 from ten years ago or something like that, like, in some sense, why, why wouldn't you want more people?

    14. AMAndrew Mayne1:01:32

        Yeah.

    15. BLBrad Lightcap1:01:32

        Um, you know, if Ronnie's team can now, you know, with a team of 10 people, do economic analysis across, you know, 10 different subjects or 10 different sectors versus, you know, two, um, because every person now is doing three or four times more, um, that's a, I mean, that's an amazing-

    16. AMAndrew Mayne1:01:50

        Amazing

    17. BLBrad Lightcap1:01:51

        ... thing, right? And so it just means that we, as a, as a company, are capable of doing more. And the thing that we kind of set out, "We'll, we'll handle that in 2026 or 2027," it's like, "No, no, we can do it right now."

    18. AMAndrew Mayne1:02:00

        Do you have favorite ChatGPT tips or advice you give people on using AI?

20. 1:02:05 – 1:05:08

    Favorite ChatGPT use cases

    1. RCRonnie Chatterji1:02:05

       ... I have a few. I think the coaching is so valuable. You know, you meet so many people who they say, "Hi, I'm a religious ChatGPT user," and you find out, like, they're not even logged in, or they don't know about deep research, and you're like: Oh, my gosh, there's so much more you can do. For me, the coaching has been so valuable on diet and fitness. Brad doesn't know this, but I'm training for a, um, [smacks lips] a big, uh, athletic adventure to play basketball at Duke, uh, at a Coach K camp. Okay, I've, I've requested time off-

    2. BLBrad Lightcap1:02:28

       Oh, nice.

    3. RCRonnie Chatterji1:02:29

       -he's got to approve it. [laughing] But I got to be in good shape, because otherwise I'm gonna get, like... I'm gonna, like, tear my ACL the first second I get out there. So ChatGPT is helping me over the next four weeks, like, really get in the best shape of, like, I guess, middle age. And, uh, how is it doing that? Well, it's looking at the food I'm eating and giving me advice and giving me calorie breakdowns. It's reducing the decisions I need to make by analyzing what I've had that day, and it's helping me track, uh, weight and, and other kind of fitness indicators. And so in doing that, I have this, like, map out to four weeks, which would have been really, really hard with the jobs we have and the travel that we're all doing to manage. And so I feel like that's a pretty simple one that you don't need super advanced tools to do, but it's really changed my outlook and made this possible. So that's my favorite one of this month.

    4. BLBrad Lightcap1:03:09

       The, um, the thing I do, especially now with o3, and I think o3 as a model, kind of broke through the, the barrier for me. It kind of crossed the chasm, uh, and I-- look, I-- all of our earlier models were great. o3, there's something deeply great. Um, and the thing I use it for is to actually, like, challenge me. So, uh, a, a lot of my job is, is I'm trying to make assumptions about how things work just based on kind of empirical observation of what companies are using us in certain ways, what users tell me they like or don't like. And, um, in some ways, you know, like I said early on, our job is to predict the future. Um, o3 has an incredible ability to actually be a question asker. So I think people think of ChatGPT as something that you can only ask questions to, um, but a lot of times, what I really want it to do is actually ask me questions and challenge my assumptions, and make an arg... a counterargument to me of why something works or doesn't work the way I think it might work. Um, and it's an incredibly effective thought partner in that regard, and it can be at really big things, [clears throat] you know, or it can be at really, you know, low-level, dumb things. I just got a puppy, uh-

    5. RCRonnie Chatterji1:04:11

       [chuckles]

    6. BLBrad Lightcap1:04:11

       ... and I've, you know, had dogs my whole life, and, uh, you know, we've, we've had a puppy that now is, um, uh, is, has been, uh, I would say, not the easiest when it comes to getting her to calm down and go to sleep. Uh, and, you know, my wife and I could not figure out how to, how to get her to do this. And so ChatGPT kind of being a, a, a resource for challenging our assumptions about what we thought we knew about puppy training, uh, for example, has been an interesting experience. [chuckles]

    7. AMAndrew Mayne1:04:36

       o3 is something special, and, and we talked a lot about, yeah, what happens when the models can, can push as well as pull in, and when they can kind of, you know, get you to think about a thing, and that has been just, just been amazing. o3 has really been a fun experience talking to. It's the first time I felt like it's not just, uh, something that's kind of telling me a thing that it looked up and versus something it thought about. Brad, Ronnie, thank you very much. This has been great, and I hope we can speak again in the future about this and maybe, uh, check on the progress of all of this.

    8. BLBrad Lightcap1:05:06

       Looking forward to it.

    9. RCRonnie Chatterji1:05:07

       Thanks for having us.

Episode duration: 1:05:08