ChatGPT emerged after OpenAI tested whether anyone would pay

Transcript

From the transcript TBPN publishes with the episode.

1. 1:09:11

   Yeah. When did when did did the API opportunity, like, really click for you? Because I do remember companies in that era that, like, quickly unlocked the power of of the API and and and grew tremendously. When did that opportunity click? Because you said initially that you're you kind of had some, yeah, don't know, concerns, kind of doubts, how useful was it gonna be? And then when did the consumer opportunity click?

2. 1:09:37

   Well, we, in 2019, 2019, had GPT-three. We knew we needed to build a product to be able to actually continue the mission, to be able to raise capital. But what did we want to build? Right? We're really here because we believe in AGI that's going to have this powerful, positive, transformative effect on society and we want to be part of it. And so we thought, well, maybe we could build something in health, and then you realize, okay, well, we're going to sell to hospitals and we're going to maybe hire We'll let other people do that.

3. 1:10:05

   Exactly, right? It's just like you have to go into one domain, and that means giving up on the g, the general. Right? It's like it feels like you're going to become That's interesting. A one particular thing, but we kinda wanna be supporting all industries at once. And so the idea was, let's build an API and let people figure it out. But this is totally not the way you're supposed to build a startup. Right? You're supposed to have a problem.

4. 1:10:25

   No one cares about the technology behind it. Add value to that problem. Focus on just that one thing. And so that's why that project was so hard. And in, you know, January 2020, February 2020, I that, you know, I, with the team, were going around trying to just find anyone that would be willing to try this API. And we were driving to different offices in in San Francisco being like, hey. We have this cool model, and it was hard enough to get people to take the meeting, much less to sign up their company for it. It was actually very fortunate. We found it we found a couple of good partners, and it was fortunate that that happened then because March 2020, suddenly, that was COVID. We weren't driving around to people's offices to try to beg them to use this, you know, this this budding new technology.

5. 1:11:06

   So it's really six months worth of grind, right, of really trying to turn like, when we when we started with g p d three, I remember it was, you know, that the inference code was not very well optimized. It was, like, don't know, a 150 or maybe 250 per token or something, and we just optimized optimized, got it down to, like, fifty milliseconds per token, which, by the way, today's models run much faster than that, which is kind of amazing for me just, like, seeing how how much fast we're able to run them with much greater intelligence. And I remember setting two goals for the team. One was I actually find one customer who's willing to pay, so literally get a dollar in for this thing. And the second is get a use case that we use at OpenAI every day.

6. 1:11:46

   That first one happened within the first couple months. So actually, that moment, was like, alright. Like, this thing is probably gonna work. But in order to get there, we had to do a bunch of, you know, just scaling the API and and really, you know, doing doing the product work. But that second one took much longer. Right? And that wasn't really until ChatGPT. And so if you fast forward a couple years, because this was, you know, mid twenty twenty when we when we first got that the API into the world, ChatGPT, we didn't release until November 2022. So you're talking, like, a decent a decent period of of two years there, a little bit longer. And I remember we were building you know, people have talked about we were going to call it maybe chat with g p d 3.5.

7. 1:12:25

   We had a a sort of precursor product called WebGPT that was built on 3.5 that we were literally paying contractors to use. Right? So this was all throughout 2022. We basically had the ChatGPT precursor that we had to pay people. They would not pay us. We had to pay them to use this thing. That's wild. The moment for me that really clicked was actually when we finished training GPT-four. So that was 08/08/2022, which actually is, like, three years ago now. It's actually pretty wild to realize that, almost to the day. And we did the initial post train of g p d four, and, honestly, I had a bunch of bugs in there. It was, like, broken for a bunch of different reasons.

8. 1:13:08

   But the model was, like, extremely creative. It was actually really interesting. It took us, like, about a year and a half to get to the point that the creative writing of our models matched that initial one that was buggy for various reasons. And I remember, you know, we had an instruction following dataset that was post trained on. So it's really we had collected examples of here's a human asking for a thing.

9. 1:13:28

   Here's what the model should do. So it's really not trained to do multi turn. So I asked her a question. It gave a response. But then I was like, well, what if we just ask another question? And it actually was able to leverage that full context. It actually was able to have a coherent chat. And the moment that we saw that, they were like, Okay, this thing is capable not just of being post trained to do this very specific thing, but it can generalize. It can kind of do the intelligent thing even though it wasn't directly trained for it. It was just so clear this was going to be the killer killer application.

10. 1:14:03

    And so then we were planning on launching g p d four in, you know, early twenty twenty three, and we had this chat infrastructure we've been working on, and it's so clear. Okay. Like, we're going to have to release the infrastructure and the model, and it's going to be this this amazing killer product. And so just almost as infrastructure ahead of getting the the real thing out, I, you know, I was excited for us to do ChatGPT, and that's why we did, you know, the and and see that come to life in November. So I think that for me, I I was really focused on GPT four as the model.

11. 1:14:36

    This is going to be the chat moment that's really gonna And kind of had missed the fact, because every time you see these new models, you just sort of see only flaws in the previous ones, and so missed the fact that GPT-three 0.5 was something that no one had really tried before in the broad sense of society, and that it was something that was already useful and that people would respond to.