The Exchanges

Q How was it, was it like a fork in how OpenAI was thinking into what Anthropic eventually did?

A Yeah, you know, I would say, you know, my conviction and the conviction of my co-founders when we founded Anthropic were two of them. And I think one, we were starting to convince OpenAI of, the other, I was, you know, not, I didn't feel that we were convincing of. So the first was the, you know, the conviction in the scaling laws. And the idea that, you know, if you scale up models, you give them more data, more compute. Again, there are a few modifications like RL, but not really very much. It's pretty close to pure scaling. Um, you, you find that, you know, when you, when you do that, you, you find, you know, incredible increases in performance. And, you know, I was finding that in like, 2019 with, with GPT two, um, you know, when we just first saw the first glimmers of the scaling laws. And of course, there were a lot of folks, you know, inside and outside who didn't believe it at all. And we really made the case to leadership like this is, this is important. This is going to be a big deal. And I think they were kind of starting to believe us and ultimately went in that direction. And there was a second, um, You know, conviction I had, which is look, you know, if, if these models are going to be kind of general cognitive agents, like general cognitive tools that match the capability of like the human brain, we, we better get this right. The economic implications are going t…

AI assessment note: “my conviction and the conviction of my co-founders when we founded Anthropic were two”

Q Do you have to build Mail and Chad?

A Yeah, yeah. You know, I don't think we need to build all those things. Um, you know, it, you know, my, my thought would be, you know, we're gonna, it's gonna be a mixture of things we make ourselves and integrating into others, right? Like, you know, we can, we can integrate Claude into Google Docs. We can integrate Claude into, into, you know, Google Sheets. Like, you know, we have external connectors there. We can, you know, we're starting to do that with, with co-work. You know, same for Microsoft Office, same for other tools. So, you know, I think, I think we do whatever is, you know, easiest and fastest to do. You know, we, we integrate into the existing tools. Now it might turn out at some point that the existing, you know, tools aren't enough and we have kind of a different vision. You know, we want to, we might want to slice things differently, right? You know, maybe traditional email doesn't make sense or traditional spreadsheets don't make sense given what you can do in, in AI. So I, you know, I don't exclude that we could Chop up products in a different way, but we're happy to use the ecosystem that exists and work with anyone else, right? In many ways, we're a platform company. We allow many people to build on us, even though we sometimes also build things ourselves.

AI assessment note: “I don't think we need to build all those things.”

Q reason, but one of the big reasons, Is how big your stock market is and how much of an opportunity it is for this risk capital to exit eventually. Uh, it's a case for why India should really allow for our stock markets to flourish. The audience that I speak to is very much the wannabe entrepreneur in India. What can they do in AI? What is an actual opportunity?

A I think there's a lot of opportunities around building at kind of the application layer. We release a new model every two or three months, and so there's an opportunity every two or three months to build some new thing That wasn't possible before. That wouldn't have worked before because the models were weak. Um, people in fact say people were, you know, the majority of our revenue still comes from the API model. People say that, you know, API models aren't viable or that they'll be commoditized or whatever. I think what people are not seeing is there's this expanding sphere of what is possible with AI and the API allows, you know, this new startup to try making something that, you know, wasn't possible before. And, and this is why the API is such a flourishing business, and it's, it's constantly in motion, it's constantly in churn, and so, and so it doesn't, you know, it doesn't get commoditized. It's a very dynamic thing. And so, I think there's an opportunity for lots of, lots of individuals to just say, you know, what can I, what can I build? Well, you know, what, what, what can I build on top of these models with an API? Like, you know, what are the things that I can make that others cannot make? Um, uh, you know, what are some new ideas? And, you know, we've, we've, we've seen that, you know, we see both with the API itself and with Claude Code. Um, you know, I think, I t…

AI assessment note: “I think there's a lot of opportunities around building at kind of the application layer.”

Q are projecting humility in the conversation that you're having right now, or how the American companies are competing with the Chinese companies which are coming about. This projection of humility where it is for the larger good and not necessarily for how I view the world as companies with shareholders, with investment in revenues and seeking profit. Is this par for the course? Is this something you have to do?

A So, you know, I, I would, I would put it in the following way. You know, I, I would say the philosophy of Anthropic from the beginning has been that we, we try not to make too many promises and we try to keep the ones that we make. So, you know, we, we set ourselves up as, you know, A for-profit, but public benefit corporation with this LTPT governance, and we've maintained that. We've said that, you know, our goal is to, you know, stay on the frontier of the technology, but, you know, to work on, uh, uh, you know, to work on, uh, um, you know, the safety and security aspects of the technology. We've pioneered the science of interpretability. We've, uh, you know, pioneered the science of alignment. I don't know if you saw, but we recently released A constitution for Claude, the ability to align models in line with the constitution. And, you know, we've done a bunch of policy advocacy and warning about risks, right? Warning about risks is not in our commercial interest, right? Like, people can come up with conspiracy theories, but, you know, I will tell you, saying that the models we build could be dangerous, whatever people might say, that's not an effective marketing strategy, and that's not the reason that we do it. And, you know, speaking up on when we disagree, even with the U.S. administration on, uh, you know, on, on, on policy matters, right? We've, we've, we've spoken u…

AI assessment note: “Warning about risks is not in our commercial interest, right?”

Q easy. I think there's a learning curve. I heard someone said, well, it's like even prompt engineering is like playing a piano. You can't sit and start playing it. To my audience, I think it becomes increasingly relevant where to learn how to set context, how to prompt, how to use cloud code better for somebody like me who comes with zero knowledge. Can you recommend how one does that?

A Yeah, I mean, first of all, I would say, you know, we're trying, we're trying increasingly to kind of like make that learning curve easier. So like one of the things that caused us to release CloudCowork, um, which is basically CloudCode for non-coders is, you know, oh man, you know, like we were noticing a bunch of non-technical people who really wanted to use CloudCode and were struggling through the command line terminal, um, to do that, which, you know, it's like, like coders use the command line terminal all the time, but like non-coders, you know, it's just kind of like makes things unnecessarily complicated. Um, so, you know, Cowork was designed to be more of a, you know, the, you know, the, the kind of, You know, it was powered by, by the cloud code engine on the back. But, you know, the idea was to kind of make it, um, you know, more, um, more like user friendly and, and like easier to use. So, you know, we're, we're definitely trying to introduce interfaces that kind of make it, make it easier. But I, you know, I would also say, you know, that there's, um, You know, there, there's like, ah, you know, classes you can take that, you know, help you learn this thing. Now, I think it's a very empirical science. You mostly learn by doing, but, you know, it's like, Anthropic has its, like, you know, part of the company that we call the Ministry of Education, and, you know, I…

AI assessment note: “You mostly learn by doing, but, you know, it's like, Anthropic has its, like”

Q I'm, I'm trying to figure out has the definition of intelligence changed per se?

A Well, you know, what I would say is five years ago, you know, you could, you could Google, and there might be a website that, you know, would tell you a little bit about this, right? But, you know, you're just, you're just looking up some text that exists, exists on the web, right? You know, maybe it's not about how to get a monkey to juggle. Maybe, you know, maybe it's about how to get a seal to juggle. You know, it's not quite exactly the same thing, because maybe exactly the same thing doesn't exist. Um, but, you know, as, as, as we see when, when people use these models, uh, you know, you can ask and you can actually get an intelligent response. You can ask a specific question and have the model write, you know, one page about, or you can give it a, you know, you can give it a, you can give it a hypothetical, you know, what if I had, you know, the monkey juggle clubs instead of balls, or, you know, what if I did this thing? And, and that information doesn't exist anywhere where, you know, whereas the model is able to kind of, Think for itself and, and come up with an answer on its own. So it's, it's, it's something, um, you know, it's, it's something totally new. It's just, it's not just matching some of the text that exists on the internet.

AI assessment note: “the model is able to kind of, Think for itself and, and come up”