Fireside Conversation: 01

Thank you so much, Mr. Sikha, for your profound and very interesting remarks. And of course, your work at VNI also exemplifies the transformative potential of artificial intelligence. And with this movement on the stage, you can make out that now we are heading into a fireside conversation. And well, this would be a remarkable conversation we’re going to have with Mr. Nandan Nilakani, co -founder and chairman in FOSIS and Dario Amode, founder of Anthropic. And before I invite our guests on the stage, let me say a few words about Mr. Nandan Nilakani, who is the architect of Aadhaar, the world’s largest biometric identity system and the intellectual godfather of India’s digital public. Infrastructure movement. Nandan Nilakani has spent decades proving that technology built in the public interest can transform entire societies.

And Aadhaar is a big example before the world. His thinking on artificial intelligence and open digital ecosystems is essential reading for anyone serious about this field. So, ladies and gentlemen, I would now invite Mr. Nandan Nilekani and Mr. Dario Amode for this conversation, which is being moderated by Mr. Rahul Mathan, partner Tri Legal. I invite all our three guests on the stage. Please welcome our guests on the stage. Thank you.

Nandan, Dario, welcome. Dario, great speech in the morning. You mentioned the… that we are in the end of the, or towards the end of the exponential. This is something that 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 Dwarkesh, you sort of walk 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 and we would be finished and done with it.

Yeah, thank you. Thank you for having us, Rahul. 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, you know, to diffuse into the world, right? We’re getting models that are very good at software engineering, that are increasingly good at, you know, biomedical innovation. We’re not there yet, but we’re on this very fast exponential. But when I look across the world and, you know, 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, you know, I think even more so in the developing world. And, you know, when I, you know, visited Infosys, one of the things I talked about with Nandan was, you know, that we’re both obviously very interested in, you know, making sure that this technology gets to everyone. And Nandan has, you know, has devoted a big part of his life to, you know, many things, you know, many things in that direction and has, you know, 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, Nandan, you said that we should do use cases. And it sounds like Dario is saying the same thing, that even if we do the foundation model, we will still need to do use cases.

No, I think it’s great what the foundations 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 billion 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, so 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.

Talia, you had a more recent essay, which you call 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. Perhaps we’ll have a different calculus on the risk -reward ratio. What do you think about that, and how would your essay address that?

You know, 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, you know, big risks and big benefits. But in the global south, the benefits… The benefits may be even bigger than… than they are anywhere else. But at the same time, that doesn’t mean, of course, that the risks aren’t real. You know, we kind of – India is the world’s largest democracy. You know, we need to think about how democracies handle AI and, you know, how we confront other countries that are authoritarian.

You know, 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, you know, autonomously behave in a way that’s under our control. And, you know, everyone in the world has to worry about that. That affects everyone in the world. And then, you know, I think of particular relevance to India is, you know, the concerns I raised around economic displacement, right, where, you know, I think the signature of this technology is going to be that it greatly grows the economic pie for the whole world. And, again, you know, huge upside because the opportunity for catch -up growth, like, you know, growth can be very, very fast.

but, you know, there’s, there, 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, in, 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, of, of, of, of AI. And, and, you know, also on a philanthropic basis, how we, 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, I think, I think India, you know, it kind of offers a particularly keen distillation of, of, you know, especially the benefits, but, but also the risks.

Nandan, you’ve had experience with an adolescent technology with you, 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, of a mature technology, would you want to give the father of a, an adolescent some advice?

I don’t know, that makes me a grandfather. So I think when you talk about diffusion, and you have to think of AI, everybody agrees it’s 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 Dario mentioned. It’s about working with different stakeholders and making them go towards a common vision. So it’s diffusion. 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, 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 create deep fakes or raise the price of your power bill, or 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.

Taddeo, 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 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 a 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. I don’t say that to promote Claude and Claude code. Like, it’s more a statement about the kind of excitement. I mean, 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, you know, all the large enterprises in India. They know much more about the Indian market. They know much more about, you know, 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, you know, create something that kind of, you know, that kind of wins for both sides, right?

We would like to be able to, you know, 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 XTAP 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 Quad with something called Open Agri. Which, you know, helps farmers in rural regions to kind of find better information and, you know, better advice to be more effective and efficient. And we’re looking to expand that a great deal.

So I think that’s something, you know, 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, you know, 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, you know, India can play, what role it can play in that?

Yeah. So, you know, language models have always… They’ve always been multilingual. But, of course, they’re better at languages than they’re… That, you know, that they’ve been… trained moron. And, you know, of course, you know, as I learned when I first came here, India has, you know, a very long tail of regional languages. And, you know, we see this as something related to access, something related to making sure we provide benefits for everyone, right? If you can only speak the most common languages, then there’s a long tail we’re not reaching, right? 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, you know, we’re not all the way there yet. We want these models to, you know, to be, you know, to be, you know, as good, even far out in the long tail of these languages as they are at, you know, speaking English. And we’re making progress towards that. We’re not there yet, but we want to keep going.

And then after you built DPI. I mean, I say after, like, as if you’ve stopped, you still continue to do it. But after you did the bulk of the work, you spend 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 we, you know, it’s been mentioned so many times today that 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 costs? Is it skill? Is it data?

Infrastructure? What is it that, you know, countries need to think about for

this? No, sure. You know, finally, it’s about a lived experience. If you’ve 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 Crop. And we did a lot of work on that. And we did a lot of work on that. And we did a lot of work on that. And we did a lot of work on that. And we did a lot of work on that. And we did a lot 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

Can you explain that?

Yeah, so the idea is that a diffusion pathway is basically a way to reach a particular goal, which you got from learning, from doing things, and then packaging it. And it’s not just technical packaging. It’s about guardrails. It’s about how do you get institutions on board? How do you make data available? There’s a whole host of things. But think of it as a toolbox or a playbook for doing things. And then this is a global initiative. So we’re going to work around the world and create multiple diffusion pathways and then share them. We’re going to switch each other so that we can accelerate this thing. And, you know, Anthropic is part of that. We have Google as part of that.

Gates Foundation is there. UNDP is there. The Kenyans. It’s a global coalition. Because what we learned from the agriculture experience, you know, we implemented, we worked with Maharashtra on their agri -stack, which is called Mahavistar. And that took us nine months to figure out how to make it work safely at scale. Using the same learning, it was done in Ethiopia. Which took three months because we had the learning of Maharashtra. And then using the same learning, the PM was very keen to see it in animal husbandry. So we worked with Amul. And we did that in three weeks. So you can see the trajectory of time, right? From nine months to three months to three weeks.

So what that shows is that if we can do this lived experience and keep improving and package that and take it to the world, we’ll move the implementation of AI to the next level. to the real world. And that I think is strategically important for the world of AI.

So 100 by 30 is the new…

Yeah, 100 diffusion pathways by 2030. And we welcome everyone to join this moment.

You have many such catchphrases, but the one that really stood out to me some time ago was India needs AI and AI needs India. We’ve spoken a bit about the India needs AI, but why does AI need India?

Yeah, because this is where we’re going to show it working. You know, I mean, I think because of the history of India’s digital journey and thanks to the leadership of Prime Minister Modi, who is the biggest champion of all the work that’s going on, we have a political leadership that’s committed. We have technologists. We have enough people with the right value system to make this happen. And we have done this before. And therefore… India will be where you’ll see most of the deployment of AI in a tangible way, where farmers are able to make more money, where children learn better, where healthcare is better, where people talk in their own language, so you have universal access.

So this is where you’re going to show this. And the world needs this to be shown and the AI companies need this to be shown because they have to show real stuff where this is working at scale for people. So I think, yeah, it’s very important.

Taryo, if I can ask you, if you were to rewrite Machines of Loving Grace, which is a beautiful 20 ,000 word or something essay for India, if you were to think about what is that utopic vision of what AI could be for India, what would it be? I mean, obviously not 20 ,000 words, but whatever few ideas you could have now.

Yeah, I mean, you know, I think a lot of what was there was universal, but there… You know, there are some things that I would accentuate that are possible when you have such a large population for running, you know, running this kind of large possibility of experiments, right? You have here a very large population for kind of studying and improving human health. You know, there’s, you know, world -class medical research. So I think I would double down especially on some of the sections about, you know, accelerating the cures for diseases. You know, we just had Demis Hassabis who, you know, has, you know, basically solved the protein folding problem with AI and kind of shown us all the way.

And, you know, what we need are like, you know, 50 improvements like that. And, you know, the hope is, you know, working together between the AI developers and, you know, the folks who diffuse AI and do the actual medical research. You know, can all of us, you know, working together between the AI companies. And folks in India really. really accelerate progress. You know, I would also say accelerating the rate of economic development. You know, there is so much technical potential and technical adeptness in India. And it actually almost seems like a perfect case study for the idea that AI could really accelerate economic growth because it seems like the base ingredients are kind of all there and AI could help to tie them together.

So, you know, in the developed world, I’ve wondered, you know, what could AI lead us to, you know, 10 % growth rates, which sounds absurd, but, you know, the thing I imagined in the positive scenario of machines of love and grief. But I think here in India, there’s a lot of catch -up growth to be done. There’s an enormous amount of technical potential and ability. And, you know, So, you know, as I’m seeing, there’s this eagerness to adopt AI. So India is one of the few places in the world where I wonder, you know, could there be 20 or 25 percent growth, which is, you know, sounds absurd, is unknown anywhere in the world. But as I think about this, it kind of stacks all the factors for a very bullish picture of how that growth could happen.

So, you know, I think I could imagine India being one of the, you know, countries in the world that most embodies this, certainly the big, the large country that most embodies this.

And Nandan, with all of these things, there needs to be some unlock. So if you were to advise governments of the world, governments of India, governments of the global south, what should they do to unlock this 20, 25 percent growth that Dario dreams of?

I don’t know about 25 and all that. If I get 10, I’ll be happy. But I think there are a number of things. Obviously, I think people before have talked about the need to create a massive compute. We need to bring in the models. I think the focus has to be on inclusion. I think this AI has to carry everybody. Everybody must feel it. Everybody must benefit from it. And that’s why I think the language is very important. We want people to be able to speak to the computer in their language, in their dialect, like mixing English, Hindi, Tamil, whatever. That needs to be done. I think that’s a big thing. And then I think making agents work for people.

I think if we can make agents work for people, then it means more inclusion because they can get complex things done because you’re hiding all the sophistication behind the agent. So I think there are a lot of things we can do, which you’ll see now in the coming years. We already have three or four examples in agriculture, in healthcare, in language, in education. In electricity, we have a lot of examples. a very good example of P2P trading. So I think all these are examples of how AI will actually benefit people. And then it is, I think as to Dario’s point, India is a country which is very positive about technology in general and AI in particular.

And we need to take advantage of that and not let them down by giving them truly transformative applications using AI, which you will see in the next two to three years.

Nandan, Dario, thank you so much. What a lovely conversation. Thank you. That was great.