#336 Professor Mausam: Why India Is Losing the AI Race and What It Will Take to Catch Up

What if the country that produces the world's top AI talent finally figured out how to keep it? In this episode of Eye on AI, Craig Smith sits down with Professor Mausam, one of India's leading AI researchers, AAAI Fellow, and founding head of the Yardi School of Artificial Intelligence at IIT Delhi, to get an honest and unflinching diagnosis of why India has fallen so far behind the US and China in artificial intelligence and what it will actually take to close that gap. Mausam breaks down the structural story behind India's deficit. A pipeline of world-class students that gets exported abroad the moment it graduates. A professor shortage so severe that IIT Delhi's entire School of AI has hired only five new faculty members in five years. A government AI mission with the right instincts but not enough speed or boldness. And a brain drain made worse by the very thing India is proud of, its English fluency, which makes its talent the easiest in the world to absorb and the hardest to bring back. Mausam walks through the full picture. How China built its research dominance not through students but through aggressively repatriating senior researchers with real salaries, real lab resources, and real authority to build research cultures from scratch. Why the AlexNet moment in 2012 was actually an equalizer that gave China's fledgling ecosystem a surprise advantage over more established Western research groups. How India's JEE coaching culture and IIT bottleneck are symptoms of a scarcity of quality institutions rather than a broken exam. What the government's AI mission is getting right on compute, data, and sectoral focus, and where the critical gaps remain. And why Mausam believes that bringing one hundred top professors back to India would do more for the country's AI future than any single government program or funding initiative. We also get into the harder questions. Whether AI degrees belong at the undergraduate level or should sit on top of a computer science foundation. Why Mausam no longer holds an optimistic view on AI's impact on software jobs and why he thinks Geoff Hinton's point about plumbers has merit. And what it would actually take for a democracy of 1.4 billion people to stop training the world's AI leaders and start keeping them. Subscribe for more conversations with the researchers, builders, and policymakers shaping the future of artificial intelligence. Stay Updated: Craig Smith on X: https://x.com/craigsshttps://x.com/craigss Eye on A. I. on X: https://x.com/EyeOn_AI (00:00) Introduction: India's AI Gap and Professor Mausam's Background (02:30) Building the Yardi School of AI at IIT Delhi (07:44) How Far China Has Pulled Ahead in AI Research (12:55) Why India Could Not Follow China's Playbook (29:18) The JEE System, Coaching Culture, and the IIT Bottleneck (30:37) AI Degrees, Job Market Realities, and the Future of Work (44:18) The Real Problem Is Professors, Not Students (48:07) Big Tech Labs in India: Helpful but Not at Scale (51:46) The Government AI Mission: Progress and Gaps (55:20) The Compute and Data Infrastructure Problem (59:54) Can India Close the Gap Before It Is Too Late

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Craig S. Smith?

  This is the second episode in my series on India. As I said earlier, India and China were roughly equivalent a couple of decades ago. Particularly in their research ecosystems, China took off and India did not. As a result, India, one of the largest economies in the world, with one of the largest populations in the world, and with a chain of terrific technical institutes, the India Institutes of Technology, has fallen far behind the US and China in its AI development. I wanted to know why, so I went to India and spoke to some of the senior researchers

• 0:43Craig S. Smith?

  at the Indian Institute of Technologies. Today, I speak with Professor Mausam. His mother blessed him with a single name, so Professor Mausam, at IIT Delhi. Professor Mousam is one of India's leading AI researchers and is particularly articulate in explaining why India has fallen behind and what it has to do to catch up. Together, we delve into the contrast between India and China's approaches to AI, the challenges facing Indian academia, the various government initiatives, and what's needed to foster true innovation and talent retention in India.

• 1:26Craig S. Smith?

  India has the opportunity to become an AI leader. The question is, is it starting too late? With that, here's a word about our sponsors, and then we'll speak to Professor Mousam.

• 1:41Craig S. Smith?

  Yeah, can you give us that background? And then we'll start talking about your research and about AI in India.

• 1:47Speaker 01

  Okay. I started out, I mean, as an undergrad student at IIT Delhi. So this is also my alma mater for my undergraduate institution. After completing the course, I wanted to do a PhD. And so I applied, you know, to the top places in the US, and Uda was kind enough to take me in. Interestingly, I didn't apply to be an AI student at the time. I applied to be a theory student. But as I did my first AI course in the first quarter at U Dub. And I just loved it. I loved it beyond belief and I was really enamored by it at the time, so.

• 2:24Craig S. Smith?

  This is what year?

• 2:26Speaker 01

  This is two thousand one.

• 2:27Craig S. Smith?

  Oh, so very early in in the AI.

• 2:29Speaker 01

  Yes, so I mean, we'll talk about that, but AI is a seventy year old, yeah, on paper phenomenon. There was AI before that, but AI as a term got coined, believe it or not, just a few days back, seventy years ago. So thirty first August, I think, in fifty five, right, at the Dartmouth AI workshops. And maybe if it was more recently, I was going into as a grad student, maybe I wouldn't have taken AI. But at the time, it enamored me because there was a lot of things to be to do. The philosophy was very exciting to me. I mean, we can talk more about that. But so after finishing that, I was looking, so I wanted to come back to India. But I was also looking for one stint in the US before I come back to India.

• 3:14Speaker 01

  And it's a pretty stroke of luck, I would say, that U Dub, my own PhD institution, decided to offer me a research faculty position in the same institution right as I finished my PhD. So it was almost like one day I was a PhD student and next day I was a faculty member in the same institution. Again, something I wouldn't recommend to others because it takes a lot of time for you to start feeling like a faculty member. Because nobody thinks you're a faculty member, right? Everybody knows you as a student. But anyway, so I was there for another six years after finishing my PhD as a research faculty. I actually, that is the time my profile started becoming stronger because I had the opportunity to really work with really amazing grad students.

• 3:58Speaker 01

  And at U Dub, and these are like, they pushed me in different directions and I also had my advisor and another senior professor as people high school advising these students with. They were my mentors in some ways and then I was learning how to mentor through this kind of a relationship. It was time for me to come back to India in two thousand thirteen. I had been a faculty member for six years. I had graduated as a student or two and many other students were about to graduate with their PhDs under my supervision or joint supervision. And so that is the time I sort of went broadly in the country. But my family is from Delhi, so it was my most natural for me to come to I T Delhi. And so I've been at I T Delhi from two thousand thirteen.

• 4:40Craig S. Smith?

  Yeah.

• 4:41Speaker 01

  And just to tell you my sort of path from then on, that was also the time when A I was coming into some kind of, you know, broad visibility, right? For want of a better word. There was a lot of energy about deep learning. Before two thousand thirteen up to two thousand twelve mostly, most of A I was probabilistic, Bayesian, right? That kind of A I. And around two thousand eleven, two thousand twelve, two thousand thirteen, all these initial results started coming about word to vec, about how you can do some, the Alex Net had just come out, you know, all of those things were happening. So when I moved back to India, suddenly not only did I have to establish a research career in a new place and India

• 5:21Speaker 01

  and sort of the standard practices I would be able to follow in Seattle may not necessarily apply here. But also the field was changing on me, right? So we had to deal with all of that change and disruption. But then over time, things stabilized and we picked up new stuff and almost every researcher had to undergo some kind of a transition. That really gave us a lot of value because now suddenly A I became a great word and the people wanted to do PhD or do research in A I. We started attracting strong students. So ever since the profile of A I researchers in India has sort of grown up, you know, just by market forces. And at some point, pretty much every university, a top university decided that, look,

• 6:03Speaker 01

  A I can develop in, within the computer science and electrical engineering departments, but we need to establish sort of separate units so that A I can really flourish. And so various institutes, including I T Khadakpur, I T Madras, I T Bombay and also I T Delhi, started units, academic units within A I. So I T Delhi started. School of Artificial Intelligence, later became Yardi School of AI because Yardi became a primary donor. And I was asked to lead the first, you know, as the founding head.

• 6:34Craig S. Smith?

  That is. Was that the first in India or the first in Delhi?

• 6:38Speaker 01

  I would say that this is around the time that everybody else who is our peer was doing similar things. So I don't know whether it was a few months earlier, a few months later, but I wouldn't take credit for being the first.

• 6:51Craig S. Smith?

  And what year was this?

• 6:52Speaker 01

  This is twenty twenty.

• 6:54Craig S. Smith?

  I see.

• 6:54Speaker 01

  I would say that IIT Madras was a little bit of a leader there because they had established a center of excellence, I believe, in a Dabba Bosh Center of Excellence in Data Science and AI. So they, I think, did a year and a half earlier than most of us. Everybody else had followed around the same time. And there was also IIT Hyderabad, I think. They also did something first. And that's about it. So that's been my journey so far. Last year I was on a sabbatical. I spent a year in New York. I worked for Bloomberg. I wanted to understand how in the modern world, AI is getting productionized. Because in the research field, in academia, we don't always think about products. We don't always think about exactly how it shows up in the end user, right?

• 7:37Speaker 01

  And so Bloomberg gave me that kind of an exposure. So I've just come back from the sabbatical and ready to be talking to you.

• 7:44Craig S. Smith?

  Uh, yeah, and one of the things I'm interested in is, I mean, that's interesting that you came back right after Alex Nut. So that was the first neural networks, supervised learning sprint. And then by twenty twenty, when you were forming that school, I think we're GANs out by then.

• 8:05Speaker 01

  But that's.

• 8:05Craig S. Smith?

  But it was transforming to generative.

• 8:08Speaker 01

  Yes.

• 8:09Craig S. Smith?

  So you've been here teaching through all of that.

• 8:13Speaker 01

  Yes.

• 8:13Craig S. Smith?

  As I said, I spent a lot of my adult life in China. And I watched China go from nothing to being a competitor of the United States in AI. And in China, I always wondered.

• 8:32Craig S. Smith?

  Where's India? Because churns out engineers at a pace comparable to India. But India has some basis in English language. It has a much, until President Trump, a much easier relationship with the United States. Yeah, and so I, that's one of the reasons I'm going around to the IITs, talking to people. Is why the delay now it seems that there is investment and a push. And the other question is, how quickly do you think India will catch up with the US and China?

• 9:15Speaker 01

  So that's a very complex question. So we'll have to deconstruct it. Pardon if I take a little bit more of the time, but I think this is a very important question. Let me first say, and maybe even correct to a certain extent what you said. You said China is a competitor. I'm gonna say China has pretty much in lots of metrics overtaken the United States. The latest of those is the AAA conference. AAA is one of the largest conferences in the field of AI. And we just heard from the program tiers that there were twenty nine thousand submissions in AAA. Now, that alone is mind boggling. I actually was the program chair of the same conference four years ago, and we did not have anywhere close to twenty thousand. We had, I think, fifteen, sixteen thousand, which was a large number for us at the time.

• 10:00Speaker 01

  But even more importantly, and so twenty nine thousand is just the denominator, so it's fine. Twenty thousand of them are submissions from China.

• 10:09Craig S. Smith?

  Yeah.

• 10:11Speaker 01

  So this is not the final accepted papers. But I would not be surprised if the acceptance rate of China and acceptance rate of US are pretty much similar at this point. A few years ago, when I was the program chair, China and US were close. China was a little ahead. But now it is just ahead by the leaps in amount because nine thousand is the rest of the world in terms of submissions and twenty thousand is China, okay?

• 10:39Craig S. Smith?

  So that's a measure of research.

• 10:41Speaker 01

  That's a measure of amount of research happening in a place.

• 10:44Craig S. Smith?

  Yeah.

• 10:45Speaker 01

  The number of accepted papers would be a measure of amount of high quality research, above and above happening at a place. And again, I am pretty sure that China would be higher than everybody else by a large margin. And this is not just AAA because we were just at ACL in Vienna a few last month. And again, China had many more papers at the conference, accepted papers than the US, any places in the world. So at this point, as I am concerned, China is not a competitor, right? China is sort of, in terms of quantity of research, much stronger than any country in the world.

• 11:20Craig S. Smith?

  What of that nine thousand, the rest of the world, how much of that was from the US? How much was from India?

• 11:26Speaker 01

  So program chairs didn't say that, but my a priority guess would be that about six to seven thousand would be from US. But we should double check because that's a guess.

• 11:34Craig S. Smith?

  Sure.

• 11:35Speaker 01

  No, I wouldn't think that India would actually measure up in this comparison, in this comparison. I remember that for AAA twenty one, because those are the numbers I had worked out myself. They were, US and China were six fifty and four fifty ish each in terms of number of papers accepted. I'm not talking about submitted at that point. India was at thirty two. Okay, so we are not even talking a little less. We're talking like a couple of orders of magnitude less. And now, of course, the research in India in the last four years has increased significantly. But so has the research everywhere else. Maybe India's speed is higher, we can double check, but it will not be higher to the level that it can start matching up to any of these large countries.

• 12:20Speaker 01

  Large, not in terms of area or population, but large in terms of the amount of research that goes on in those areas. So I think the real question to ask is, you know, why? You know, because that's the question, right? And we all have our theories and I can share mine and these are of course theories, right? So the first question we have to ask is how did China do it from our point of view, right? I mean, I don't know the.

• 12:43Craig S. Smith?

  And particularly, yeah, just sorry to interrupt, but China destroyed its higher education in the sixties.

• 12:51Speaker 01

  I see.

• 12:51Craig S. Smith?

  Which makes it even more remarkable.

• 12:55Speaker 01

  There were a few things that really worked in their favor. And one was the fact that early on, and when I say early on, this is pre-AI revolution. Maybe very early two thousands, late nineties, early on. They started incentivizing really top researchers in the US. Who are of Chinese origin to come back to China. And establish research labs with almost, what is the right word, a lot of resources, basically. Yeah. They being the sort of supreme in establishing that group. Now, that was, I think, very visionary, if you think about it.

• 13:33Speaker 01

  Because if you don't have a culture of research, see, research is almost the edge of the knowledge that we understand as a human race, right? So you cannot leapfrog into that place in a little bit of time or a little bit of effort. So people who have that excellence established. If you suddenly start paying them a lot of money and say, look, you should go come back to our country. Of course, you are Chinese, so there is incentive in the nationalistic ideology is present in all of us. We would like to go back and support our nation. And not only will we give you, we will give you a lot of salary, we will give you a lot of resources.

• 14:15Speaker 01

  You will have all the labs, you can, you know, do this, you can do that, you have a lot of power, a lot of authority, a lot of. Initiative can be taken by you to establish a research credible research group, a credible research group in this place. I think that is something every researcher would yearn for because. We become researchers for impact that we can give and impact comes in very many shapes and forms. And sometimes impact comes just in the form of how many research papers I wrote and how much, you know, citations I got. But more often than not, impact comes in the form of how multiplicative my impact was with regards to. You know, education with regards to number of lives touched, did my research go into a, into some product, did the people get benefited from it?

• 14:59Speaker 01

  You know, anything like that, we all work hard to achieve all these kinds of. Impacts, right? And in the U S, anybody who is not American is always on the fringe, right? You know, as an Indian, I would hang out with Indian community, as Chinese, Chinese will hang out with Chinese community. So we never feel that this is our country. Now, I'm not talking about second generation and third generation Americans, but as first generation. And we go into the country from first, after having grown up in a different country. It doesn't feel your country, it feels like a country that supports you. It feels like a country that gives you opportunity, feels like a country that, you know, handles you, you know, you are happy there. I'm not saying you are unhappy, but if you can go back to the your own country that you grew up in, you know, that will be a great kind of impact, you know?

• 15:43Speaker 01

  So I think Chinese government and also there is always this sort of unfortunate thing that. My mother used to say, I don't agree, but my mother used to say that, you know, a. Strong dictator with the right heart, with the right head, whatever, is much better than a democracy, right? And, you know, he uses different words, I'm sort of paraphrasing. And so if the Chinese dictator, to real government or the government which has a lot of authority, let's not use the word dictatorial. They also have some level of democracy. But if the head of the country decides one day that they want to establish China. As a research for runner.

• 16:27Speaker 01

  Then the amount of authority that they can exercise, the amount of things that they can do, how they can use the money very fast. You know, that doesn't easily come into democracies. There are many checks and balances, but the checks and balances sometimes slow you down. In conjunction to the fact that China had already by then established itself as a country of manufacturing. And that was bringing in a lot of money into the Chinese government, pretty much. Everything sold anywhere in the world with a very high likelihood is manufactured in China. So all the whole, the markets are actually in some ways not controlled, but sort of China has a role to play and China benefits from it. So I think the, there were three things that happened at the time. They had enough money, surplus money.

• 17:13Speaker 01

  The government had power. And the government decided to do something about research. And they gave incentivized, used all the tricks of the trade and established mechanisms. So that is amazing, people can come back to the country, you know? But that doesn't create research culture, it starts research culture. Now, they kept improving their research for the next, I would say, whatever, eight, ten years. But till two thousand eleven, two thousand twelve, two thousand thirteen, they were still not anywhere close to being a forerunner in AI. Or in any of such, you know, fields. But then something interesting happened. And what happened is AI changed on us. Alex Net happened.

• 17:57Speaker 01

  Now, this is the time when every researcher has to reinvent themselves. There were only three or four researchers in the world, like the Jeff Hinton and Yann Le Cun and Joshua Benjou and Andrew, sorry, Andrew Ng. And, you know, the other, a couple of other Stanford guys like Chris Manning and some people in Europe, Jürgen, Schmidt-Huber. Few people in the world who had been saying to the rest of the world that, look, you should be working on this kind of AI. But they were not, nobody was. In fact, all these papers are getting rejected from New Rips, from Triple AI. They have a lot of bad blood from those times, right? So this community, the research community on neural networks was ostracized. New Rips, which has neural word in the first letter, was rejecting all the neural papers.

• 18:40Speaker 01

  It had become, people used to joke that it should become bips, not nips, because for Bayesian, right? Right. So modulo these six, seven people, research groups, pretty much everybody else was doing what everybody else was doing, which suddenly became less important. It was a time when there was almost like a reset button pressed in the field of AI. If you look at a paper that was published in twenty twelve and you look at a paper that is being published today, the amount of connection will be extremely loose. Because that style of research has now gone out, neural networks is overtaken and, you know, that is the in thing and that is the thing that is causing all this change and revolution.

• 19:21Speaker 01

  At that time, this fledgling research culture that China had got a boost. Because now it was suddenly the case that no group was any better than any other group. That's right. So this change and because they were constantly trying to establish themselves. Maybe it was even slightly easier for them than establish research groups because the research groups have to unlearn something. They have to, you know, change something that has already been going on at a very high level and slowly move, right? On the other hand, if you are starting out relatively fresh, you are trying to establish yourself and suddenly this thing happens. You are much faster to jump into it and nobody had any benefit at the time. So I think these are the few things that really were in China's favor.

• 20:06Speaker 01

  Yeah. And so then from that point onwards, China is on a path. And now they don't need to incentivize people to go back to China. In fact, another thing that works in China's favor, I'm sorry to say, is the fact that they are pretty bad at English. Yeah. You know, these things go both ways, right? So the, for China, it is really good. In fact, China doesn't even encourage English as much in their country because they want. I mean, I'm saying it from my point of view. That they want, you know, people who are growing up in their country to come contribute back to the country with a higher probability. And this would naturally happen if the English is weak. If the English is very good, it can still happen.

• 20:48Speaker 01

  The, this is much easier path for almost everybody. So now let's look at India now in contrast to all of this, right? So the first thing to realize is that in the nineties, India was bankrupt. When I say bankrupt, I mean that our reserves had dwindled to a large extent. And it is said that we didn't have money to pay our government servants. This is the time when the finance minister opened India up. So until then, at until that point, India was a really closed economy, the socialist economy to a large extent. It was never communist, but it was still socialist to some extent, maybe almost pro-left.

• 21:31Speaker 01

  Kind of ideology was more common if you look at it from a distance. And we never, we were mostly living in austerity because money wasn't readily available, okay?

• 21:43Speaker 01

  Now, in the nineties, Indian markets were opened so that inflow of money can happen from everywhere else in the world so that we can pay our salaries.

• 21:50Craig S. Smith?

  Yeah.

• 21:51Speaker 01

  Okay. So, in a few years, Indian economy did stabilize. That's the good news, right? So far, so good. Then, the other revolution that started happening in our country was around the early two thousands where the I T service industry really started to develop. And this service industry really changed the face of the country.

• 22:10Craig S. Smith?

  Yeah.

• 22:11Speaker 01

  It changed the face of the country. In fact, there are all these terms in the time my job got Bangalore'd. Started happening because a lot of the work that was happening in the rest of the world was actually now moving to India, right? India really benefited from this, no question about it. But this was not yet the same level of benefit that the manufacturing industry probably gave China earlier than this, right? So, none of this led, I mean, it led to better quality of life in the country. It led to people no longer feeling that we live in a poor nation, right? Feeling that it's not like the third world, or if it's the third world, you're the best of the third world, or you know, things like that.

• 22:48Craig S. Smith?

  Yeah.

• 22:48Speaker 01

  That sentiment also changes slowly, perception changes slowly. People started spending, people were, until then, saving, people were always in the saving mode. I have never seen any of my parents or their, you know, generation people, unless they are from the money, from the riches, to be spending for luxury, to be spending for comfort. We grew up in a household where you would think carefully about various products, do pro con analysis before buying any small, you know, like V C R or things like that, anything little, there will be a lot of effort put in to, to do the right thing because we can't buy it, we can't throw it. If something gets broken, we go and get it fixed, we don't throw it. That's part of our culture, right?

• 23:29Speaker 01

  So with that mindset, we never really could take drastic steps like China did. So.

• 23:40Speaker 01

  We always want to have the person, people who are the top researchers in the world come back to India. But we will never give them anything special.

• 23:47Craig S. Smith?

  Yeah.

• 23:48Speaker 01

  We will suddenly not give them a million dollar salary. If they want to come back to India, they should, you know, work in the salary that everybody else is getting. They should work in the resources. Sure, you are more visible, you will probably attract more resources sometime down the line. But you will not have a leadership position from day one to establish a research group or a culture. So this has been part of the mindset at every step. We do not, we do things top down also. I'm not saying we don't do things top down, but there are lots of checks and balances. Whenever the government, the PM decides that they want to do something, there are five organizations who want to take it forward. And five organizations will take it forward in their own ways. I am not going to say that any way is wrong and the one way is right. I'm not making bad value judgment.

• 24:33Speaker 01

  Area times velocity is constant. So if the same amount of money gets dispersed at a larger, in different directions, you know, in the smaller pockets, then the impact slows down, right? So I think those are the challenges that we have been facing in the country. So we have never been successful in bringing that professors. If you, let me just complete. Secondly, we have good English. And so it is much easier for us to go elsewhere and establish our personal lives, right? And to make matters worse, I'm sure this is similar in China. But at least today, the development in China is at a different level. So the quality of life in China is at a very different level than India.

• 25:13Speaker 01

  So India is also progressing, but it is not progressing at the same pace, just because we don't have the same amount of money and the same amount of resources. And also there is some corruption in every country. And again, I wouldn't go as far as saying that corruption is the reason we don't succeed. But I would say that it is also a factor, right? I'm, I don't know how much of a factor it is in China. So all of these things add up. We assimilate really well in the US. We become the CEOs there, the CEO of Google, we are the CEO of X, CEO of Twitter, we are the CEO of Microsoft, we are the CEO of pretty much every company if you start thinking about it, right? But these are people who start, who went there and never came back. They will give back, but. It doesn't change the issues that India is facing. Just money cannot cut it. Yes, money does help.

• 25:55Speaker 01

  But we need to also retain our talent. To retain our talent, we need to give them the environment so that they can be successful. If we, if our environment slowly creates roadblocks on the path of success, then people will at some point get frustrated and say, to hell with it, I'll just go back, go elsewhere and just set up my shop there. And I've seen, I've talked to a couple of startups who are doing well in the West Coast and so on. I was in the US last year, I traveled. And so a few people told me, one group specifically, that, look, we tried for three years to establish a startup in our country because we cared for it. But there were always little things that kept coming in our way. And at some point, we realized that if we really want to succeed, you have to go elsewhere.

• 26:37Speaker 01

  Maybe we'll come back to India once you have succeeded, but that's not the same. So I think we have been a little bit unsuccessful in creating an ecosystem of innovation, of research. And I would go out on a limb to say that all of this gets spurred by professors. Now, I am a professor, so you can almost feel that I'm tooting my own horn. But I really believe that information flows downwards. A person who understands the depth at the highest level will train the next teachers. A teacher will understand a depth to a level that they will train the next engineers. The engineers will have trained well, so they will, you know, do work here and create the ecosystem.

• 27:19Speaker 01

  If you do not have the highest quality teacher, professor, you will not create the highest quality of teachers. If you don't have highest quality teachers, you will not create a large body of strong engineers who are ready to take on the world. Even if you had them, you don't have the ecosystem. So I think it's systemic change will be needed. If we really want to, you know, get out of this local optimal.

• 27:41Craig S. Smith?

  Yeah, and that's something I wanted to ask. I'm here really because my wife is an education researcher and she was at a conference in Mumbai. And we went to Cota to see the coaching schools. And, you know, Cota is sort of subsiding, but.

• 28:02Craig S. Smith?

  Coaching is spread all over the country.

• 28:04Speaker 01

  Right.

• 28:05Craig S. Smith?

  And you have these kids that are working so hard to pass this J E E. Main and advanced in order to get into an I I T. But those are not focused at all on on A I subjects. And then the I I Ts, you have these A I schools now. But the bulk of the people coming out of the I I Ts are not A I engineers. The and from what I've heard, there's still, you go through this. You know, this tiny hole to get into the I E T.

• 28:47Craig S. Smith?

  And then you come out the other side and there's still very high unemployment. Among I I T graduates, I don't know if that's what I've been told, I don't know if that's true. But. I've seen some of the I E Ts are now offering. Degrees in A I for which you don't need to pass the J E E. And is that exam structure, has that been counterproductive in developing a cohort of? A I engineers?

• 29:18Speaker 01

  Let me deconstruct your question step by step, because you actually there's a ton of issues. In just framing the question and I'll come back to whether it is productive or not productive for A I, but it's important to understand the system first. Why is everybody fighting to get into A I, to I I T? Now, in the U S universities, let's always keep the example of U S in mind, you have a lot of Ivy League. Universities, but you also have a lot of non Ivy League, but really amazing universities, right? Nobody is gonna say that, oh, come on, U C San Diego is not good, or U C Irvine is not good, these are amazing universities. They are just not a Harvard and that's all right. And maybe Harvard is a bad word in the current political system, anyway. Why is it that everybody is trying to get into I I Ts and you should know that twenty years ago, we had seven I I Ts? Now we have credit to.

• 30:04Speaker 01

  The reason is that for whatever reason, IITs and Indian Institute of Science and a couple of other such institutions have been able to maintain their premier status at a level that they can be at least for undergraduate education compared to education anywhere in the world. I can believe that IIT undergraduates are as good as Stanford undergraduates. Maybe they don't have as much startup ecosystem, but other than that, the quality of undergraduates, the quality of education that we provide them, they're all at par. Yeah. But it goes down really rapidly as soon as you go out of these seven or eight IITs. Even the twenty-two IITs that we talk about, they were created in name first.

• 30:48Speaker 01

  It's not like a good institution was running very well and we now gave them the IIT status. Yeah. This is one way of doing it. They did it for a couple of such institutions. But by and large, they created new IITs from scratch with zero faculty members as institutions which would come up from scratch. Now, you and I know that education institutions cannot be created in a day. So, an education institution, it was created in the sixties, right after our independence or something like that, early fifty, late fifties, early sixties. Now, it has in the next thirty, forty years established its credibility and become at par the rest, right? But the same is not happening for all these younger IITs. Yeah.

• 31:31Speaker 01

  Now, how would it happen? It would happen if a lot of amazing professors really stayed in India or came back to India after having learned from the best and established research careers here. So, there are like thousands of jobs vacant. If any one good faculty member candidate comes back to the country, every IIT competes for them. Even in the best of the IITs like IIT Bombay and IIT Delhi, we have faculty positions which are easily available for good people. Yeah. And what happens equivalently in the US system? In the US system, people apply to ten, twelve universities at the undergraduate level. You do know that there is also a lot of stress there, you know, we can't take.

• 32:12Speaker 01

  We can't ignore the stress that anybody who is fifteen, sixteen year old trying to figure out their college goes through. No, it's, there is a lot of stress, both ways. It's different kind of stress. So in, in the US, you better have an art, you better have done voluntary work, you better have a sport, you better excel in your grades. You better did, you better have done some fundraising for something, you better be a part of robotics. Only if you have all these things, will you be actually considered for the top school, you know, you know this grind.

• 32:45Craig S. Smith?

  Yeah, I have kids, right, yeah.

• 32:46Speaker 01

  So this is the grind in the US. The grind in India is that look at the scale that we are operating at. The number of students that we have, the number of top premier places that we have. It is impossible to make this wholesome individual and have them go through this regard. So we take the view that we will do a test. And based on the test, if you have achieved this much, and if you have established excellence among your peers, then you can be taken for this top. So it's a competition, there is, there's a competition, that there, there's a different competition, here there's a different competition, but competition stays. Now, when competition happens, market gets created around the competition.

• 33:27Speaker 01

  So now my friends are paying twenty five thousand dollars so that somebody can counsel the child in every step of the admission process for college in the US.

• 33:39Craig S. Smith?

  Yeah.

• 33:40Speaker 01

  Because there is so much insider information that they need to know, they need to know the value of doing more voluntary work versus less arts for this profile, blah, blah, blah, right? A counselor really guides them through it. In the same way, the market that gets created here is to teach them physics, chemistry and math, because that is what they are tested on. And at eleven, twelve, you know, this is what you should expect to test them on. I mean, AI stands on top of computer science and their computer science knowledge cannot be assumed, right? At that level, because some people are coming from villages, we still have people who have never seen a computer. In in in they never touched a computer, they may have a phone. Everybody has a tiny computer, but we call it phones, you know. Basically, we have to make sure that whatever is our education system that can deal with all Indias.

• 34:24Speaker 01

  Again, I often tell people India is not one country. And so is US, I mean, again, there is the south, there is the, there is the Midwest and there is the coast and there is the blacks and there is the Caucasians and there is lots of Americas. But I think the diversity is much higher in the US, in India, sorry. Because we are dealing, not the diversity of nationalities, but diversity of different points of view and different lifestyles that some people are in the villages and they can't, they don't have any means. They are studying under light, public light. And there are some people who are really affluent and they will, you know, travel to vacations in the, to the US over summers. So we're really talking about a high diversity.

• 35:02Speaker 01

  So we have the exam or the admission process needs to be from the lowest common denominator, otherwise it would be really unfair to many. No. And so a test is an easy and scalable solution. In fact, in our time, we used to write answers, now it's only tick, tick mark because you can't scale grading beyond a point. So because of that, markets get created because of that, coaching institutes get created because of that. Everybody doesn't have a good coaching institute around them because of that people start going elsewhere and you know, quota just came up as a center for learning because of their mental problems started happening. They are also happening in the US.

• 35:42Speaker 01

  So I wouldn't say personally that any of this is a major issue, it's different. But I don't find it negative beyond the fact that if we had many top IITs, this kind of pressure would not have been there. It doesn't have to be IIT, if we had many top undergrad institutions of high quality, this kind of, that caters to a size of population as India.

• 36:13Speaker 01

  This would not, the pressure would have been much easier, whether you send your kid to Kota or whether you keep them here. Yeah, people would have worked hard, but people would have had many opportunities to get high quality education. I would really hope we live in an India like this in a few years, but I don't see that happening. And the reason I don't see that happening is for that, we need a lot of good professors to come back. Then we need a lot of good teachers to be trained. This process takes time and that is not really happening. Okay, so that is the first part of the narrative. Of the question that you asked me. The second part was that these kids are not really learning AI and these kids get admitted into various degrees. And then they don't always get jobs and then there is some other IIT madras basically which has started the bachelor's programs. Let's talk about that for a minute.

• 36:57Speaker 01

  As we discussed that, I don't think we can have input with AI because they wouldn't know computers for get AI, right? So at that point, we shouldn't expect them to know AI, we should expect them to have fundamentals and physics, chemistry, maths is a fair way to do fundamentals. Maybe you can add some other things. Actually, I feel that it is better that not everybody is coming into AI. And the reason is that if you think about how future of work looks like. It is actually not clear that computer scientists are going to stay at the top of the industry for a very long time. The writing is already on the wall, I would say.

• 37:34Craig S. Smith?

  Yeah.

• 37:35Speaker 01

  The jobs are coming down, Microsoft and TCS and Google and everybody is laying off Meta, whatever. Everybody is Amazon, everybody is laying off engineers. Berkeley undergrads last year, computer science, fifty percent of them did not get a job.

• 37:54Craig S. Smith?

  Oh, is that right?

• 37:55Speaker 01

  There, there was a post on LinkedIn by a professor from Berkeley, so you should double check that. I can't speak, you should double check the fact, maybe if it's wrong, I will be happy to be stand corrected, to stand corrected. But essentially, this is not a phenomenon that is India or IIT specific. This is a global phenomenon. And I really hope that you have done other podcasts which thinks about the long term impact of AI on the job market. Because you will always get two opposing views. One opposing view is dystopic, one is, you know, optimistic, right? One would say that a lot of jobs will be lost, but a lot of jobs will be created. And the other will say that, look, all the jobs that we understand, how many of them are going to be gone and we don't know what is going to be created, if anything.

• 38:40Speaker 01

  And even though I'm an AI researcher, I am not in the purely optimistic view. Until three years ago, I was, but with ChatGPT, I think things have changed. With GPT four, things have changed with all these clouds of the world. So I feel strongly that computer science will still be needed, but the number of computer scientists needed will be much less. Actually, people argue, some people argue, Geoff Hinton argues, that it's better to be a plumber than to be a computer scientist. Again, I don't take the extreme view, but there is a point to that sentiment. And the point is that either you be one of the best computer scientists. Or you take up a skill which is more sort of with your, doing things with your hands.

• 39:23Speaker 01

  Because robotics is not yet there. Right. And there will maybe come a time five, maybe two, three decades down the line, or maybe earlier, who knows, right? Where robotics and AI will come together at a level that a lot of things that we can do with our hands, robots will be able to do. That is not yet happening. So at least for the next round of kids coming up. I am of the view that you cannot mindlessly take computer science as your discipline. You should think about if doing a, getting a good job is the only goal, right? If you're really passionate about a field, you should really do that, because then you become the best of that. But if the goal is to just get a good life, you cannot just decide to take what is hot today because it may not be hot tomorrow. So just to answer the question that you raised.

• 40:07Speaker 01

  I think the fact, I think it was true that in twenty twenty three, or maybe it was twenty twenty four. I think there was one year when a lot of IIT Delhi students also did not get placed. I think it was twenty twenty four. But this year is better. Twenty twenty five is better already. A lot of the students did get placed from IIT Delhi. And however, it is not entirely clear to me that asking these students to train in different disciplines is a bad idea. Because it is good to learn civil engineering because you will still have to make roads. It is good to learn mechanical engineering because you will still be doing, you know, design automation, you will still be doing many things that I studied that.

• 40:51Speaker 01

  And it is still good to learn computer science. But I think what was happening de facto for the last twenty years is irrespective of your engineering discipline. You had a high probability of moving into a computer science job. That is gonna change, in my opinion. Now, the other thing is, do we need a lot of AI people? And I believe that we do need a lot of AI people in the interim. I don't know for how long, but for now, we do need a lot of AI people. Now, there are different IITs take slightly different views. Yeah. IIT Bombay, IIT Delhi take the view that AI sits on top of computer science. And so in order to really understand the depth of AI, you need to understand the depth of computer science. It should be considered as a master's discipline rather than an undergraduate discipline.

• 41:36Speaker 01

  There are others who take the view that AI has now become so pervasive that we should have undergraduate degrees in it, it's a discipline. And then there are some people who take the view that JEE is such a high bar. That let us give some online education, some MOOC style education to a lot of the students who have not been able to. Who have not been able to get into the top institutions. So basically, what IIT Madras is trying to do is that they have an online program, mostly online program. Think of it like a course, but it's a full degree. And the input is easy, you can easily get in and then you grind. But you don't get, you don't grind at the same level that an IIT student grinds along with their peer group and personal teaching in, in room teaching.

• 42:19Speaker 01

  This is all online. So there will be some students who will really benefit from this because they are self motivated. And they never got good quality education and once they got access to good quality education, they felt like, you know, they can succeed. But I would also say that good quality education existed even before this degree. Coursera had so many courses.

• 42:38Craig S. Smith?

  Yeah.

• 42:38Speaker 01

  The first AI course, the first move was a move from Stanford, you may remember, right? I think it was Andrew, Andrew and no, it was Peter Norvig and Sebastian, what is happening to my memory, anyway. It was from Stanford. And that is when Coursera and Udacity and all these platforms got created and everybody MIT edX and everything started happening. So, good quality educational content has been there for a long time. The reason they never worked is because the kind of sustained motivation needed to go through a long curriculum without having good peers around you and succeed has been, you know, it has been difficult to achieve for students.

• 43:22Speaker 01

  So the jury, in my opinion, is out on the BSc program of IIT Madras. That said, I think it's great that they did this. It created yet another revenue. Especially for India because sometimes if there are students in India, they may find the accent of, you know, other people harder to understand. Sometimes they may be able to find other peers who are also taking IIT Madras. A thing because it's correspondence, it's a sort of an online course. They may have, you know, peer groups that they can interact with personally. IIT Madras also had, I think, some view of bringing students to the campus for a few classes or something. I don't understand the whole of it, but I think if you really strongly believe in online education. I T Madras has done a great thing.

• 44:05Speaker 01

  If you feel that online education can help a few but doesn't really help a lot of people, then I don't think I T Madras thing is also gonna help. And let's see what happens in the next five, ten years, he will have a better understanding. This is as much as I can say about very hard.

• 44:18Craig S. Smith?

  Yeah, so the bottom line is it's the advance of A I in India or bringing A I up is not a human resources problem and it's not really an education problem. Because you do have these schools of A I, you do have the I I Ts with whether or not they're studying computer science. You have brilliant students. I- is it a funding? I mean, is it more important that the there isn't the proper funding from the government? And I know that's changing.

• 44:51Speaker 01

  So I would say that it's an H R problem. And it's not an H R problem with regards to students. It's an H R problem with regards to professors. Yeah, so as I have said it a couple of times earlier, I believe that the whole ecosystem really gets spurred with professors. They are sort of, they don't get the limelight. And so people don't think from that perspective. But this has been my view for several years. That until you can incentivize the best professor to come back to India or come to India or stay in India and teach, you will not change the ecosystem. And so therefore, it is an H R problem because we have School of A I. In the last five years, we have been able to hire five new people.

• 45:34Speaker 01

  We have C minds in I T Bombay. I don't know how many people they have been able to hire, maybe three or four. So we, it's not like suddenly we started hiring, we got fifty people or twenty people and they go and we all our slots are full. None of that is happening. Why? Because the best of the students who do a P H D in the best of the institutions, including my own undergrads, they have done P H Ds everywhere in the world. I have students who have done P H Ds at C M U, P H D at Stanford, P H D at U D O B, everywhere. None of them, not one of them has come back to India and become a faculty member. A, it's very hard for them to become a faculty member because the amount of money they will get in industry is a couple of orders of magnitude higher.

• 46:15Speaker 01

  And even if they get hired, they want to become an academic, they will not come to India because there's a cost differential between and the resource differential between US and India. And so what ends up happening is there are very few people in AI PhD world who want to become academics. And there are far fewer people and there are very few people in AI world who want to come to India and the intersection is practically null. Or maybe a few handful and those handful people get hired at I T Bombay, I T L A, I T Madras, but that's it. So, so if you want to change the system, yes, you will need resources, et cetera, but you'll first need professors. I can bet you that if you can get hundred top professors next year, in five years, we will have five hundred new teachers.

• 47:00Speaker 01

  And if we have five hundred new teachers, then I T Madras's BSc online will not be needed.

• 47:05Craig S. Smith?

  Yeah.

• 47:06Speaker 01

  Because people can go and learn in a class.

• 47:08Craig S. Smith?

  There's a guy, you probably know him, Partha Telakdar.

• 47:11Speaker 01

  Yes.

• 47:12Craig S. Smith?

  Yeah, I interviewed him on the podcast when he was still at CMU.

• 47:16Speaker 01

  Oh, wow.

• 47:18Craig S. Smith?

  And then, then he came to Bangalore, I T Bangalore, and I wanted to interview him on this trip. He now works at Google DeepMind.

• 47:28Speaker 01

  Yeah.

• 47:28Craig S. Smith?

  Google DeepMind.

• 47:29Speaker 01

  Yeah.

• 47:29Craig S. Smith?

  Uh, and Google is very difficult to interview people in Google. I'm not able to talk to them. But big AI giants, Google and Amazon and Nvidia, they're investing tremendous, tremendous amounts of money in India. It, it maybe, I don't know proportionally, maybe it's not tremendous, but it looks like a lot of money. And they're hiring a lot of the people, the top researchers in India. Is that a good thing? Because and could that draw some people back from overseas who want to live in their home country?

• 48:06Speaker 01

  Yes. So when Google got established, Google Research.

• 48:10Craig S. Smith?

  Yeah.

• 48:11Speaker 01

  In India, I'm talking about Google Research in India, this was seven, eight years ago. I was actually at their inauguration, I was invited. And I said one thing, that to me, the success of Google Research will be not that they could hire a lot of Indian talent in India. To Google. But it would be that they would be able to encourage, incentivize, facilitate and bring a lot of people not in India back to India. To answer your question, I think it's a great thing that we have opportunities here. If some people want to come back to India, they can come back into these top research centers. They will end up doing high quality work. They will also have a slightly better balance in their, you know, salary and, you know, quality of living.

• 48:55Speaker 01

  I mean, this is not strictly true, we should talk about it. I believe that I T professor's salary is infinite. Because we can get a lot of honorarium from a lot of company projects and consultancies that we are allowed to do. And so our salary is potentially infinite, but people don't realize that. But let's, let's keep that on the side because not everybody who becomes like an academic, becomes an academic for the infinite salary. So most people don't spend their time optimizing salary and therefore we don't have any very strong exemplars to showcase that, oh, this person is really earning much more than a Google salary while being an academic. Or even if it's there, nobody's flaunting it, so we don't know. Nevertheless, I hoped that Microsoft Research India, IBM Research India,

• 49:40Speaker 01

  Google Research, DeepMind, Google DeepMind, no, it was Google Research, not Google DeepMind India. They all will become natural attractors for amazing quality talent and they will be able to bring people en masse at scale. Now, two things have happened. They have definitely attracted people back. I personally know people who were in the U S, living a good life and have decided to move back and join Google or join Microsoft or, you know, whatnot. So I do know that this is happening, but I know it anecdotally. I do not know it statistically. Which is to say that it is helping the Indian ecosystem, but not by a lot.

• 50:23Craig S. Smith?

  Yeah.

• 50:23Speaker 01

  So if by natural process of evolution, if somebody feels that they want to come back to the country, often it's for the family, they are the only child, or often it's for nationalistic streak, or you know, some of those one or two kinds of typical people who want to come back to India. IBM Research and Google Research and Microsoft Research and I T Delhi and I T Bombay and I T Madras and I S C, these will be all the typical contenders for a top person. And some people will go to academia, some people will go to these research centers. We will all benefit slowly. But it is not happening at the, that the scale that I would have hoped. We are a country of, I don't know how many billion people, right, one point four or whatever.

• 51:02Speaker 01

  You can count these top A I researchers on two fingers or whatever, two sexy finger. I'm just, it's, we won't find more than, so I think in two thousand eighteen, we had three thirty six P H Ds in A I in the country. Now that number may have changed, but that was less than two percent of the world's P H Ds. Imagine that, you know, we are one seventh of the world's population, but we are less than two percent of the world's P H Ds.

• 51:28Craig S. Smith?

  Yeah.

• 51:29Speaker 01

  This was two thousand eighteen, so things may have improved, but in my opinion, they haven't improved by leaps and bounds.

• 51:34Craig S. Smith?

  What about the, the government's A I? I've forgotten what it's called, but this government initiative, I'm gonna talk to Abhishek Singh. Is that important?

• 51:45Speaker 01

  Is it on it?

• 51:46Craig S. Smith?

  Yeah.

• 51:47Speaker 01

  So, I mean, the government has been very supportive of A I from day one. Actually, in India, we are used to the government waking up late. But this government for A I has been proactive. So, that is the good part.

• 52:03Craig S. Smith?

  Hmm.

• 52:03Speaker 01

  They have invested money slowly, they have created policies. Early on, national strategy on A I came in way back in two thousand eighteen or something. I think it is Jensen Huang in two thousand eighteen gave a talk in front of Modi from Nvidia. And later it got morphed into digital A I mission, which Abhishek Singh has been running. Or they also understand the issues, they understand the value of data, they understand the value of compute, they understand the value of talent. They have been putting money in specific things. We can critique it, I mean, as a professor, I can critique it, I can give you the pros and cons from my perspective, different people will have different ideologies. I personally feel that the speed has not been good enough. I feel that the compute must promise way back in two thousand eighteen, nineteen.

• 52:49Speaker 01

  We are still in the process of getting it, acquiring it. I feel that there hasn't been any out of the box solution to bring back talent. It has been more in the spirit of let's develop the talent here.

• 53:03Craig S. Smith?

  Yeah.

• 53:03Speaker 01

  Which is also fine, but I do think that it would have, you know, made us move faster if we could somehow attract people. But I don't think that we can come in from a capitalistic view that many other. Countries can come in that will give it like Meta is suddenly offering an unreasonable amount of money for the talent, right? No, I'm not saying Meta levels, but the idea is that we give them a certain level of perks, not just in their personal emoluments, but also in their resources that they have at their disposal. So that they can move things faster than we can, you know, move fast, just like China did. We have not had any policy of that nature in India. The government has put in a lot of money on specific sectors.

• 53:47Speaker 01

  So they haven't taken the view that we need to develop AI. They have taken the view that we need to contextualize AI for specific sectors like healthcare, like agriculture, like this. And so the emphasis is on products or proofs of demonstration which can, which are ready to scale up, which use AI for specific problems in that sector, requires human experts and AI experts to come together. It's a fair view, it's a view, it's a point of view. And maybe this is the best way India should develop. But as an AI professor, I feel sometimes disillusioned that why don't we put in at least some large amount of money in developing fundamentals of AI? Because any applied AI researcher needs to still be guided by the fundamental AI researcher.

• 54:29Speaker 01

  So we can't just take the fundamentals out and say that we will just adopt the fundamentals from everywhere in the world and then we will just contextualize them. I feel that we are missing parts of the picture, there are gaps. But I would also say that the government has worked very hard in various kinds of AI initiatives. And Abhishek Singh will give you the best and really he has done a lot of work and just amazing amount of work. So he will give you a lot of these things that the government has focused on. But I still feel that there are aspects that if also focused on, if we could bring that talent somehow, then it would really make a difference. If we could make the startups life easier, maybe we will not lose startups. If we would, if we could get a lot of amazing teachers that get trained by these top professors,

• 55:14Speaker 01

  you know, maybe the life would be slightly different. So I think there are gaps that we need to think about, the countries need a lot.

• 55:19Craig S. Smith?

  Yeah, AI, you need data, compute and algorithms. India certainly has a lot of data. Is, is there enough compute? I know the government is building data centers. What's happened in the States is the big private companies own the data centers. And the research, there's, I'm sure you heard it. The University of Washington academia is sort of begging for compute. And so a lot of top researchers go to industry because they have access to compute. Does that happen in India? Is Tata, for example, building data centers?

• 56:02Craig S. Smith?

  And do they support academia? I mean, how does I T Delhi get its compute?

• 56:10Speaker 01

  Yeah. So these are very important questions. I think right from National Strategy Document in way back in two thousand and eighteen. There has been a promise of large compute. It was called the Eravat system. Eravat is a fictional elephant in our culture. The, the speed at which the computer is coming in is very slow. There are things that have happened and Abhishek will tell you more. Now the compute is available to us at subsidized costs in, in I T's. I T Delhi, I T Bombay, I T Madras, they all have been doing their own compute basically to large extent. So we have been buying GPUs. We have been setting up data centers in our own facilities. These are smaller data centers, not at the level of the country will benefit. And often they also have government support. For example, the Indian government gave us fifteen million dollars for School of A I.

• 56:55Speaker 01

  To set up a compute facility which will have four hundred of eight hundred GPUs. So that's not unreasonably small. But unfortunately, we also in I T Delhi got slower in building it. So now we are very close to building the completing the data center. Maybe in a month, we will have the data center ready and then we will start use the compute early next year. But it has been longer than we anticipated. I'm sure this is the situation in many other universities. Some universities are faster. So a lot of models are coming up. We buy compute. We give it to a company to manage it. That is model number one. Model number two, we don't buy compute. We just get the money. And use the cloud compute. Some data centers exist, government has subsidized it for us.

• 57:40Speaker 01

  We buy compute, we host it internally. And manage it as individual professors. We buy compute, we host it internally, manage it as the whole institution. All of these models are there, the government is supporting all the models. It's, I'm not saying that they're not supporting any, they're supporting as much models as they can support. But still, as the country, the, the speed at which we should have had compute, we have not been successful. There are many again reasons for that.

• 58:09Craig S. Smith?

  And then data, I mean certainly India is overflowing with data.

• 58:14Speaker 01

  Right. So data is the other question. We have been a culture where all our data is in silos. Yeah. And there is a sense of privacy and security on sharing data. And there is a sort of natural sense of not open trust between even, you know, two government institutions or, so as I A I Ts we benefit from it because people trust the I A I T system. But Google and Microsoft would not always be able to get some of the government data because they want the Indian data to stay inside India. So there's also a lot of push by the Indian government to create, you know, sovereign L L Ms, train our own L L Ms on India data. They've also created, you know, I think digital A I mission has created some repositories of data and they are trying to collect more and more data.

• 58:57Speaker 01

  There are some professors in India who are specifically curating data for the problems in India, like I T Madras is doing a lot of work on curating multilingual data. Again, Google is also doing some of that, Microsoft is also probably doing some of that. So the point is that there is a lot of activity. I think if I have to just sort of summarize where we are, there is activity in almost all of these directions. It's a bit diffused and it's, there are many actors and there are many players. And so there's a little bit of a chaos in the whole organization and it's not like there is one winner or two competitors and, you know, you can just work with them and keep things moving.

• 59:38Speaker 01

  So I think that's where we are. I'm hoping that these things will consolidate a little bit and a clearer picture will emerge. And the infrastructure issues will get taken care of in the next two, three years that we can really move forward. But by then, other cultures would have moved much further, yeah, and so it will be harder to catch up, unfortunately.

• 59:54Craig S. Smith?

  Yeah. Okay, I don't wanna wear out my welcome.

• 59:58Speaker 01

  I hope we end it on a positive note because there's a lot of excitement in the country as well.

• 1:00:03Craig S. Smith?

  Yeah, you expressed some of that.