You spoke about in 'Machines of Loving Grace' that we would have a country of geniuses in a data center, and the models over the last, I guess, two months have been sort of giving us a sense that we're getting there. But in your podcast with Dario, you sort of walked that back a bit by saying, you know, we may reach a country of geniuses in a data center, but the impact on society will take a long time. Can you explain what that means? Because we thought we'd do AGI here and we'd be finished and done with it.
Yeah, thank you. Thank you for having us, Raul. You know, I would say there is this duality between the fundamental capabilities of the technology and the time that it takes for those capabilities to diffuse into the world, right? We're getting models that are very good at software engineering, that are increasingly good at, you know, biomed innovation. We're not there yet, but we're on this very fast exponential. But when I look across the world and I look across the enterprises of the world, we have many enterprises as customers. Even if we freezed in place what the technology was capable of today, I think the economic impact could be much greater than it is because, you know, it just takes time. There are just frictions to adopt things through enterprises, and I think even more so in the developing world. And you know, when I visited Infosys, one of the things I talked about with Nandan was, you know, that we're both obviously very interested in making sure that this technology gets to everyone. And Nandan has devoted a big part of his life to many things in that direction and has built out India's digital public infrastructure. And so, you know, I think this question of diffusion is very tied to the question of how do we make sure that everyone benefits.
So when the foundation models came, Nan, you said that we should do use cases, and it sounds like Dario is saying the same thing, that even if we do the foundational model, we will still need to do use cases.
No, I think it's great what the foundation models are doing and the speed of evolution. But what we have learned is that diffusion of technology is a different ballgame. And how do you get technology to a billion people? And I think India, we have a little bit of experience with that. 1.4 billion people on Aadhaar, 500 million people on UPI, 20 billion transactions a month, the world's largest cash transfer system, the largest financial inclusion system, you name it, all that stuff. And we learned that diffusion is a technique. It's both an art and a science. It involves institutions, it involves policymaking, negotiations, dealing with incumbents, dealing with newcomers, strategies for execution. So the whole, you know, trust building. It's a whole host of things. And I think if all the investments in AI are going to deliver the value to society, not just to individuals, we'll have to look at diffusion pathways to take this to everyone. And I think India will lead on that. That's why I've always been saying that India should focus on becoming the use case capital of the world.
You had a more recent essay which you called 'The Adolescence of Technology', which is a little more somber, spoke a little bit about sort of dimming the enthusiasm of the first essay. And I want you to perhaps unpack that a little bit. You know, we all have spoken about the risks of the technology, but particularly in the Global South, where we think that AI is going to be hugely beneficial for us, we perhaps will have a different calculus on the risk-reward ratio. What do you think about that, and how would your essay address that?
I think that's an insightful comment, which is that, you know, I think in the Global South there's an opportunity for AI to accelerate catch-up growth, to solve a bunch of problems that are in the way of catch-up growth. And so, you know, I think AI is a technology that has big risks and big benefits, but in the Global South the benefits may be even bigger than they are anywhere else. But at the same time, that doesn't mean, of course, that the risks aren't real. You know, India is the world's largest democracy, we need to think about how democracies handle AI and how we confront other countries that are authoritarian. That's one of the risks I talk about. Another risk I talk about is making sure that AI systems are safe and predictable and autonomously behave in a way that's under our control, and everyone in the world has to worry about that. And then, you know, I think of particular relevance to India is the concerns I raised around economic displacement, right? Where I think the signature of this technology is going to be that it greatly grows the economic pie for the whole world, and again, huge upside because the opportunity for catch-up growth can be very, very fast. But, you know, things are going to change and there's some potential for disruption. And, you know, I think what I've been thinking about as I visited India these last few days and the last time I visited is, you know, how can we work together with the companies in India to kind of drive this growth for everyone, to make sure that the existing companies, large and small, continue to prosper along with us and the other makers of AI. And, you know, also on a philanthropic basis, how we make sure that the benefits reach everyone, both in an economic sense, in a health sense, in kind of other senses. So, you know, I think India is, you know, it kind of offers a particularly keen distillation of, you know, especially the benefits, but also the risks.
Nan, you've had experience with an adolescent technology with the whole DPI. In the early days of DPI, it was challenging. There were challenges with getting, you know, the big vision, which of course now we're looking at and in hindsight it looks like it was easy, but the early days was difficult. So as the father of a mature technology, would you want to give the father of an adolescent some advice? I know that makes me a grandfather.
Yeah. So, I think when you talk about diffusion, and you know, you have to think of AI, everybody agrees is like a general purpose technology, like people give the simile to fire or electricity or whatever. It's about starting from the user and how can we improve their lives. How can we take a billion people and help them to learn better? How can we take a billion people and give them better healthcare? How can we take a half a billion farmers and improve their earnings? You have to start from there and then figure out how to make it happen. And it's not just technology. Technology is just one piece of the puzzle. It's about institutions. It's about trust building. It's about negotiations. It's about guardrails, which, you know, Dario mentioned. It's about working with different stakeholders and making them go towards a common vision. So diffusion is difficult. It's not a simple task. So I think I feel that India will demonstrate this because we have the experience of diffusion at population scale in all the various areas. And obviously diffusion of AI, there are some differences that we need to think about, data, you know, guardrails and so on. But I think we can build a pathway or multiple pathways to that goal, and that will show the world. Because I believe right now in AI there's a race to the top and a race to the bottom, and the race to the bottom is faster than the race to the top. So I think all of us who have a stake in AI being useful to humanity have to accelerate and redouble our efforts to make the diffusion happen. Otherwise the consequences are going to be very, very difficult because there's going to be a backlash. If the only thing that AI does is, you know, create deepfakes or raise the price of your power bill or, you know, all the other things that are happening, people are going to respond. I mean, the resentment of the blue collar worker led to the train wreck of globalization. The resentment of the white collar worker is going to lead to the train wreck of AI. So I think we really have to work very hard to show profound, useful cases of AI.
Dario, you were in India in October and you're back again now. You spend a lot of time actually with the developer community. You clearly were impressed because you've come back so quickly. Could you tell us a little bit about, you know, what your experience is with how India is building and using AI? Perhaps just go through the stack. I mean, enterprise, small business, startups, then developers. What's different about the way India does it?
Yeah, so I would say there's just an excitement here and technical acumen, and we can even see it in the statistics of usage of Claude. You know, use of Claude for technical kind of programming and software engineering, mathematical tasks, the fraction is substantially higher here in India than it is in most other places in the world. And, you know, every time I go to speak at one of these, you know, kind of, you know, we'll host these builder or developer events in India, just there's a lot of excitement. You know, I can feel the brimming excitement of like, you know, what is something that we can build. In just the last four months, you know, the use of Claude and Claude Code has doubled in India. And, you know, I'm sure it's the same for the other developers. I don't say that to promote Claude and Claude Code, like it's more a statement about the kind of excitement in India. On the enterprise level, I mean, you know, the two of us just announced a partnership just yesterday. So, you know, we're really excited to work with all the large enterprises in India. They know much more about the Indian market, they know much more about distribution, they know how to serve enterprises within India, and, you know, they're much better at that than we are. And, you know, can we plug our technology into what they do and create something that kind of wins for both sides, right? We would like to be able to jointly win with the companies in India. And then finally, I think there's another element that's almost unique, which is that there's an excitement to build, but there's an excitement to build for public good and for philanthropic benefits. So, you know, Nandan kindly introduced me to the EkStep Foundation, of course builds digital infrastructure, and we've already started to work on a number of projects really to reach people in rural areas. We're trying to combine Claude with something called Open AgriNet, which helps farmers in rural regions to kind of find better information and better advice to be more effective and efficient, and we're looking to expand that a great deal. So I think that's something totally unique to India, and that, you know, through folks in the private sector we would get connected to these efforts and there would be mutual enthusiasm to promote these efforts.
And you of course have an office, you've declared a managing director, but actually more importantly, Sonnet 4.6, which dropped yesterday very inconveniently so I couldn't try it, apparently is doing very well on 10 Indic languages. So there seems to be a bit of a focus in your development as well on India. Can you tell me why that's important, why language, cultural context is important, and what role India can play in that?
Yeah, so, you know, language models have always been multilingual, but of course they're better at languages that they've been trained more on. And, you know, of course, as I learned when I first came here, India has a very long tail of regional languages. And, you know, we see this as something related to access, something related to making, we provide benefits for everyone, right? If you could only speak the most common languages, then there's a long tail we're not reaching. The farmers that we mentioned, you know, many of them speak one of the less common regional languages. And so we've put in place a push, you know, collaborating with folks in India to acquire more data for this long tail of Indic languages, and Sonnet 4.6 represents an improvement. We're not all the way there yet. We want these models to be as good even far out in the long tail of these languages as they are at speaking English. And we're making progress towards that. We're not there yet, but we want to keep going.
Now, Nan, after you built DPI, I mean, I say after like as if you stopped, you still continue to do it, but after you did the bulk of the work, you spent some time and effort actually taking it out to other countries. And I was wondering whether you've thought about that for AI. And, you know, as it's been mentioned so many times today, this is the first AI summit in the Global South, and so I think perhaps countries of the Global South, if there's a model as it were for doing this, would benefit from those ideas. So as you think about it, is it cost, is it skill, is it data, infrastructure, what is it that countries need to think about for this?
Oh sure, no, you know, finally it's about a lived experience. If you have done it, you can do it better next time. So what we did in the DPI part, the digital public infrastructure, is that after several years of that experience, we worked with global philanthropists, set up something called Co-Develop, and said let's take DPI global. And today we have some version of DPI running in about 40 countries around the world. We recently had a summit in Cape Town where we had 1,200 delegates from 109 countries. So it's become a global moment, and we feel that AI has to be, if AI has to really be impactful, we need something similar. So yesterday we just launched something called 100 Diffusion Pathways by 2030. We like to have targets.
