LIVE: Mukesh Ambani Speaks at India AI Impact Summit 2026 Delhi

I think that will be our focus, and AI will be immensely used in that area. And of course, we can talk about healthcare, education, deep research, medical sciences. I think all those areas will flourish on the back of this. So from our company standpoint, AI is becoming a really integral part of how we operate, serve our customers, build our networks, and manage our networks.

I agree. And maybe from my perspective, just a couple of things. I am the lead director on Pfizer, and so to just think about the opportunities for personalized medicine right now, or the fact that every student in India can have access to the world's information on their device. How cool it is. Maybe just a couple of things for me in terms of the implications. The one is, given the number of people who use AI in India will be greater than I think anywhere in the world over a few years, I think the leadership that India can play, not just in what these models mean, how do you think about data, how do you think about privacy and security and trust, but one area we're particularly passionate about, Sunil, is this area of content authenticity. We help produce the world's content, and so I think if we can make sure that, and the honorable Prime Minister talked about that, in fact, in one of my meetings with him, his eyes really lit up when he said, 'I want every piece of information that's produced to have the provenance and the watermark so that people can actually know what is real and what's fake.' But I just think it's just this incredible opportunity for India. We're as a company incredibly honored to participate with it, and I know I am really thrilled that the organizers allowed us this little opportunity to share how excited we are. But I will let you have the last word.

No, Shantanu, thank you very much. I just want to bring you in before we end today, and for our audience here. You know, the Prime Minister also spoke about making open standards, keeping AI open to the world for the benefit of democratizing, in a sense, AI as opposed to caging it and having it in the hands of a few. Talk about it. A lot of people have views on this from countries like India and many other, all the European leaders who are assembled here today. There seems to be a very clear message: engage with each other, make open standards, AI should be available to all for the benefit of humanity. Is there any danger that some of the leading AI developer companies may keep it more controlled, and we may have to fight that battle hard?

I think you're going to have the inevitable challenge between commercial enterprises who want to keep information proprietary, Sunil, and how they advance it with how do you do good for humanity. And so I think he was absolutely correct in reflecting that this is going to be an ongoing challenge. I can speak for Adobe. I mean, one of the things we've always done is everything that we do is open standards. I think the reason why PDF has adopted itself so massively is because it was an open standard. But I think it'll require companies and enterprises to behave differently and really recognize what is their sustainable advantage. And the sustainable advantage cannot, I think, over time be just the model. It has to be the use cases of what people are doing with that model. And so I think it'll require all of us also in companies to prevent, again as he said, from being disrupted by not just doing what we are doing. But I'm actually confident now. I do think India is better positioned than most other countries. The question is, I mean, you've again been a pioneer in bringing your services and connectivity around the world. I'm less confident about what will happen in those countries. I'm a lot more confident about what will happen in India.

So how can we showcase India's frugal power of innovation? Look at the Chandrayaan, the moon mission. India did it at $74 million. The US did it at $92 billion. And India had a perfect landing on the moon on the difficult side of the moon. How can we persuade US companies, large conglomerates, to use India not only for millions of people using their products but how to learn from frugal innovation that we do here?

You know, that's our secret sauce. I mean, in many ways, I see Raj and so many other good friends here from India who've done well in the US. I think it's because we use jugaad. And so, you know, I think to some degree, that is the secret sauce that exists in India, and that's how I think we've all been able to succeed on the global stage. But on that note, thank you very much.

Thank you so much, Mr. Sunil Mittal and Mr. Shantanu, for that enriching conversation. Ladies and gentlemen, now it's my honor to introduce our keynote speaker, Mr. Mukesh Dhirubhai Ambani, Chairman and Managing Director of Reliance Industries, a global powerhouse shaping the future of business and innovation. Under his visionary leadership, Reliance has transformed industries from energy and telecommunications to retail and digital services, impacting millions of lives. Ladies and gentlemen, please welcome Mr. Mukesh Dhirubhai Ambani.

Thank you so much, Mr. Mukesh Dhirubhai Ambani, for your strong belief in India's capabilities and also for being at the forefront of India's AI revolution. Ladies and gentlemen, let's have a big round of applause for Mr. Ambani. And now I would like to invite Sir Demis Hassabis. He's the founder and CEO of Google DeepMind, the co-founder of Google DeepMind, and well, he is also the Nobel laureate. A chess prodigy, neuroscientist, and game designer before he became one of the world's leading artificial intelligence researchers. Sir Demis Hassabis brings an almost uniquely cross-disciplinary mind to the challenge of building artificial general intelligence. DeepMind's AlphaFold solved a 50-year-old problem in biology, and he's well just getting started. Please welcome the co-founder and CEO of Google DeepMind, Sir Hassabis.

Thank you. It's a huge honor to be here today with so many of my esteemed colleagues from industry, academia, and government. And congratulations to Prime Minister Modi and the Indian government on convening such an impressive summit at this very pivotal moment for AI. It's fantastic to see how the summit has evolved over the years, with the first meeting convened by Prime Minister Sunak at Bletchley Park in the UK. It's become an incredibly important convening point for international dialogue and hopefully cooperation in the future over the future of AI. When we started DeepMind in 2010, almost nobody was working on AI in industry. It was just a dream. And it's been incredible to see how in the last 15 years where we've come from those humble beginnings to now where we are today, where the whole world is talking about AI. The reason I've spent my whole career working on AI is I always believed it would be one of the most important and beneficial technologies ever invented. And for me, my passion is to advance scientific discovery. And I always felt that AI would be the ultimate tool for accelerating scientific discovery and being a force multiplier for human ingenuity. From a very young age, I've been obsessed with the great questions of science, the nature of reality, the nature of consciousness, these deep mysteries that are in the universe. And I think AI can help us find answers to these questions that we've pondered over for thousands of years. We're already starting to see the beginnings of this with systems like AlphaFold that we built to solve the 50-year grand challenge of protein folding. And we hope that this will just be the first example of amazing advances in science and medicine that have been enabled by AI. And we and others are working on many other branches of science now to bring AI tools to help advance material science, fusion, physics, and mathematics. In fact, almost every branch of science and medicine can be impacted by AI. And now in 2026, we're at another threshold moment where AGI, artificial general intelligence, is on the horizon, maybe within the next five years. And we're seeing these general-purpose systems, foundational model systems, becoming increasingly capable almost week by week. So this is obviously an amazing opportunity that we should all grasp, economic and productivity as well as in the sciences. But it's also something that we have to approach with humility and understanding that we don't have all the answers yet as to how this technology is going to develop and be deployed into the world. I've been really impressed with what I've seen in India. I spent some time prior to the summit in Bangalore. We have a really big office there, Google and DeepMind, a great research office where we do some really critical research that we then bring to our products and our technologies around the world in areas like efficient models, continual learning, and multilingual capabilities. I also had time to give a talk at the Indian Institute of Science in Bangalore, and I was incredibly impressed by the students and the faculty there. Their enthusiasm and their energy for AI and their ideas for how to use AI to improve India's standing in the world and to also seize all the new economic opportunities and scientific opportunities that AI opens up is incredibly impressive to see the energy around the country. And I think India will indeed be a powerhouse for AI in and across the globe. We have many partnerships. Sundar, you heard Sundar announce many Google partnerships that we have with India. I'm especially proud of our deep partnership with Mr. Ambani and the Reliance Jio group to bring intelligence to everyone in India with our Gemini foundation models in partnership with Reliance. So we hope to build on that in the next few years. So if I was to try and quantify what's coming down the line with the advent of AGI, I think it's going to be one of the most momentous periods in human history, probably something more like the advent of fire or electricity. One way maybe we can quantify that is I think it's going to be something like 10 times the impact of the industrial revolution but happening at 10 times the speed, probably unfolding in a matter of a decade rather than a century. So really this enormous amount of change is going to come, and it's still to be written how we can make that beneficial for the whole world. And I think the main way we should try to do this is by taking a scientific approach, using the scientific method to understand what the capabilities of these systems are, to build good guardrails and monitoring systems to understand more deeply what these systems are capable of and how we can make sure that they serve the purposes that we want. And then of course simultaneously we also have to be bold to grasp these new opportunities to advance science and medicine and to improve human health and the human condition that society and the globe badly needs. So I think we've got to try and navigate this moment very carefully, very thoughtfully. And if we do so, I'm very optimistic that we'll usher in a great new era. And but of course this can't just be left to technologists. And that's why summits like this are really important to bring together all parts of society. The technologists that are building it, the scientists that are building it, governments and how to deploy it for the best use of their citizens. But also artists, social scientists, and philosophers. We need to bring all of these debates into the tent to understand how we should navigate this next period in human history. And I think summits like this, international summits like this, are critical to encourage this kind of international dialogue and cooperation. And if we get this right, these next steps right, I think we can usher in a new golden era of scientific discovery and improve the lives and health of everyone in the world. Thank you.

Thank you so much, sir, for your very profound and illuminating address. We really thank you. Sincere gratitude to your address, ladies and gentlemen. And now I would like to invite Mr. Vishal Sikka. He's the founder and CEO of VNI. As CEO of Infosys, Vishal Sikka led one of the most ambitious transformations in Indian IT history before leaving to build VNI, a company focused on human-centered artificial intelligence. He is a computer scientist by training, a philosopher by temperament. He is one of the most original thinkers at the intersection of AI and enterprise. Please welcome the founder and CEO of VNI, Mr. Vishal Sikka.

Thank you so much. Thank you so much for that wonderful introduction and what an amazing event. I want to share three points from a long time that I have spent in AI. My first point is that what we see today in the world of AI, people who know what they are doing with AI are astonishingly effective with AI. Recently, a friend of mine, he and I were students together at Stanford. He has a large service that he runs, an open public service. That service was built by 15 people, very world-class engineers, over nine months. Recently, he rebuilt that service entirely by himself in 14 days using one of the generative AI coding tools. So, if you are counting, that is about a more than 250 times improvement in productivity. Now, he's a genius, and not everyone gets a 250 times productivity gain, but you will see that people who understand how to use AI are astonishingly effective with it. And I had a similar experience recently with a customer of mine who is a distributor of home goods, and one of their main suppliers shut down their factories in one of their countries. And they did analysis using our product, all kinds of simulation scenarios, and over a few days they reached the decision that they need to exit that country entirely. I asked him, you know, such a monumental decision to get out of an entire country, how long would that have taken you before? And he said easily it would have taken a year, and it would have involved heavy-duty consultants and things like that. So we now have instant access to knowledge in any language, a condensation of things that we can present in any way. It is an incredible power, and yes, it is deeply disruptive to the ways that we have worked before, the way that we have done things in the past. But at the same time, and even more importantly, we can do unprecedented things with this, things that we could never do before. So this astonishing effectiveness, and Yeshua referred to this as a jagged frontier. It is not uniform. Not everyone sees this. So that's my second point. Being effective with AI requires not only a knowledge of AI itself but understanding its limitations and how to overcome those limitations. There is a huge gap between LLMs and the business users inside enterprises especially, and how to bring value to those users, and overcoming that gap is where a lot of value-creating opportunity is. That bridging that gap requires delivering correct systems, trusted, verifiable, reliable systems that deliver value to people. My own company works in this area. A layer that sits above the language models and delivers value to business users while ensuring correctness and things like that. When we overcome that gap, we can deliver massive value. I talked about it just now. We can transform every existing system. Legacy systems, enormous complexities inside enterprises can be removed. Industries can be transformed. We can give end users wings. We can amplify them to deliver things that were not possible to do before, or in the best case, it required professionals to do this. Doing that also requires not just overcoming the limitations of AI but also imagination to see what is not there, to see what is possible. India has all of this in great abundance. The honorable Prime Minister has called for a billion entrepreneurs, people who can overcome these and deliver value using AI. And I think this is exactly what the world needs and what India has the potential for. My third point is that we not only have to master today's AI but we have to leapfrog it. AI today has enormous limitations. I have worked in AI for the last 38 years. You know, one of our scriptures, it was written by the Shankaracharya, and it has a beautiful line. What it means is that when you are faced with a life or death situation, the knowledge of a book does not help you. Knowledge without wisdom does not save us. That wisdom comes from living, from experience.

AI today has plenty of limitations. Yeshua mentioned hallucinations. That's one of the main issues blocking the use of AI in enterprises. But beyond hallucinations, understanding the world, understanding physical activities, the physical movement, this is one of the next frontiers. Safety, safety of AI, and the honorable prime minister talked about this today, is an existential issue. Swarms of agents can be made to do completely reckless things and we don't yet have ways to understand or deal with this. We have to solve this issue. We have to deliver AI that is safe. We have done this with nuclear power for the last 80 plus years. We can and we must do this with AI.

Energy is another one of these issues. Where I live in California on Highway 101 just north of San Tomas, I drive by there every time I go to see my dad. There is a massive data center that is coming up. It's 720 megawatt. And this idea that I write a prompt and these gazillion GPUs blast into existence to produce a response and then I make a tiny change to that prompt and then they do that again. It just seems like a completely absurd idea, especially to someone who has been around AI for such a long time.

I have, thanks to the ministry of IT, honorable Ashwini Vaishnav ji, I have a colleague who has been accompanying me throughout this conference and he told me that yesterday he walked 32,000 steps and I asked him what did you eat and he said I ate two burgers. Two burgers. You know we normally eat 2,000 calories in a day, that's about a 100 watt light bulb, like less than one of these light bulbs and out of that our brain, our nervous system is maybe 15, 20 watt. That's like when your laptop is in sleep mode it takes more power than that. So there are many zeros still to be removed from these models and the models themselves have to be removed. So I think that there is a tremendous opportunity here.

India is a country of the human potential. We have plenty of times before delivered the ability to billion plus Indians. Mukesh talked about Jio and Sunil talked about Airtel and how now we have billion plus Indians who have data and connectivity. And when I was young, one of my earliest childhood memories is of worry in my parents' faces around food. They used to tell stories of how there was a shortage of food and then the green revolution happened and India is now one of the largest exporters of food in one generation. So I think that when you look at the time of intelligence, it is not only an opportunity to learn about this technology, to learn to master this technology, to understand its limitations, but to leapfrog that and to build the next generation of it. And as this summit so vividly demonstrates, we can be on our way to a human revolution powered by AI, by good AI, by purposeful AI where every one of us, a billion entrepreneurs, is not just making a living but is making a life, not some artificial life or some artificial general life but our own life and the life of others. And that would be so much fun to do. Thank you so much.

Thank you so much, Mr. Sika, 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 Infosys and Dario Amodei, founder of Anthropic. And before I invite our guests on this stage, let me say a few words about Mr. Nandan 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 Nilakani and Mr. Dario Amodei for this conversation which is being moderated by Mr. Rahul Matan, partner Trilegal. I invite all our three guests on the stage.

Please welcome our guests on the stage.

Dario. Welcome Dario. Great speech in the morning. You mentioned 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 Darkesh, 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 Asia here and we'd 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 diffuse into the world. Right, we're getting models that are very good at software engineering, that are increasingly good at 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 froze 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 when I visited Infosys, one of the things I talked about with Nandan was, you know, 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 built out India's digital public infrastructure. And so 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 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 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. 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?

You know I think that's an insightful comment which is that 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 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, growth can be very very fast. But you know things are going to change and there's some potential for disruption. And I think what I've been thinking about as I visited India these last few days and the last time I visited is 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 also on a philanthropic basis how we make sure that the benefits reach everyone both in an economic sense, in health sense, in kind of other senses. So you know I think India offers a particularly keen distillation of especially the benefits but also the risks.

Now Nandan, 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 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.

So I think when you talk about diffusion and 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 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, 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.

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 every time I go to speak at one of these, 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 what is something that we can build. In just the last four months, 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, it's more a statement about the kind of excitement in India. On the enterprise level, I mean, the two of us just announced a partnership just yesterday. So 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 they're much better at that than we are. And can we plug our technology into what they do and then create something that kind of wins for both sides. 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 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 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 you set 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 can India 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 it can only speak the most common languages then there's a long tail we're not reaching. The farmers that we mentioned, many of them speak one of the less common regional languages. So we put in place a push, you know, collaborating with folks in India to acquire more data for this long tail of Indic languages and set 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 Nandan, 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 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 cost, is it skill, is it data, infrastructure, what is it that countries need to think about for this?

No sure, 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 1200 delegates from 109 countries. So you know 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.

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. We're going to work around the world and create multiple diffusion pathways and then share them with 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 Kenyan, 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 Mahavisttar 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 3 weeks. So you can see the trajectory of time right from 9 months to 3 months to 3 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 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?

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.

Dario, 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 you know whatever few ideas you could have now.

Yeah I mean you know I think a lot of what was there was universal. But there are some things that I would accentuate that are possible when you have such a large population for running this kind of large possibility of experiments. Right, you have a very large population for kind of studying and improving human health. You know there's world-class medical research so I think I would double down especially on some of the sections about accelerating the cures for diseases. You know just had Demis Hassabis who has basically solved the protein folding problem with AI and kind of shown us all the way. And what we need are like 50 improvements like that. And the hope is working together between the AI developers and the folks who diffuse AI and do the actual medical research, can all of us working together between the AI companies and folks in India really accelerate progress. 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 could AI lead us to 10% growth rates which sound absurd but you know that's the thing I imagined in the positive scenario of Machines of Loving Grace. 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 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 could there be 20 or 25% growth which 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 being in India being one of the countries in the world that most embodies this, certainly 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% growth that Dario dreams of?

I don't know about 25 and all that, if I get to 10 I'll be happy. But I think a number of things have, obviously I think people before have talked about the need to create massive compute, we need to bring in the models, we need, 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, mixing English, Hindi, Tamil, whatever 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 very good example of P2P trading. So I think all these are examples of how AI will actually benefit people and then 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.

Thank you so much Mr. Nandan Nilakani and Mr. Dario Amodei and thank you Rahul Matan for moderating it. Well, it was quite an engaging conversation I must say and they are the pioneers and the thought leaders of artificial intelligence and they shared their profound perspectives. I thank our panelists. Ladies and gentlemen, our next speaker is Mr. Rishad Premji. He is the executive chairman of Wipro. The son of one of India's most beloved business leaders, Rishad Premji has carved out his own identity as a thoughtful steward of Wipro's transformation into an artificial intelligence native technology services company. He's also an unusually candid voice on the responsibilities that business leaders carry in times of technological disruption. Ladies and gentlemen, please welcome the executive chairman of Wipro, Mr. Rishad Premji.

A warm welcome once again. That's Mr. Rishad Premji.

You know thank you for those of you who are here for being here. Once in a generation a technology emerges that doesn't just change what we can do, it truly changes what we must do. AI for me is certainly that technology and how we as a country, how India responds in the next few years will shape not just our own economic trajectory but our ability to solve problems that matter to over a billion people.

For the past several years, the conversation around AI has focused just not on the possibility. What can it do? How powerful could it become? How quickly could it evolve? But we are now at an inflection point. The conversation has fundamentally shifted from possibility to practicality, from experimentation to adoption and from pilots to scale impact. This shift matters and it matters tremendously because technology creates value only when it is applied to solve real world problems responsibly and at scale. So what does this moment mean for India? It means India has the opportunity to become one of the world's most consequential environments for the application of AI. Not just as a builder of the technology but as a place where AI is tested against real world complexity and made to work at scale.

Our context as a country is demanding. Systems here must work across multiple languages, across urban and rural settings and across populations with very different levels of access, need, data quality and infrastructure. That raises the bar, but it also makes success meaningful.

We already see what this looks like in practice. In education, AI can support learning outcomes in local languages and help address teacher shortages and skill mismatches. In healthcare, it can enable earlier disease screening and strengthen rural care, especially where access is limited. And in public services, it can help build smarter, safer infrastructure and reduce leakages in welfare delivery.

Which brings me to India's strengths and why I believe India is well placed today to take advantage of all of this. Let me just highlight a few that matter most and have been highlighted by many. One of the most significant is our experience with DPI. UPI today processes over 20 billion transactions every month and has transformed how individuals and businesses participate in the digital economy. It has demonstrated that technology can scale rapidly when it is accessible, reliable and most importantly inclusive.

India also has one of the largest and fastest growing pools of AI talent in the world. We are truly the AI talent destination of the world. Approximately 650,000 professionals in India work in AI related roles today and this number will double by 2027. This talent brings not only technical capability but importantly practical experience in applying technology in complex real world environments.

Equally importantly many of the foundations to build out this talent are already in place. Government initiatives to train 10 million young people in AI along with industry partnerships with universities are expanding access to practical job ready training. Curriculum is evolving and people are giving opportunities as apprenticeships to get exposure to real world applications.

This capability is reinforced by a vibrant innovation ecosystem. India is home, as many of us know, to the world's third largest technology startup base, including more than 4,000 startups in the deep tech and AI space. Together, these companies are helping translate technological capability into practical real world applications.

We are already seeing what this looks like on the ground. In agriculture for example, farmers across Karnataka, Maharashtra, Telangana, AP and Punjab are using AI systems trained on satellite imagery and local crop data. These systems provide early pest alerts and in some regions have reduced crop losses by nearly 25%.

In small commerce, artisans in Gujarat, Tamil Nadu and UP are using AI related platforms connected to open networks. Products are automatically cataloged, descriptions translated across languages, prices optimized, and logistics coordinated, allowing small sellers to reach markets that were once out of reach. And we are also seeing deliberate investments in the future. National initiatives are expanding access to compute infrastructure and building capacity across the AI stack in our country.

At the same time and equally importantly, we as a country are taking a very pragmatic approach to governance, putting early guardrails in place, but balancing accountability with innovation so AI can scale safely and with confidence.

All of this lays a strong foundation for India to lead in the AI era. But there is one more factor that I believe positions us as a country uniquely. Our long engagement with global enterprises. Today the constraint as many have said is not access to technology. The real world begins when AI is introduced into large real world organizations. In those environments, technology has evolved over many years. Application landscapes are complex. Data is fragmented. Workflows are siloed. Processes vary across geography, business units, and regulatory regimes. Decision making is rarely uniform.

Making AI work in this environment means modernizing legacy architectures. It means curating and labeling data to create highly specialized context aware models. It means orchestrating across agents in ways that are reliable and secure. And it means earning confidence of security teams, risk leaders, regulators, and critically the people who are expected to use these systems every day. This is where a more practical pattern has emerged in enterprises.

Models designed for specific processes or decisions tend to deliver the most reliable results. When AI is closely aligned to a defined workflow, it becomes more predictable, easier to govern, and more effective over time. What enterprises need today is not a model that does everything, but models that do the right thing consistently inside how work actually happens. But technology alignment alone is not enough for these systems to deliver value in organizations. Organizations themselves will have to invest in change, taking people truly along, helping them adapt to new ways of working, redesigning roles and decision-making, and building confidence in how AI is used. That includes reskilling people, reskilling teams to work effectively with AI tools so that they understand the outputs and exercise judgment where it matters most.

When models are well aligned to workflows and people are supported through the transition, AI becomes not just deployable but it becomes sustainable at scale and that plays directly to India's strengths. We have decades of experience working inside complex enterprises helping them modernize systems, manage risk and take people along through this change. And that works in environments like these is not just deployable, it is resilient, responsible and truly scalable.

The same dynamics that determine success inside organizations will also shape how countries navigate this moment. As we look ahead, India's advantage in AI will not be defined only by the size of our models or the scale of our infrastructure. It'll be defined by the choices we make about where we apply AI, how we diffuse it, how responsibly is it deployed, and whether we can translate capability into real impact for governments, citizens and enterprises.

India's advantage will come from developing talent at scale. Not just people trained on AI, but people who can apply it with context, judgment, and an ability to adapt to change. That is why AI fluency must extend beyond engineers to teachers to nurses to administrators to supervisors to small business owners among everyone else. The dividing line will not be human versus machine. It will truly be between those who adapt and those who hesitate to adapt.

Technology shifts inevitably create uncertainty. But for countries that act decisively, they also create opportunity. India has embraced such shifts in the past and I believe we are really well positioned to do so again.

I want to close by sharing a personal story from the work of the Azim Premji Foundation which is also the majority shareholder of our company Wipro. You know India sees 2.7 million tuberculosis cases every year making it one of the country's most serious public health challenges. Early detection is essential, but confirming TB often requires patients to travel to distant public hospitals for sputum molecular tests. For many, the real barrier is not medical capability, but it is access. To address this, our foundation is running a pilot in a rural community in Tamil Nadu. Community health workers carry portable X-ray devices directly to people's homes. AI analyzes the X-rays instantly and identifies signs consistent with TB, enabling that early screening and faster referral without requiring patients to travel. If successful, this approach can help detect TB earlier and extend the reach of health care into communities that need it most. With a national doctor to population ratio of roughly 1 is to 800 and even deeper shortages in rural India, AI does not replace care. It multiplies scarce expertise infinitely.

The same last mile challenges exist across other countries in continents of Asia, Africa and Latin America. Home to more than four billion people. Solutions that work here in India at scale, low-cost, multilingual and resilient can travel far beyond our own borders.

If we can do that, India's contribution can be vast. Not just in building AI but in applying it to solve problems for enterprises, for our own country and for the world at large thoughtfully, inclusively and with impact at scale. Thank you for listening to me.

Thank you so much Mr. Premji for your visionary insights which I'm sure will undoubtedly guide the path forward. And we also thank Mr. Premji for highlighting how AI is being used by Wipro for human centric projects and for the welfare. That is what India is aiming at to have an impact at ground level to change the lives of human beings. Ladies and gentlemen, few individuals have done more to bring artificial general intelligence from the realm of science fiction into boardrooms, into parliaments and living rooms than our next speaker, Sam Altman, CEO OpenAI. Under his leadership, OpenAI launched ChatGPT and forced the world to reevaluate its relationship with artificial intelligence. So ladies and gentlemen, please welcome CEO of OpenAI, Mr. Sam Altman.

Thank you so much. It's really a treat to be here in India and it's incredible to see the country's leadership in advanced AI. I was last here a little over a year ago and it's striking how much progress has happened since then. We've gone from AI systems that struggled with high school level math to systems that can do research level mathematics now and derive novel results in theoretical physics. It's also striking how much progress India has made in its mission to put AI to work for more people in more parts of the country. And India's leadership in sovereign AI building on infrastructure, SLMs and much more has been great to watch.

More than 100 million people in India use ChatGPT every week. More than a third of them are students. India is also the fastest growing market now for Codex, our coding agent that works to help people develop software faster and better. India, the world's largest democracy, is well positioned to lead in AI, not just to build it, but to shape it and decide what our future's going to look like. It's important to move quickly.

On our current trajectory, we believe we may be only a couple of years away from early versions of true super intelligence. If we are right, by the end of 2028, more of the world's intellectual capacity could reside inside of data centers than outside of them. This is an extraordinary statement to make, and of course, we could be wrong, but I think it really bears serious consideration.

A super intelligence at some point on its development curve would be capable of doing a better job being the CEO of a major company than any executive, certainly me, or doing better research than our best scientists.

As we prepare for this possibility, we are guided by three core beliefs.

Number one, we believe that democratization of AI is the only fair and safe path forward. Democratization of AI is the best way to ensure that humanity flourishes. On the other hand, centralization of this technology in one company or country could lead to ruin. The desirable future a couple of decades from now has got to look like a world of liberty, democracy, widespread flourishing, and an increase in human agency.

Some people want effective totalitarianism in exchange for a cure for cancer. I don't think we should accept that trade-off, nor do I think we need to. AI should extend individual human will. We'll probably need super intelligence to help us figure out the new governance mechanisms to ensure that this happens fairly at scale and to avoid problems like extremely unbalanced compute access or something else.

Second, we believe that AI resilience is a core safety strategy. We don't mean that this is the only safety strategy. We will continue to need to build safe systems and solve difficult technical alignment challenges. But increasingly, we need to start broadening how we think about safety to include societal resilience. No AI lab, no AI system can deliver a good future on their own. For an obvious example, there'll be extremely capable bio models available open source that could help people create new pathogens. We need a society-wide approach about how we're going to defend against this.

And third, this future of AI is not going to unfold exactly like anyone predicts. And we believe that many people need to have a stake in shaping the outcome. The development of AI has already held many surprises, and I assume there are bigger ones to come. We understand that with technology this powerful, people want answers. But it's important to be humble about what we don't know, and always remember that sometimes our best guesses are wrong. Most of the important discoveries happen when technology and society meet, sometimes have some friction and co-evolve.

For example, we don't yet know how to think about some super intelligence being aligned with dictators and totalitarian countries. We don't know how to think about countries using AI to fight new kinds of war with each other. We don't know how to think about when and whether countries are going to have to think about new forms of social contracts. But we think it's important to have more understanding and society-wide debate before we're all surprised.

Special note and related to all three points, we continue to believe that iterative deployment is a key strategic insight and that society needs to contend with and use each successive new level of AI capability, have time to integrate it, understand it, and decide how to move forward. This has been working surprisingly well so far.

If we are right and systems continue to improve at this pace, it's going to change the economics of a lot of things. A really great thing about AI progress is that it looks like many things are going to get much cheaper and have much faster economic growth. We're already seeing what AI is doing for access to high-quality healthcare, education, and more. In the coming years, we expect to see robots make many products and physical goods cheaper as supply chains get automated. The limit to how far this cost reduction can go may only be government policy.

But the other side of this coin is that current jobs are going to get disrupted. As AI can do more and more of the things that drive our economy today, it'll be very hard to outwork a GPU in many ways. It'll be easy in some other ways. For example, we really seem hardwired to care about other people much more than we care about machines. We're somewhat less concerned about the long-term future. Technology always...

Disrupts jobs. We always find new and better things to do. The people of 500 years ago would have thought that our current jobs often look silly, like ways to entertain ourselves, create stress. And the people 500 years from now hopefully will look at us, hopefully look to us like impossibly rich people playing games, trying to find ways to pass their times. But we should all hope they feel much more fulfilled than we do today. I'm confident we will keep being driven to be useful to each other, to express our creativity, to gain status, to compete, and much more. But the specifics of what we do day-to-day will probably look very different. Each generation has built on the work of the generations before. And with new tools, the scaffolding gets a little taller. This collective external lattice, the set of tools that we have built up around ourselves is remarkable, and we are capable of doing things that our great great grandparents couldn't have dreamed possible. It is a moral imperative to make sure that our great great grandchildren can say the same. And technology and especially AI is how we're going to get there. For a democratic AI future, it is not enough to just give people tools and wealth. We also need to give them agency and power. The vision that AI companies lay out fundamentally reduced to either unilateral control or decentralized power. Sharing control means accepting that some things are going to go wrong in exchange for not having one thing go mega wrong. Cemented totalitarian control. This is a fundamental trade-off of democracy and it is one that we believe in very strongly as the way to give everyone collective agency over the future. Of course, this is not to suggest that we won't need any regulation or safeguards. We obviously do urgently like we have for other powerful technologies. In particular, we expect the world may need something like the IAEA for international coordination of AI and especially for it to have the ability to rapidly respond to changing circumstances. The next few years will test global society as this technology continues to improve at a rapid pace. We can choose to either empower people or concentrate power. Thank you very much.

Thank you Mr. Sam Altman for your very interesting and compelling remarks. Ladies and gentlemen, I would like to now welcome Mr. Brad Smith, vice chair and president Microsoft. Mr. Brad Smith has been Microsoft's conscience and its chief diplomat through some of the most consequential debates in technology policy from privacy and cyber security to AI regulation. His book, Tools and Weapons, remains one of the most lucid accounts of the responsibilities tech companies carry in the modern world. So, please welcome the vice chair and president of Microsoft, Mr. Brad Smith.

Good afternoon. It's always an important day when the world comes together under one roof as we have today. It gives us an opportunity together to ask important questions, even hard questions, and think about how we want to answer them. As we think about this summit, the first AI summit in the global south, it's only right that we start, I believe, by focusing on AI and what it means for the global south. In some ways, I think the best way to start thinking about AI is to look more broadly and think about the state of the world in which we live. We live in a tumultuous time and in a fragmented world, but I think in so many ways the deepest and most enduring divide has been the economic divide between the global north and south. And what I believe we need to recognize is that this economic divide is a result more than anything else of a technology divide. The technology divide created by unequal access to electricity. Electricity became one of humanity's most important general-purpose technologies. Meaning it spread across economies. It was applied in every industry. It boosted productivity. Where electricity went, economic development and prosperity followed. But as we all know, electricity did not spread everywhere at the same pace. It was literally 144 years ago that the first electrical power plant started operating in lower Manhattan. And yet we come together today and we still live in a world where 700 million people lack access to electricity. Now comes AI. AI perhaps more than any other technology this century will play a bigger role either in closing this economic divide or in exacerbating it and making it even wider. That is perhaps the single most important question for us I would suggest today as we think about the role of AI in the global south. How can we do better? Because we need to do better. What will it take? I think it's going to take a few things that will require that we all come together and work together. First, the obvious. We need to bring infrastructure to the global south. That means data centers and compute. It also means more connectivity. It means more electricity. That is going to take not only the world's best technology, it's going to require an enormous amount of investment. That's why we at Microsoft announced yesterday morning that we're on pace to spend $50 billion by the end of this decade to bring AI to the global south. And of all the countries in which we are investing, India, not surprisingly, is one of the largest. But we'll need to harness private capital, investments from tech companies, other sources of private capital, government funding. We'll need governments and others to generate demand for the use of AI in the global south because that is the only way to get the wheels of the market spinning and to do what we need to do together. That's the first thing we need to do together. There's a second thing we need to do. We've talked about it here already today and it is so clear when you study the history of technology. Infrastructure is not only hardware. It's not only wires and grids. It's skilling for people. Because the key to enabling a country and a population to use a general purpose technology at scale is to give people across the country access to the skills they need to put it to work. And that's why it's such good news that we seem so many governments supported by the United Nations and supported by private companies investing in more skilling. It's actually something that should speak to all of us. Certainly, as a tech company, we're committed. We've launched through Microsoft Elevate new initiatives, including one we're announcing this week, Microsoft Elevate for Educators to equip teachers with access to help their students learn how to use AI. But in the truth, it doesn't matter where you work, you have a role to play. Because the lesson of digital technology, I was an example of this was that it took employers to open their doors to computing. It takes employers today to open their doors to new AI tools. It will take employers to invest in the skilling of their employees. It's not just for the next generation. It's for every generation that this fully matters. Then there's a third challenge for the global south. We need to make AI work effectively for the global south and that requires some special initiatives at least two. First, we need to make AI as effective in every language as it is in English. And today it is not. Performance tests show that's the case. That's why one of the good things to come out of this week is new announcements to invest upstream in better data in other languages to provide better tools and measurement systems for AI that is built in other languages to build out data providence with a view to linguistic diversity. Diversity that we need to advance around the world and we need to use AI in the global south to solve the problems that matter to the global south oftentimes as we're doing here in India that's about improvements in agriculture or as a number of partners including Microsoft are doing this week launching a new initiative to address food security across Africa. These are just two of the myriad of opportunities we have to put AI to work in ways that will bring faster benefits to countries in most of the world. If we do those three things well, build infrastructure, invest in skilling, address real world problems, then I think it may create the foundation to think more and do more about the question I am willing to bet will be a bigger part of the conversation in the next few AI summits. What will AI mean for the future of work and jobs? Within these walls, I think we're mostly enthusiastic about the future of AI. But outside these walls, I think we need to recognize that increasingly around the world and especially in some countries, many parents are asking a common question. What will AI mean for my kids? What will AI mean for my family? What will AI mean for our future? I get it that some people are excited and they'll do well, but what about us? Us meaning most of the people who live on this planet. I think we have something to prove. I think we have something to prove not only to communities and countries and our customers, but to ourselves that we can not only embrace but pursue a brighter future for people. It's great to come to conferences like this and hear people talk about all of the advances in technology, but let's remember one other thing as well. Human capability is neither fixed nor finite. It's great to think about what it would mean to have computers in a data center that would be like a country of geniuses. But let's also recognize this. Compared to the people who lived in the bronze age, all of you, all of us are already geniuses. Whenever technology advances, it creates a new platform, a new foundation that enables people to stand taller and reach higher if, and only if we're committed to using that technology. Well, as AI makes it possible to cure more diseases, then it is right that we expect that it will improve human health. As we use AI already every day to find faster answers, it gives us the opportunity to ask more questions. The fundamental fuel of human capability has always been the same, curiosity. We need to look at AI as the next great generator for human curiosity and we need to take some inspiration because we all know the world could use a little more inspiration. I often think about the following. Before the invention of the washing machine, it took someone almost always a woman between six and eight hours to wash a load of laundry. But as the washing machine improved, that was compressed to 30 minutes. But do you know what happened? One thing happened more than anything else. Everyone wanted to wear cleaner clothes. Everyone expected to wear cleaner clothes. People did their laundry a lot more often. They had better clothes and they had more time and they put that time to work to do more with their lives. Ultimately that is the question for us and this too is not just a question for companies. It's not what AI will do to people, it's what people will use AI to do for themselves. And it's not just people who create products, it's every government, it's every company, it's every nonprofit, it's every employer. Because we all have the opportunity to work with our people to manage through the change that is coming to show people how with the right AI skills, they can create jobs and careers that will be brighter for their future. That will not be easy, but if that's not our goal, then we're missing the big picture. As we come away from this AI summit, it reflects so much progress. But I would say one thing as well. Each of these AI summits is a proud moment for a great nation. But we have an opportunity rather than have summits that are islands that are disconnected from the summits before or that follow. We need to build bridges. We need to build bridges between these summits. We need to define clear goals. We need to have common measurement systems. And every year we need to ask the same question. Did we make 12 months of progress in the year that just preceded our meeting? How can we build on that progress to do more and move faster in the year ahead? For those of us who come to these meetings in different countries every year, I hope we will take that away. Let's aim higher, not just for technology, but for what technology can do for people. Let's be clear in defining what we want to accomplish. Let's put in place the ability for us to measure our progress and all hold ourselves accountable as a global community. If we can do these things, then we can use these summits and we can use this next generation of technology to build a better world. I know that's what we within these walls want ourselves to do. But even more than that, I know that the people outside these walls are hoping and expecting us to do just that. Thank you very much.

Thank you so much, Mr. Brad Smith, for that very energizing address, ladies and gentlemen. And I think he really deserves an energetic applause from you all. His address has actually given a very constructive direction to the discourse on artificial intelligence. And well, now we are moving to the next conversation for which our guest is the person who's often called the godfather of deep learning. Our guest is Mr. Yann LeCun, executive chairman, Advanced Machine Intelligence Labs and his foundational work on convolutional neural networks underpins virtually every image recognition system in use today. Now at the frontier of next generation AI architectures, he's one of the field's most provocative and independent voices. Please welcome our next speaker, Mr. Yann LeCun. And this conversation will be moderated by Miss Maria Shaquille, managing editor India Today. Please welcome our guest and our moderator, Mr. Yann LeCun.

Welcome. Good afternoon everyone. So let's begin with the big idea here, Professor LeCun. Are we on a path to creating the smartest mind that humanity has ever known? And will that happen in our lifetime?

Maybe in the lifetime of some people here. Possibly not in mine. We'll see. It will take a while. But I think the more interesting thing that we're going to build is an amplifier for human intelligence. So maybe not an entity that surpasses human intelligence in all domains although that will happen at some point but at least something that will amplify human intelligence in ways that will accelerate progress.

So then will we end up defining and redefining genius? What will a genius be?

Well, you know, I think several thousand years ago or even a few centuries ago, what people identified as genius is very different from what we currently identify as genius. And I think there will be more evolution of that concept of genius. You know, in the past perhaps, you know, genius was, you know, some act of creation or invention, but maybe not at the theoretical level like we tend to think of it today. It was, you know, more practical. Certainly in the very ancient past, people who figured out how to cultivate crops or domesticate animals probably were seen as genius.

So you know we have often seen and this is a thought that you have all pretty openly shared that AI is powerful but not intelligent. When we make that distinction and there are conversations around LLM where do you see intelligence and AI driven power?

Yeah, I think there's a lot of confusion really because we tend to anthropomorphize systems that can reproduce certain human functions. So what's I mean LLMs are incredibly useful. There's no question about that. And they do amplify human intelligence like computer technology going back to the 1940s. But LLMs to some extent except for a few domains are mostly information retrieval systems. They can compress a lot of factual knowledge that has been previously produced by humans and can give easy access to it. In a way it's kind of a natural evolution of the printing press, the libraries, the internet and search engines, right? It's just a more efficient way to access information. And there are a few domains where the intelligent capabilities of those systems actually is more than that. It's more than just retrieval. So for generating code maybe doing some type of mathematics that we're getting the impression that it's beyond this but it's still to a large extent domains where reasoning has to do with manipulating symbols. The problem is that, you know, why do we have systems that can pass the bar exam and win mathematics olympiads, but we don't have domestic robots? We don't even have self-driving cars, and we certainly do not have self-driving cars that can teach themselves to drive in 20 hours of practice like any 17 year old. So, we're missing something big still.

So, what are we teaching a 17 year old then?

Well, so the question is how does a baby learn or animal, right? Animals have a much better understanding of the physical world than any AI systems that we have today which is why we don't have smart robots. And so we learn about the world, how the world works mostly by observation when we are babies a few months old and then we learn by interaction and we learn mental models of the world that allows us to apprehend any new situation even if we haven't been exposed to it beforehand, we can still handle it. So a big buzz word in AI today is world models. And this is really this idea that we develop mental models of the world that allow us to think ahead to apprehend new situations, plan sequence of actions, reason and predict the consequences of our actions which is absolutely critical and AI doesn't do this really.

There is the sense professor that perhaps AI will unlock an era of radical abundance. Will this abundance benefit us?

Well, so if you talk to economists they tell you if we can measure the improvement that AI will bring to productivity which is amount of wealth produced per hour worked it's going to add up to maybe 6% per year. Okay, this is from economists that actually have studied the effect of technological revolutions on the labor market and the economy. People like Philip Aghion or Erik Brynjolfsson. And so that seems small it's actually quite big and it's certainly going to accelerate scientific progress, progress in medicine. I do not believe there's going to be like a singular identifiable point where the economy is going to take off and there's going to be abundance. And there's also the question of the policies surrounding this, you know, are those benefits going to be shared across humanity or different categories of people in various countries. That's a political question has nothing to do with technology.

So if economists see this as boom will then openness survive?

It's not going to be an event. It's going to be progressive. There is this false idea that somehow at some point we're going to discover the secret of human level intelligence. I don't like the phrase AGI because human intelligence is specialized. So I don't like the artificial general intelligence phrase but it's not going to be an event. We're not going to discover one secret. We're going to make continuous progress and we're not going to be able to measure that progress by just having a series of tests that are going to test whether a machine is more intelligent than humans because machines are already more intelligent than humans on a large number, a growing number of narrow tasks. And so it's not like a uniform scalar measurement of quality. It's a collection of quality. But what's more important is that intelligence is not just a collection of skills. It's an ability to learn new skills extremely quickly and even to accomplish new tasks without being trained to do it the first time we apprehend it. That's really what intelligence should be measured at. So we're not going to be able to just design a test that is going to figure out are machines more intelligent than humans.

So if it's about upskilling and ensuring that you're relevant then only perhaps you're intelligent. Will that then mean that the countries that adopt AI and the pace at which India and the scale at which India has adopted AI the challenge would be to create talent which is upskilled and reskilled and have the required skills for this.

Absolutely. So the relationship that we're going to have with intelligent AI systems is going to be similar to the relationship that a leader in business politics or academia or some other domain has with their staff. Okay. AI is going to be our staff. Every one of us is going to be a manager of a staff of intelligent machines. They'll do our bidding. They might be smarter than us but certainly if you are an academic or a politician you work with staff that are smarter than you. In fact that's the whole point. You need to attract people who are smarter than you because that's what makes you more productive. For an academic students who are smarter than their professor and teach, it's not the professor that teaches graduate students it's the other way around actually. And certainly we have a lot of examples of politicians who are surrounded by people who are smarter than them.