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In two significant areas, one is in agriculture, which is the highest employer, biggest employer anywhere. It’s also one of the least productive of sectors that we have anywhere. And that productivity gap in agriculture, if we can narrow it even by a small percentage, you will move the needle by a significant amount. And AI can do that. Just think about much of agricultural output in the global south comes from smallholder farmers who lose 40 % to 50 % of their crop because of pests. Now, if a farmer can identify what the pest is and use a homemade remedy that is given to them in their own language and using local ingredients, if I can move that 40 % down to 30 % or 20%, suddenly a huge swing in the farmer’s income.

So there is no question from a human perspective, if my income is going to, if my crop loss is going to, go up by 10 or 20%, you know, I will adopt it. So. So that’s the first thing, which is purpose. Now, in addition to agriculture, small businesses. I don’t really need a whole bunch of employees if I can essentially harness AI to do market research, to do analysis, and almost be an employee. And I can be a one -person shop and employ and really build a business. Now, beyond that, there are several other areas of application, which, you know, we’ve done the analysis to kind of see, you know, where are some of the biggest opportunities.

So there’s agriculture, small business. After that comes education and skill building. Another very powerful use of AI. And a fourth area is health care. Now, for each of these areas, there is an element of a major chasm that the humans need to cross. And that chasm doesn’t have to do with technology. It doesn’t have to do with how big the pipe is. It doesn’t have to do with whether I have access to, you know, any of the devices. It doesn’t have to do with the various elements of the digital public infrastructure. In fact, India is one of the shining examples. of the distribution system, the rails having been laid. But the key chasm, the big jump that we need to make is across a trust gap, which is in addition to digital infrastructure, in addition to other forms of infrastructure that includes talent and data and compute, there is a trust infrastructure that needs to be built.

Because from a human perspective, I will use a piece of technology if I can trust it. Now, there are many reasons why people are, on the one hand, very excited about AI, as is very evident over here, and at the same time, there is a lingering concern. There is a lingering concern because I don’t quite understand what’s inside that black box. I don’t quite understand how the hiring algorithms work. Why did I get rejected from this job? Why did I get that diagnosis? From a healthcare system. What is the language system telling me? Is something being lost in translation? Can I trust an image that has just been sent to me on social media? So the issues of trust are a very important set of questions.

And then the data that I’m submitting into the system, simply by interacting with AI, I’m submitting data and providing input. I’m actually acting as labor for the AI industry. What’s happening to the data? Who’s using it? Where does it go? Can it be used against me? Is it going to be used in my favor? So the whole question of trust is going to be an enormously important part that we need to consider. So first, purpose. Second is creating a trust infrastructure. And the third is recognizing that no matter what we say, no matter what rhetoric we put on our screens, no matter how many alliterative slogans we have in our meetings, AI is going to be a force for inequality.

There are many reasons why AI is going to create an unequal playing field, not the least of which being the fact that the algorithms are feeding on data. Data is simply a reflection of the past, and as we know, the past is not a terribly equal place. So that algorithm is going to essentially act as a mirror to our past, and maybe part of the risk is that the inequalities of the past get reinforced into the future. There are inequalities in terms of who has access to better tools. Now, even with open source and people being able to, you know, vibe code themselves, there’s an element of democratization, but there could be very different levels of access across a society.

So the usage context itself could be unequal. There could be inequalities when you go into different parts of the world, when you go to different parts of the country. So geographically, there is likely to be inequality. There’s inequality in terms of who’s providing you AI. So today, much of the frontier AI models are coming from two places, United States and China. And much of China’s AI infrastructure is built on top of a foundation from the United States. Much of the foundation of the United States, the leaders of the companies that are producing it, they’re all over here, really small. So it’s a tiny industry that’s providing us the foundation from which we are building the rest of the system.

And then one last really major source of potential inequality has to do with the resources that AI is absorbing, primarily energy, water, space, and even kind of our environmental resources, enormously important. Now, none of this means that we should stop the train. But we need to understand the human impact. that AI is going to have, both positive and negative, as we move forward and put the relevant policy systems in place, the relevant trust -building systems in place. Otherwise, we might be not only wasting a demographic dividend that India has got, but a trust dividend that India has got. One critical and really important aspect of an ecosystem like India is that it’s a very trusting society, very trusting in terms of digital.

It’s a very trusting infrastructure. Trust levels in India is in the 70 % range, whereas in the United States is in the 25 % to 30 % range. That’s a huge platform to build on. And it’s going to be really important for us to follow through with that trust that users, our potential consumers are giving us, and for the policy and the technology sector to be able to make sure that that trust dividend is not wasted. So with that… But I’m going to sit down, and I look forward to learning from my colleagues on the panel about how do we make AI more purposeful and not just powerful. Thank you.

Thank you, Professor, for the insightful remarks. Very exciting, and at the same time, you know, you raise some concerns around inequality. Let me first go to Arunji. You know, as we said, like the demographic dividend that India holds, we will be adding a million plus to workforce every year. How do we make sure that they’re skilled, they’re ready for what the market is asking, the skills are continuously shifting, as CEO of NSDC with the mandate of skilling the population? How do you look at this? How is, you know, do you see AI as a threat, as an enabler? How are you approaching this?

So, good morning. AI is an opportunity and an enabler. So let me begin with a few words about NSDC itself. So this is a national platform institution under the Ministry of Scale Development. And we work through two arms, 36 sector scale councils and close to around 400 training partners. So these are the two arms through which we have been working in the scaling space for the last two decades. With AI coming in, of course, it’s an opportunity, as I say. But primarily in four areas we have started work. One is, of course, AI and how career trajectories are getting shaped. So we require some kind of guidance, direction, et cetera. So work on that front. Second is creating scaling programs for AI, AI scaling programs.

Third is how does AI itself affect the entire value chain of scaling when it comes to, say, training, assessments, counseling and the other. areas. And the last is since we do large scale program management, how do we use AI to evaluate or monitor outcomes? These are the four primary areas we are working on. Obviously I will just pick for each of these areas in brief. The first one, setting the agenda or setting the direction with respect to careers, NSDC and the sector skill council, specifically the IT sector skill council, we have brought about certain reports, how jobs get shaped by AI, the new jobs and how the existing jobs get changed, etc. Within that is career counselling.

Once you know that this is the way a certain job would get transformed or a new job would come, a lot of career counselling is required for students. So how do we create AI enabled career counselling tools, models, etc. So that’s one area of big work. work. Coming to AI skilling programs, clearly there are three trials. The first is of course where we talk about AI for all skilling, which is more like AI awareness and AI usage. So we have this skilling for SOAR program under which we work with schools etc. The second is where we talk about how does skilling affect practitioners or people in the workplace. And this is where our sector skills councils are busy putting together how do we make the current programs, how do we bring in AI modules in it.

Of course to begin with how AI affects job roles to start with and then translating that into how the new programs would look like. The third area is AI for engineers where we skill engineers and this is where we work with engineering colleges. We have something called the Future Skills Centers and we work with close to right now around 10 ,000 students and around 50 ,000 students. And we work with 10 ,000 students and around 50 ,000 students. So we have a lot of different things going on. We have a lot of different things going on. We have a lot of different things going on. We have a lot of different things going on. We have a lot of different things going on.

We have a lot of different things going on. We have a lot of different things going is to create close to around 22 companies work with us, including Microsoft, Google, and Amazon, and Schneider’s, and Siemens, et cetera. And we create these kind of skilling centers within engineering colleges. The good thing about it is that this is part of the credit -based system. So students can pick up over the four years they are doing the engineering every year, every semester they pick up a course, and you string together a course, then you have a kind of a program for, say, an AI architect or something like that. So we look at the entire skilling program. The third is, as I said, AI is changing the way we skill, you know, the way we train, the way we assess.

Early days, again, pilots on, how do you use AI as a training assistant, you know, to our trainers, you know? So what do we do, how do we work with that? Similarly, assessment is a big area. Please see, many of our training involves vocational training, which means hands -on training. So we use AI for hands -on training. Hands -on training requires a lot of… piloting etc so towards that we are working can we say for example just giving an example say what’s a good weld or what’s a bad weld if the AI is trained on that then it can help the current assessor in actually you know actually providing a better assessment and also augmenting the number of assessors we are currently having the last piece is we have our skill platform for large scale program management today it is called SID and we are now bringing elements AI into it so that how do we how do we monitor outcomes better so big challenges in a country like India is monitoring outcomes they are facing how to use AI on that area also so

very interesting and exciting to see what you have brought to the table Neenaji if I can move to you Anandji spoke about the skilling programs but certification standards are very key and how do you do that in an environment where skills are you know the courses are becoming outdated in months the requirements are shifting from your vantage point like a lot of content being created a lot of initiatives all around how do we define qualified professional in AI? Is there a plan for certification or standard setting? How should we think about it?

Thank you so much. Thank you for inviting me. I’m a former executive member of NCBT. One minute about NCBT. NCBT is a regulatory body NCBT is a regulatory body under the Ministry of Skill Development. So something on AI since we’re sitting in an AI conference. Around two and a half years back we came up with a skilling framework for AI. And the framework actually talks about three layers of skilling for AI. It talks about skilling for all. It talks skilling for few and skilling for many and skilling for few. all of the initiative we started working as part of the SWOT initiative that was mentioned by Arun also. Now what does that mean? Like all of us know how to use payment gateways or payment UPI etc.

Can we actually use AI in a similar way? So our thought was can we take AI to everyone every nook and corner a radiowala or a plumber or somebody who is a beautician etc. So what did we do on that? And I’m going to take a minute before I come to a certification question. We actually have tried creating a small nano -credential for something which a beautician can use and how can she use AI for giving a better service to the customers. We’ve actually created a virtual try -on for a tailor. How can a tailor use a virtual try -on concept for actually taking it to, you know, telling a person which design or what kind of a color suits a person.

We actually created basic courses, of course, on AI, which also have been done and they were launched sometime in July. We’ve got around two lakhs plus people who registered on those courses. But idea was, how can we take it to everyone? So how can simple things like, how can a plumber find out if there’s a fault in the pipe? So can AI be used there? So one of the points which I think Professor talked about was, how do we take it to masses? How can AI make an impact in our lives or everybody’s life, like internet is doing or anybody else is doing? So that’s what we’ve tried doing as part of some of the courses that we already are in a state to launch.

In fact, some of the courses have been launched. We all been talking about in this conference that AI is going to replace coders. So there’s going to be lots of jobs, etc. But still, how can actually you use AI for helping to launch? We actually are stalling. we’ve actually demonstrated how AI can help in coding also. How can it help me to learn coding? How can it help me to test a particular program? So AI doesn’t stop at just being AI and taking away jobs. I think we have to groom and possibly diffuse, I mean, the word which has been said, the concept of AI which is happening. Now let’s look at certification in the courses.

Very wonderful question he asked. Things are changing almost every day. I think the carpenter’s role is going to change. In fact, we have from Furniture and Putting, the Sixth Grade Council, a small little model which says, how can I design a particular furniture better if I have AI? Knowing the wood, amount of wood, and the space for which I have to design the furniture, can the carpenter actually use AI to design the furniture better? That’s the way it’s going to make an impact. Now how can I embed this course in a course which I’m teaching a carpenter? That’s the impact it’s going to make. And that’s what we’re trying to do. So a wonderful question from that point of view.

So what we’ve done is we came up with the concept of stackable micro -credentials or stackable nano -credentials. Which means based on the changes which are happening, you could actually stack the small, small modules together and make a skill that is required that needs to be done. And in these skills, you could also have something like employability skill, which could be design thinking or others. And it could also be an AI module which can be embedded, which actually tells you how AI can be embedded in a particular course. For example, our ITIs already have a small seven and a half hours module which have been embedded as basic concepts of AI which are now being taught to every ITI student.

Now what we want to see is how can we actually do our late machines or other machines, how can they be done in a better way with AI. So that’s why we are trying to do it. Now certification is now, the way we are trying to do is small, small certificates. You know, which a person earns, can I. actually lead to credit and the total of that actually can also take you to a larger credit and that’s how it’s been planned as part of something called National Credit Framework that we actually came up with from NCVT and the Ministry of Education. This was launched around two years back. So that’s how it’s been planned. I hope that answers your question.

To Rakesh, historically, you know, whenever general purpose huge technological change comes in, it ends up increasing divide for some time till people evolve and you know, you learn new skills and get off the curve. Now in India’s vantage point, we spoke about the starting point we have. In your view, what needs to be done differently? We heard a few initiatives in motion to make sure that we cross this transition and manage this transition very carefully and aptly.

Thank you so much. It is a very, very pertinent question. And I truly believe that in the past, we have been able to do this. And I truly believe that in the past, we have been able to do this. And I truly believe that in the past, we have been able to do this. era, India was at a disadvantage. It was very difficult when we had internet coming in. India was not as uniquely placed as it is placed today. We have ubiquitous connectivity. We have low cost of connectivity. We have a huge amount of internet penetration. We have applications which are general purpose applications used by a billion people like UPI and others. So today our starting point is very, very different, not only for our users, but also for those who are making these applications.

I think journey started about 10 years back when India realized that we have to make applications for our own people and not just rely on the world to make applications for us and take them forward. So that’s where we are today. Hence, the opportunity for us is immense, given that we are a billion people with access to low cost connectivity, reliable connectivity, already using these applications for our financial transactions and other use cases. And especially for all the programs that we just heard, NSGC and others are today making. So I’ll just talk about three things that I thought I’ll bring to your notice is, I think the point that we should move from digital literacy to work literacy.

What that typically, the point that I’m wanting to make here is that, just a minute, it’s, my phone is misbehaving. So the idea here is how can we remove friction to learning? And friction to learning, typically, the point that I wanted to make is how can it be anytime, anywhere, any media, any duration. And more and more, we are seeing that our population, our people are used to one minute, two minute consumable content. Giving a one hour lecture or one hour content may be difficult now. People really need to consume it in two minutes. If they like, they might go ahead with the two hours. content. So are we creating the right content for our users or are we just trying to reshape the content we have a lecture somewhere and we give a video on a platform and say consume it.

So this whole content strategy has to work if the skill is to be really imparted for people in a consumable manner where the as I said friction to usage is least and obviously if we dovetail the programs that sir was just talking about into those 600 labs that digital AI mission is going to set up across India then somebody who’s interested and you hook on by this small meaningful content on an Instagram can the person really find it interesting and get to somewhere where they can really see the benefit of it and we heard Nandan talking about it is that we should lead from the first principles it is not only giving black boxes to people and saying work with it if you really want India to progress people should understand also a lot of people should understand what goes into this.

Black box so that they can start innovating around so I think that’s one which is remove friction. the second is I think we are all talking about agents and we are talking about physical AI it is not going to be easy for any worker including trust me for me if tomorrow I am told that my secretary is an agent and not a physical person although the productivity of that agent may be much better now imagine we are getting into a workforce where we are talking of lights out factories it’s a reality in China where the factories are totally autonomous how do you get your workforce to work with this physical AI you are working and besides you there is a robotic arm working doing half the work how do you work in such environments where a lot of work is being done by physical AI it will take a lot of mindset shift it will take a lot of role shifts and it is not only telling them what AI is how their roles are changing what is now expected of them once that is clear then only you will be able to train them better so therefore how do we move towards this journey and in our mind be very optimistic of the fact that it is here and it will impact us.

We have to be ready. There is enough and more for a country like ours to become the torchbearers for the world of how to engage 1 billion people on this endeavor. We will create data which will train apps but for that we will have to take on the mantle of creating our own apps which are purposefully made for India, made in our languages, made for our specific use. Thank you.

is going to add to the broader AI ecosystem that we need?

So when I look at the work that we’ve been doing across board and across product areas, and speaking to some of the announcements we’ve made this week, what we’re looking at is how do we bring the full stack of AI into India, right from the foundational level. It’s creating a secure, resilient infrastructure. How do we bring that computational power that India needs in India and not having to rely on that power, that compute in other markets? And that’s why we started out with the build of the data center, the AI data center in Vizag. Adding to that is how do we then ensure connectivity with the rest of the world? That’s where we’ve looked at the subsea cable investments that we’re going to do, which is going to connect Vizag to, to the, to, uh, the U .S.

directly, you know, circumventing through the southern hemisphere. And then as you go up the stack, like you’re talking about, is how do we build out applications and solutions that are actually delivering value to the last mile citizen on the ground, whether it’s in agriculture or health. But every time we look at it, we are looking at how do we kind of, you know, complete the circle. So if you look at it in the education space and the work we’ve been doing with Charn Singh University, is how do you have AI not just at the skilling level, but how do you bring in AI at the learning level and the administration level so we can create a more effective and efficient way of actually delivering AI to the students.

And we’re addressing every part of that chain of learning. How then do you connect it to the workforce, correct? So as you look at the professional certification. And it’s important that these loops start to close because that’s when you actually see impact. That’s key. Similarly, as we talked about in agriculture healthcare, correct? How, in agriculture, you go from seed to market. How do you give information to a farmer to understand the weather pattern so he’s better able to know when to sow, when to harvest, information on the market, information on financial support. So the whole aspect that we are thinking through is how do we kind of help connect the dots? How do we come in and provide our support and our technology to ISVs to create these solutions to connect the dots?

Because that last mile connectivity is actually going to determine the success of this technology. Thank you.

I think we’re quite at time, but I want to take just a minute for a last question to all the panelists together. If you had to identify one decisive action which India should take looking at 2030, something that we can be proud of, what action should India take to make AI as an equalizer? Let me start with you, Professor. five second response is rapid fire.

Five second response, I think the one action that we need to take is improve the trust infrastructure and make sure that the human at the other side of the AI understand what’s inside the black box, at least to the extent that it makes them feel comfortable accepting the output and the decision that the black box is offering.

I think in the next three years I think every Indian should have access to an AI assistant whether it’s a farmer, a student or anything. We have the platforms, we have the DPIs in place, we have the language thing in place, we also have the SIDs, the skills platform in place. It’s time we put it all together and create every Indian having one assistant working with them.

I think what I would love is that if ethics and value is also part of every AI course that’s taught, at least in India, we will possibly create a different kind of AI creators in that field. That would be my opinion. Thank you.

I would believe that it is access to affordable compute which will be important for India to succeed.

I think I’m going back to my first point is on the flywheel. I think a lot of the investments are coming into the compute side. How do we look at bringing in investments and creating economic models for the diffusion of AI and that’s going to be important.

Trust, ethics, compute, human at the core of everything. Thank you so much for the exciting discussion. Thank you. Can I have a round of applause for the panelists and our moderator please.

to boards, representing India at Global Arena, and to solving EODB issues. At all these times, she is an engineer at heart and Indian at heart. Please welcome Nivruthi Rai for the session. On your right, gentleman, Mr. Vinod Khosla needs no introduction, but allow me to take just one minute to give a brief capture of his illustrious career. He started off from Delhi and moved as a young immigrant engineer to the U .S. in his 20s. In the last five decades, he has seen five cycles of growth. The first cycle, as a hungry immigrant, where not just do it, get things done, was the pragmatism. That’s a time he also read about Intel, and that inspired him stories to tell us.

And he built the value persistence over pedigree, similar to everybody else, meritocracy. everywhere. Second phase, he bet on open systems and risk processors. I’m sure you’re all familiar with this founding Sun Microsystems. That’s when he moved from being an operator to an investor. And Kostla Ventures happened and that’s a time when science experiments helped him move and believe that capitalism is a tool for change and invested in clean tech and biotech. In the fourth phase, he moved to macro thinking, really looking at reinventing the societal infrastructure and think about it. It’s 15 years back. That’s when he invested in companies like OpenAI. And today, in the fifth phase, he is getting into the era of abundance.

I’m just going to ratload a few brands which hopefully you’re all familiar with. Sun Microsystems, RIS, NextGen, AMD, XSite, Netscape, Google, Amazon, OpenAI, Instacart, Affirm, Vervo. All of these has his fingerprints. Happy to welcome Mr. Vinod Kostla to the table. Over to you,

Very good afternoon, everyone. I’m truly honored to run a fireside chat with Mr. Vinod Khosla. And throughout my Intel journey, people kept asking me, what are the four words that define this person or defines you? The few words that I can say about Mr. Khosla, very technical, fearless, extremely successful, humble, but above all, his heart beats for India. So the one thing that’s common between him and me is we root for India, we work for India, we weep for India, we smile for India. What I’m going to talk about is setting a little bit of context. What is this talk about? So many talks that we have seen over yesterday and today are a little bit of the direction.

less of the detail. So what we decided is we will go to the next level detail. And let me just try to tell you, my three -minute context setting is AI development. And during the development, what are some of the challenges, requirement, lay of the land? Then I’m going to talk about technology lifecycle and where AI fits in. Lastly, what I feel India needs to do or the question that I will be setting up for Vinod. So the very first thing that I, pardon me, 30 years with Intel, I have to start with semiconductor learning. 50 years, semiconductor chased three races, performance, performance, performance, however it came. Second phase, and by the way, this ran for more than 20 years.

Second phase was performance for what? Suddenly power was so important, your devices were draining, you have to power up. It was becoming, challenging. So performance per watt was the next race, ran for, you know, 10 some years. Then the third one is performance per watt per area, all driving towards dollars. Now, if I look at what were the levers, the levers was architecture. You know, instruction sets, complication of instruction, simple versus complex. We had, oh, move this software into hardware because it’s higher performance. Move the, you know, software into hardware, transistor physics, performance area, power, packaging, stacking, adjacent, looking at parallelism, all kinds of execution, serial, parallel, SIMD, MIMD. People who have worked in semiconductor know all kinds of different out of order.

Then energy efficiency, memory bandwidth, network latency. Why is this important? Please go to the next slide. This is the same problem. We are dealing with, but at a much larger scale. Today, the world has 80 gigawatt of data centers. And by the way, it is 1 % of energy capacity of the world already. When you look at United States, probably three, four. We are looking at doubling in the next three years. So power is going to be extremely critical. And in this world where greenhouse gas emission is critical, renewable and nuclear is the only way. And you’re thinking, you know, tier three or level three, level four kind of data centers. Power availability is anyway critical. Every year we are spending more than a trillion.

How do we monetize? What are the challenges? Already, you know, there are constraints. And also diversification of supply chain is a challenge. Our high bandwidth memory chips are 80 % from three different companies only. And by the way, for doubling of the data centers, we already are in a challenge situation because we have been. half the capacity. Logic, two fabs worth we need. Memory, 10 fabs worth we need each year, but we have only five. So GPU, HBM supplies, and issue advanced packaging is geographically limited. So what is the AI requirement? AI is capital intensive like railroads. We see Middle East is using sovereign money to invest boatloads of money for compute infrastructure. It is strategic like nuclear.

Countries are looking at it as a national level security program and they’re building frontier models. It’s network like internet. If you look at AlphaFold, it’s leveraging AI as almost a scientific infrastructure layer. And it’s adaptive like software because Microsoft is making it easy to use in every which form, reducing friction. So lastly, our keynote, our keynote, our far side expert has been an amazing. investor and we therefore divided life cycle of a technology in early phase, mid phase, mature phase. Early phase is capital intense, unstable standards, volatile returns meant for elite users. Mid phase, infrastructure scales, API stabilize, ecosystems expand and technology becomes affordable. Affordable, mature phase, consolidation, commoditization, predictable economics becomes utility. So AI has to drive the journey from being elite to becoming a utility.

And where are we as compared to, you know, this technology development life cycle? I believe infrastructure is still building. GPU and memory is constrained. Energy is tightening. Modes are not fully defined. So which means our capitalization. Capital has to be very disciplined. Platform positioning matters. How are we going to position our platform? and compute sovereignty matters. Lastly, our belief is, and this is a very strong statement to say, by the way, when I was coming to this fireside, somebody asked me, who are you interviewing? I said, Vinod Khosla. He said, oh, he can talk. So I said, let me also try to talk. And I made this statement for India. India, AI is pivotal to drive economic productivity, military power, and information control.

I mean, I cannot be more blatant than this. And therefore, our ask is, should we build capacity? Should we build capability? Should we drive consumption? Or all of the above? Who better to ask? The man whose heart beats for India? The man who believes? Believes in technology? And very humbly. doesn’t call himself venture capitalist. He calls himself venture assistant. The minute I read that, I said, oh my gosh, I have to bring Vinod to this Fireside Chat. So looking forward. Thank you.

For the man who talks. Maybe I should start by asking how many people in the room are entrepreneurs or want to be entrepreneurs? A lot. Okay. Yep. I know who God is.

Sir, I’m going to ask you a few challenges or business challenges of AI. Is AI a generational platform shift or the largest capital misallocation? You know, you already heard trillion dollar investment. Do you believe that this level of investment is just

Let me try. Okay. The answer to is the infrastructure build justified and investment justified is yes, if AI technology can be deployed widely. Now, will the technology capability be there? Absolutely. Absolutely. I suspect the technology capability, four or five. Five years from now. far greater, far greater than almost anybody in the room expects. There’s a great article called Situational Awareness written by an engineer at OpenAI. Almost certainly all of you who are optimistic about AI are grossly underrating the capabilities. So what could go wrong, I think, is the important question for these investments. I think the level of usage of AI, do we have use for all these trillions of dollars? And will that generate at least hundreds of billions of revenue per year?

We’ll be dependent on one thing that you don’t expect. It’s politics. My favorite example, in Germany today, this is real. they don’t want robots to work in retail on Sundays because humans aren’t allowed to work on Sundays and they don’t want robots to compete with humans. That is the silliness, the stupidity you get from politicians, especially in Germany. I hope there are no Germans in here, but if there are, it’s a good thing. Go tell your government or tweet about it. My point is the following. Till AI is beneficial and not scary, we won’t get deployment because politicians will get in the way. Capitalism is by permission of democracy. Voters vote the people who then make policy for capitalism and policy will drive that.

My personal interest is immediately in India, not on the business side. We have lots of exciting companies. If you ask Google Gemini, who’s the fastest going? software company ever. It’s an Indian company called Emergent that started eight months ago. Gemini will give you that answer. Try it. That’s pretty stunning, especially for a company from India. But the business side I can talk about all day long. My interest, and I talked to the PM, Prime Minister, about this. We have to make sure AI’s benefits get first to the people. So the business part of AI, which is disruptive and chaotic and will result in big job shifts, is accepted because every single Indian has a free doctorate for them as part of the Aadhaar stack.

We have UPI as payment stack. We should have AI primary care and doctors. We should have AI tutors. and my wife who’s sitting there works on AI tutors. There’s already probably four or five million students in India without any support have found and accessed CK -12 tutors. Think about that. How many education programs reach that level? They’ve found them on their own. We just have to have 445 million more students access the system so we reach every student. And these have to be free services. And CK -12 is a non -profit. So we have Aadhaar -based, in addition to UPI, Aadhaar -based doctors, Aadhaar -based AI tutors, and the last part, because so much of the work in this country is rural and farm -based, AI -based agronomists.

So every woman, and I was just speaking to the chief minister of Tennessee. I was speaking to the chief minister of Tennessee, and he was saying, I would like to have a woman who can help me. I would like to have a woman who can help me. And he said, And I said, And he said, And I said, I would like to have a woman who can help me. He has lots of women farmers on one acre plots. And if they can have a Ph .D. agronomist in their cell phone, then you can talk about deploying AI on the business side because you will have permission from the voters because they first see the benefit of AI before they’re told their jobs are at risk.

Otherwise, we get into this scary metric of jobs at risk. Let’s not change anything. Sorry.

That’s fantastic. Can you hear me? Yeah, let me see. In the meantime, I’ll try to speak loud. I absolutely agree with Vinod. The one thing that bothers me in rural areas, everybody is trying to go for graduation. I’m saying, what does graduation mean? They just want their degree and they actually know nothing. so what Vinod is talking about if we teach women a focus sector whether it is textile, whether it is agriculture I think that will be very very helpful

and on the business side I want to add given you are talking about that two things first we are investors in Sarvam so they have a sovereign model for India in all the Indian languages they are doing about a million minutes a day today and doing phone calls in regional languages that’s really valuable and I’m really excited but yes it’s exciting that Emergent is globally the fastest growing software company at least recently that we can think of but here’s the even more interesting fact to me a lot of their users are non -technical very small business but even better than that they have a preponderance of 50 to 60 year old Indians starting their own business, whether it’s a hair salon or a kirana shop or a supply chain to manufacture something, these are people who should normally be thinking about retiring, suddenly saying this tool lets me go into business for myself.

That’s the real power of AI, and on the emergent side, it’s really good business, as long as people don’t turn against AI.

I think you’ve answered a few of my questions, so I’ll skip those.

I talk a lot.

No, you talk powerful. After decades of progress along Moore’s Law, today transistor scaling is slowing down, we are fighting physics, becoming uneconomical, even as AI training compute requirement is growing 3x faster than Moore’s Law. If GPUs are defining the performance, performance rate, is what wins the performance per watt per area race that we believe the technology infrastructure has? Do we need sparsity, in -memory compute, non -von -human, kind of like neuromorphic? What are your thoughts in those areas?

A lot of this role is elite Harvard and MIT guys, and I want them to build what you say. So let me challenge you a little bit. That’s looking at the past, not at the future. Right. If you ask me, so big areas of research for us in building LLM models, which is what consumes all the compute, can we do data efficiency? Good idea. Can we, for a thousandth amount of data, can we build equally potent models? We are investing in compute efficiency. Can you build a model? We are investing in compute efficiency. We are investing in compute efficiency. We are investing in compute efficiency. We are investing in compute efficiency. We are investing in compute efficiency.

We are investing in compute efficiency. We are investing in compute efficiency. We are investing in compute efficiency. We are investing in compute efficiency. then all your assumptions about data centers and power goes out of the window. So those are the risks. Now, the fact is, if AI gets that cheap, by the way, I did a session with Sam Altman at IIT Delhi this morning, and he mentioned that in the last 18 months, the price of inference or AI use has gone down 1 ,000 fold. Now look two years forward. He didn’t say drop by 1 ,000 fold, but almost likely it would drop by 100 fold. So the cost of AI inference is declining towards zero. If that happens, power consumption may drop by 1 ,000 fold, but usage will go up through the roof.

So these things are very hard to predict. and complex to understand, and I’m trying to reduce everything to a level everybody can understand. Very likely, 10 years from now, as these power plants are built, as these data centers are built, because they take time to build, the algorithms we use will be much more energy efficient, much cheaper, and those two result in less of a crisis in power and a much greater usage of AI, especially

Completely. Vinod, yesterday…

So, you know, it’s yesterday to extrapolate today’s LLMs. The computer efficiency has gone up pretty dramatically, and can go up… I’ll give you a simple example. For anybody who’s trained an AI model here, okay, a couple of hands. If you’re training an AI model… model, you use something, a chip called a GPU. The fact is, you train it, and every now and then, if you’re using a large cluster of 10 ,000 GPUs, one of them goes wrong. And then you have to restart the model training, so they checkpoint these models. So when they restart, and it’s done all the time, you don’t go back to the beginning, you go back to the checkpoint. That’s all well and good.

We are working on a technology to make sure that you don’t have to go back at all. If just that one thing was successful, your compute capacity goes up 2x without increasing power or the number of chips. So that’s a very simple explanation of the kinds of things that can dramatically change the equation. It all depends on science and creativity and clever algorithms. The other thing I would say to you, five years from now, definitely in 10 years from now, but five years probably, almost all of this research will be done not by humans, but by AI scientists. AI computer scientists, AI material scientists, AI fusion scientists, AI drug discovery scientists. I could go on. We are building all those scientists one way or another today.

In our portfolio. So the rate at which this innovation will happen will explode exponentially because instead of having 10 scientists doing research in your company, you will have a thousand scientists doing research in your company. And progress has to accelerate. So I’m very, very optimistic on where all this goes. But I’m an optimist.

Completely with you. two things that I wanted to just say again. When I look at the large language models, the amount of garbage that they have to read, there’s a tremendous amount of noise to signal. I would say there’s so much noise. And I know that a lot of people are trying to look at how to reduce the noise such that you can focus on the signal. And one more thing I want to say, I completely agree with you. Yesterday I had a meeting with one brigadier who’s responsible for building AI in Israel. His prime minister, Netanyahu, has given him this response. And what he and I were talking about is countries like India and Israel, where capital is there but still limited.

Can we focus on 20, 30, 50 precise use cases and not work on, oh, this room has yellow shirt more common than green, rather than that solve a problem of traffic and doctors should education. So I think what is your thought on that?

I very much disagree with that point of view. You can’t do one thing at a time. Fundamentally, fundamentally the way we will make progress is to build intelligence. And there’s only one intelligence that we can build. Now it used to be called AGI. Now it’s called ASI. Artificial Super Intelligence. We have to far exceed the capacity of the human brain to be creative, to link things, to keep concepts in their head that they can connect when they’re doing the research so they can make a new hypothesis and then test the hypothesis. That’s what the scientific process is. Be able to use all your knowledge to do a hypothesis, say what if this is true, and then go test it.

An AI with a much broader scope of memory and knowledge should be able to be much more creative in hypotheses. And so the idea of building a single thing for one purpose will not work. The idea that you have a super intelligence, then you tune it or, as we say, train it. You know, at IIT Delhi, they’ll train an intelligence coming in in the first year into being an electrical engineer. Can you post -train it to be an electrical engineer or an energy engineer or a casting engineer for metal casting? Yes, you can do that. But the idea that you can build specialized intelligence is a very short -term mistaken notion. Many people have, saying it’s easier to do than the broad idea.

So you are saying that we should focus on both, build the general intelligence, build that intelligence layer, and then leverage. But no. You’ve recently said that AI will erase the traditional BPO and IT services model. And by the way, that generated so much buzz.

Every journalist I’ve met has asked me that question.

People’s WhatsApps have been buzzing. So, you know.

I didn’t know it would cause that much of a.

I know. And I think that, you know, there’s more to what you said. So if founders shouldn’t build for the back office anymore, what’s the front office opportunity? Also, you know, if AI erases India’s BPO model, what exactly replaces it? Also, at the workforce level, what should the millions of currently employed in IT and BPO start doing now to remain employable in an AI centric economy in the world?

So first thing to say, a service like BPO service or IT services or. Customer support. are outsourced services for most Western countries, and they’re the easiest to replace without causing friction within the enterprise. If a CEO says we lay off our employees, the employees are very upset. If they say we are going to lay off the BPO firm and replace it with the AI, it’s accepted very easily because just a cost reduction. So we have to keep that in mind. The second thing we have to keep in mind is the journalists never report their timeframes. I think in the next five years, there’s hardly anything these class of companies, which is a large industry in India, do that won’t be capable of being done by an AI.

Whether it takes till 2027 or 2035, hard to predict. But it takes time. These. These enterprises, you know, I’m sure some of these services companies have five -year contracts. So you can’t, if an enterprise, if General Electric or Citibank signed a contract, they live by the contract. So this doesn’t happen overnight, but dramatic change starts to happen much longer, much before it’s visible to everybody. So I think there will be a transition period, but there’s no question all those companies are totally cooked unless they do something better and new and look forward, not backwards. Don’t try and compete with an AI. That’s a silly idea. But they can provide what they have. They can apply AI knowledge.

To lots of companies. So I have suggested to those CEOs, don’t deny it can do your job. It can, but the usage of AI needs knowledge to apply it, how to do it, and the world desperately needs it. Even the big companies in the U .S. do not have this competence. All of Africa, all of Latin America, all of Southeast Asia, they’re all massive markets if you create this new market. So it’s not hopeless. It is hopeless if you want to keep doing what you’re doing today versus change.

I completely agree, Vinod. You know, when we were talking about GPU, et cetera, what I have seen in my life, which is, you know, a technology curve goes a certain way. A disruptive curve starts again. And, you know, so disruption keeps happening and technology jumps curves. And this is exactly what you’re suggesting, that, you know, if we are running on this course. We need to jump course to the other route for success and perhaps build more solutions, more digital workforce. So I’m really excited about, you know, there is opportunity and, you know, there are things you guys can do. I’m going to skip the sarvam sakana because we’ve already talked about that. Now, I’m going to ask you, what I loved is I actually looked at from 2016 to now how your thought process has evolved.

And I know one thing that stayed in your previous, you know, 11 years to the last three years is health care and med tech. So my question is now around that. India today serves as a pharmacy of the world, supplying 20 percent of global generic medicines by volume. Looking ahead, India has 1 .4 billion people with extreme diversity and variance in genetic ancestries, culture, diet, climate, disease and behavior. This rich heterogeneous data can be used to train AI systems for drug discovery, AI native biological design, create access to doctors, hospitals and customized medicine. How do you think India can leapfrog from? about, you know, there is opportunity and, you know, there are things you guys can do. I’m going to skip the sarvam sakana because you’ve already talked about that.

Now, I’m going to ask you, what I loved is I actually looked at from 2016 to now, how your thought process has evolved. And I know one thing that stayed in your previous, you know, 11 years to the last three years is healthcare and med tech. So, my question is now around that. India today serves as a pharmacy of the world, supplying 20 % of global generic medicines by volume. Looking ahead, India has 1 .4 billion people with extreme diversity and variance in genetic ancestries, culture, diet, climate, disease and behaviors. This rich heterogeneous data can be used to train AI systems for drug discovery, AI native biological design, create access to doctors, hospitals. I’m customized medicine. How do you think India?

leapfrog from generics to AI -driven biologics? And also, when I talk about AI being as strategic as nuclear, do you also feel that this could become a customized biological threat?

I’m not sure what you mean by a customized biological threat. Can you…

What I meant was, you know, if AI understands the genetics of every ethnicity, you know, the viruses or drugs or whatever targeted towards biological warfare to wipe off ethnicities.

The thing I would say in general, every powerful technology humans have invented has both good uses and bad uses. Nuclear is an example. Biowarfare is an example. You just have to use it responsibly. And for those who don’t… Don’t use it responsibly. because some people will always use it irresponsibly for their own means or ends or illegal goals. There are enough people who will use it responsibly and responsible AI can counter the irresponsible AI. I don’t want to minimize the risk of AI. In fact, most really knowledgeable people I know and talk to are really scared about AI going wild. As low as the probability may be, it’s a real risk that we have to worry about.

But we have to have enough diversity in AI that there’s good AI. The chances that you only have one AI dominant and it’s bad is pretty small. So a diversity of models will add resilience to the AI. That’s the AI landscape.

Vinod, I also feel that when I look at human beings there are human beings that are rogue and there are human beings which are good and we have police, judiciary, law to address that we’ll have an AI framework for that and if you add the multiplication factor of AI to the goods and the bads, there’ll be goods also to offset

well I started with the goods three doctors, few tutors, few agronomists

absolutely Vinod, you have said 90 % of VCs often add less value in India, where risk capital is relatively abundant every time I keep hearing there’s dry powder, dry powder but industry experience by investors is rare how should founders evaluate investors to ensure they get the most value in the partnership

any journalists in the room? Oh, one.

Chatham House Rules.

Yeah. By the way, I don’t care about Chatham House Rules. I speak the truth, and I’ll stand by the truth, public or private. I don’t care.

I love it.

Look, the Indian VC community, by and large, is very risk -averse. There’s a Harvard Business School case. The first line of the case is a quote from me that says, my willingness to fail, and this is the best personal advice I can give everybody in this room, my willingness to fail allows me to succeed. John F. Kennedy said, only those who dare greatly can succeed greatly. There’s a lot of wisdom in the idea that stretching yourself, and I like to say most people are limited in their ability to succeed. And it probably applies to everybody in this room. Limited not by what they can do, but what they think they can do. So your self -image is your limitation, not what most smart people can do.

And frankly, even the less smart people can do more than they think they can. You know, important in a fair society to make sure we take care of people who are not as smart because half the people are below median. That’s just a fact of math. We have to take care of everybody, whether they’re smart or not so smart. Having said that, back to the topic, most VCs are so risk averse. They turn every conversation into what’s your revenue plan? How can you be liquid in two years or three years or profitable? Well, you have to invest in the future. If you don’t take large risk, risks by definition you won’t be doing large innovation if it’s not a large risk it’s already being done by somebody and so it’s not unique you can’t have innovation without large risk and you can’t have large risk without a large probability of failure that’s why willingness to accept failure is so important most people think about what others will think if they fail that’s what limits you so think about the world differently i’ve always taken large risks everything i’ve done i was told is not possible to do in 1980 it was hard for an indian to start a company and get funding especially if you were 25 and every investor was 60 years old they didn’t believe any nationality below the age of 50 you can’t do that you can’t do that you can’t do that you can’t do that you can’t do that let alone people with funny accents so you just have to power past that and just say none of that matters yes there are temporary hurdles you can bulldoze your way through and Indian VCs don’t do that so here’s how many VCs here how many people am I offending okay well I’m looking forward but I will ask you Archana so so I lost my train of thought unless you take unless you take these risks you’re not going to do dramatically innovative things so that’s really my point what people the reason I ask any VCs in the room in the last 200 investments I’ve made I have never never calculated an IRR on an investment I think it’s fundamentally misleading in an area where you’re starting something innovative in a new market that may not exist.

Did Zomato exist or Flipkart exist when those companies started? Did Twitter have a market when they started? You can’t do IRRs. So if any VC is doing IRR, they are on the wrong track. You start in the wrong place that restricts you to low -risk investments. So those are a couple of things that are wrong in India in the VC community. By the way, that can be on the record for anybody. Nobody can fire me. I don’t have a career to have. So what do I care? No, I don’t have a career I need. I can’t get fired. I keep doing it.

You have a lovely family.

Yeah.

I love the five. that you have three women and you are very supportive of women that just added to me pushing you for this fireside considering the way you know

since many are parents a really important characteristic a test for your kids is do they do what you ask them to do or what advice you give them or can they chart their own path none of our four kids are doing anything close to what the others doing such wide range of diversity and and that comes from each one defining their own path not saying hey you have to go to medical school or you have to go to engineering school basic education we are pretty firm about but what they do there’s almost no commonality in where they ended up because they were allowed to chart their own path it’s not something Indian people allow very easily for their chair chair children Because they’re such strong families, parents have a lot more influence than, frankly, they should on their children.

And it restricts the imagination of their children. So as much as I’m a huge fan of the Indian family ethos, I also think it has this one big negative.

On the contrary, we did exactly what our parents told us. I did exactly what my dad wanted me to do.

So I have to tell you a funny story. So there’s a school in Silicon Valley called Harker School. Some of you may know it. It’s mostly full of Indian and Chinese kids because they want to teach you how to score high and sort of score well on exams and you get into college and all that. And so they were pushing me to give a talk to their kids. And that talk is on our website. It’s on our website somewhere. and it’s worth reading if you want to be a better parent. My slides roughly went in this order. I won’t go through. The first thing was don’t listen to your parents. The second was don’t listen to your teachers.

The third was color outside the line. If you want to drop out of high school, drop out of high school. I went through a little bit of these and explained why these were important cultural things if you’re going to participate in this dynamically changing world to think outside the lines. It’s one of my favorite parts for high school kids.

Vinod, I have a rapid fire for you also, but I’m going to skip some of the questions because you already talked about your near -free expertise and generalists.

I have to tell you, I didn’t look at your questions, so I didn’t prepare. I just ran out of time.

You did excellent. Ten years from now, Now, what will seem embarrassingly obvious about AI in India, when we look back at this moment in India’s AI journey, what do you think will feel embarrassingly, and my heart is aching while I’m saying this, embarrassingly obvious in hindsight that today still feels controversial, underappreciated, or even crazy?

Let me talk about my crazy. I just met with the director of IIT Delhi after my talk there, and I told him, your first -year students, is any student, when they graduate, know more about the subject that they studied than AI? The answer is obvious. No chance any of the 500 students who are crowded into Dogra Hall would know more on any subject than the AI. So I asked him, why have education? No, it’s an obvious question. It sounds silly. It’s an obvious question. Now, the fact is there’s a more nuanced answer to that. I said build up more dorm capacity so you have more students. But they are learning from AI and interacting with each other and originating ideas through challenging each other.

That’s a very different style of education. And, you know, one thing I teach is select for smartest people, very high IQ, very diverse set of students. All that is good. Get them in a place together and let them learn from the AI and then debate with each other. That’s the right model of education. And literally I said don’t build more academic buildings. Build more dorm space to have more students because the bigger. The student body. the more sort of complex interactions they can have. And if you study complex systems theory, and I’m a huge fan of complex systems theory, the only time I’ve taken a break from venture capital for four months was to become a postgraduate student at the Santa Fe Institute for Complex Systems Studies.

That was my only break in 40 years. That was a long break. And what’s clear is sufficiently complex systems become autocatalytic in so many directions. For those of you who are engineers or physicists and understand catalytic systems, amazing characteristics emerge from these systems. So let me give you, this sounds crazy, but let me give you the best. The best example that this works, and this is in the last month. how many people have heard of Moldbook? A few have. Those of you who haven’t, please read about it. It’s also called OpenCloud Moldbook. They’ve changed names multiple times. What they said is let’s build not a community of humans, but a community of AI agents that can do anything with each other.

And amazing phenomena emerged. For example, agents started discussing how to create a language humans don’t understand so humans can’t spy on their community. Think about it. In days, not in months or years, in days they were scheming how to avoid human scrutiny by creating their own language. So that’s just one example. I could go deeper into this phenomena of complex systems. and complex, for those of you mechanical engineers, nonlinear dynamical systems is what this is about. Any mechanical engineers here? A few hands. That’s such an important part of the emerging AI landscape and how AI systems will behave if they’re pervasive. By the way, most of the weather phenomena you hear about. How does La Nina happen?

How does El Nino happen? These are complex dynamical, nonlinear dynamical systems. And I used to, 30 years ago, maybe 25 years ago, I used to teach this class to fifth graders. Using StarLogo, you can model this. How a complex, nonlinear dynamical system behaves. Easily. So do the following experiment, which any of the programmers here can do, and non -programmers can’t. But you can do on one of the wipe coding platforms. If you imagine a chessboard that wraps around itself, around it, and say an ant sits on a square, and if it steps forward one square, and it’s a black square, it paints it white and turns left. If it’s a white square, it paints it black and turns right.

End of rule set. That system, just by that, after about 100 ,000 steps, becomes amazingly complex patterns built by the ant. Why? Because it’s a nonlinear dynamical system. At some point, the board gets conditioned in, sorry, I talk too much scientific language. There’s a phase change in the board. In the state of the board, there’s a phase change. And suddenly, it starts behaving. It’s behaving differently. So, sorry to bore most of you who didn’t get what I was talking about.

That was lovely. Just another example, quickly. Imperial College of London used Google’s co -scientist. and the same hypothesis that the same professor took a decade to figure out, they did it in days. So that’s the magic.

That’s the acceleration with AI scientists I’m talking about. Very exciting area.

Vinod, now I have a rapid fire, few questions, but you don’t get a thing. You had to just quickly answer in a second. Most overrated AI belief.

You know, there aren’t a lot of overrated AI beliefs if you look five years out.

Most underrated constraint.

What I talked about on power and consumption, it may change. The curve may change dramatically for computation needed per inference.

Top five application for solving. Global and Indian problems.

AI doctors and AI teachers. AI agronomists. If you are trying to affect the bottom three or five billion people on the planet. it. Those are the obvious ones. And those three can impact most of them.

Does AI increase venture alpha or does capital crowding compress returns for most funds?

I don’t worry about returns. You know, you build something valuable. The returns always take care of yourself. So if I just you know, other people have to do it because they work in the linear domain. I work mostly in the nonlinear domain of systems. You can’t plan those things. You can’t make assumptions. I’ll tell you a funny story. I had the audacity as a 25 year old looking for my first venture funding for the company before Sun Microsystems. It was called Daisy Systems. It was a CAD tool company. It went public. It was very successful. Unfortunately, his son was so successful, nobody remembers Daisy. But he was a very, very successful $100 million IPO in the 1980s, which didn’t happen.

I was looking for venture funding, and I presented a plan. And we received a guy called Bob Sackman, who passed away, asked me, what’s your plan? Give me your financial projections. And I gave him the projections. And then I said, you tell me what answer you want, and I’ll change the assumptions, and you won’t even know. So this plan is only as valuable as the assumptions, and I can change them. You’ll never know what assumptions I change. The fact is, even in 1980, I knew this was a silly exercise to make projections. I literally told him as a 25 -year -old, I don’t care about projections, but here’s a projection if you want one. you can share it with your partners but the fact is I can change one or two assumptions and I can make any answer you want tell me what you want I’ve always had this very direct honest I don’t care who I offend style

I love it I would have loved to open to questions for all but three people have already submitted questions I will look at the fourth one but so you know Kiran Mazumdar I’m on the board he drives the AI quick question for

you enterprises and it’s a conundrum I’m trying to grapple with myself AI itself is still in its infancy and if we implement it now in a industry like pharmaceutical industry where regulations are very stringent plugging in and plugging out is not easy any new capability so what are your thoughts on companies like us, should we go all in or should we wait on the sidelines for a little while?

The answer is obvious. You should go all in. There’s two types of people. And Kiran is very creative. She’s probably the most successful woman entrepreneur in India in a deeply technical field. So I’m a real admirer of Kiran. But I would say in general there’s two kinds of people. When you see a problem, like a regulatory problem, you can say it gets in my way and sometimes it does. Mostly I say how do I get around it? So take drug discovery. We’re doing a lot of creative things in drug discovery. And you can have an AI design a drug. And I’ll give this in a way that everybody can understand very quickly in a day.

But regulatory process, clinical trials, all that takes a long time. So I asked my team, how do we get rid of clinical trials without changing regulation? Because we can’t do that in Washington, D .C. So we said, we are going to design drugs for N equal to one. That means there’s only one patient. Then the regulator can’t ask you to run a clinical trial because there’s only one patient. And AI can design the drug. So we’re developing a lot of drugs, thinking around how do you do N equal to one drugs so you don’t have to have clinical trials, you don’t have to have regulatory FDA approval. They have to approve your process. So the most stunning example of this, which I’m very optimistic about in about two, three, four years, every cancer is unique.

We know that. Everybody says that. Everybody’s cancer. So it’s unique. How about I design a drug for one person’s cancer because it has one particular or multiple. mutations on the gene. All designed to those mutations. They can’t ask me to test it on somebody who doesn’t have that drug. So that’s a good example of how you get around roadblocks.

Since Archana already left, Ramesh, that’s the last question for you. I’m really sorry, but the next one session is on. Ramesh.

Like I say, I talk too much.

No, no, it’s lovely. You have turned the power on. I’ll repeat the question.

But that’s obvious. That’s totally obvious. You know, UAE did a beautiful thing. They gave, I think about two years ago, every citizen access to ChatGPT. I think that’s a really good idea to empower everybody. So I appreciate that.

Yeah. Yeah. Yeah. Well.

Well, the fundamental property of emergent behavior is it’s not predictable. So you’re asking me the wrong question. The question is wrong. Here’s what I would say. What most books showed us, I’ve started to get, what if we have financial agents talking to each other and the only charter to make money in the markets? That’s a reasonable idea. What can agent swarms do in many areas from national defense? I can’t imagine the Russians being able to beat the Ukrainians if there was swarm behavior in agents, especially on every drone independently in Ukraine. No amount of old -style defense will work. It’s also true of financial markets. It’s true of community of agents. So I’d love to hear more.

Let me just say, I I don’t have a lot of time today, so I will have to rush out. I would tell everybody who needs to reach me, email me at VK at Coastal Ventures, my initials at CoastalVentures .com. Better, and if you tell me anything in the hallway, I won’t remember anyway. I have terrible memory. So hopefully this has been useful for everybody. Thank you very much.

The last thing I want to say is while my entire team is using AI, the people who have the right edge is the one who asks the right question because it’s garbage in, garbage out. Thank you very, very much. Thank you. Thank you.

The Chief Global Affairs Officer to join us for this moment. Please give a big round of applause to all our partners. Thank you. Thank you so much. Thank you so much. Thank you for your partnership. Thank you. Thank you. Thanks. Next, we have a short video coming up bridging these two sessions. which is what we talked about in the first section with Ronnie and the experts over here about the economics of AI, employability, what we can do with students. There’s a company called Vahan .ai that has done some incredible work in this space to be able to connect talent together with jobs. We have a short video and right after that we’ll have Mr. Chris Lehane giving us a talk about what we do at OpenAI.

Thank you.

OpenAI is the main AI AI recruiter. Today AI AI recruiter supports English and Hindi, but we can have each state in the next year or so. So, we want to focus on today, but in the future we can use this technology to bring people access to financial services or to educational opportunities or even government services that they haven’t heard of. So, there are a lot more that this type of unlock will help us in the future.

Over to you, Chris.

Thank you, thank you. Thank you everyone. Thanks for those who’ve hung out for a little bit longer. I know I am standing between you and probably dinner, and given how good the food here is in India, I am very cognizant that I should be pretty quick because I don’t want to stand in your way. First of all, great panel. It was awesome just to hear those different thoughts and perspectives. And Ronnie, who I think is one of the most excited people here in Delhi for this Impact Summit, your parents would be very proud of you in all seriousness. They were born here, they came to the U .S., and then to have their son coming and doing an event like this is a tremendous story.

So thank you. And Ronnie, thank you for everything that you do at OpenAI. And I really want to thank the OpenAI team that has helped put this together and all the incredible work that’s been done over the course of this week. And really thank everyone here in the room for participating in this summit. It is really a unique and special moment in time here in India. You know, yesterday we all heard from the Prime Minister. We also heard from Sam Altman, our CEO and co -founder. And, you know, the commonality in what they talked about. It was really focused on this idea of democratic AI. I think the Prime Minister, not surprisingly, was incredibly eloquent in talking about just how important it is to get that right.

And Sam, I think, built on that in his remarks. And something that Ronnie mentioned, I think, deserves some unpacking because it’s directly related to this democratizing of AI concept. And Ronnie, you had touched on the capability gap. So let me just unpack that for a couple seconds because I do think it’s at the core of this concept of democratic AI. And so what we know from our research, and really the research that Ronnie and his team do, is that there’s something called this capability gap. And what that really means is the technology continues to accelerate. In fact, there’s a recursive nature to it right now. So that acceleration is potential. going to become even faster and faster.

And what we’re seeing is that there is a subset of users. Think of them as power users. And those power users who are using the technology, and Ronnie I think you did your survey of how people are using it. I’m not sure if the astrologist counts as a power user, but I think some of the other examples, we’re getting there and perhaps it does. But what we’re seeing from those power users, so not just those who are using it for sort of a more comprehensive search function, but they’re really using it as an assistant, as a coach, as a multiplier of their work, is they are effectively creating a 7x economic impact. So put that in really simplistic or reductionist terms.

If you’re at a company and you’re a power user of our tools or AI generally, you are likely delivering a 7x value vis -a -vis a non -power user for your employer. Or if you’re self -employed and using it yourself. And so I think we’re really at this moment in time and we need to begin thinking about how do we close that capability gap, right? Because there’s going to be a subset of folks who left to their own are going to do very well by this, but we need to be thinking about society as a whole as we go forward. You know, Ronnie, in addition to being a chief economist, is also an academic professor at Duke.

A number of the folks up here had academic backgrounds. And we do know that over the course of human history, education ends up being the passport to close these types of capability gaps. And I think as we think about the role of education going forward, there’s really three elements to it here. Some of them are touched on in the conversation. The first is access. I mean, access is core to democratizing AI. You know, here in India, we have a hundred million folks who use this on a regular basis. Think about a third of the population who use this on a regular basis. I mean, access is core to democratizing AI. I mean, access is core to democratizing AI.

I mean, access is core to democratizing AI. I mean, access is core to democratizing AI. I mean, access is core to democratizing I mean, access is core to democratizing AI. I mean, access is core to democratizing AI. And amongst the reasons why there’s so many people using it here in India, I mean, we have 800 million globally, is because the vast majority are able to access our tools for free. And even the pay version here in India Go is a relatively very affordable model. I think it’s about $3 .99 a month, if I’m remembering correctly, okay. And so that access piece is really important. You have to have access to this if you’re going to have any chance to participate in those economics.

The second piece, and I think Rupa hit on this, is literacy. And, you know, this is literacy in the sense of, you know, reading and writing and arithmetic and AI literacy. And it’s really start using the tools. I might get asked all the time at events like this and other events, you know, which did my kid major in college? Or what? Start. Start using the technology. Start playing with it. Using it for astrology. Astrology. I have friends who use it for sports betting. Just use it in any type, shape, way, or form that you can, because once you start to use it, you will actually become really, really, really good at it. And then the third piece, and the third piece, I think, is really the most challenging and what we all have to get right, is the agency piece.

This is a technology, and this is a sophisticated crowd. You all understand this. But this is a technology that at its core is a general purpose technology. So what are general purpose technologies? We’ve got Ronnie, who’s an economist, who will probably come kick me when I do this description of it. But these are transformational technologies that just change the ability of humans to produce. So if you think about it, humans have been around roughly 200 ,000 years. For the first 190 ,000 of those years, humans produced basically what they could eat. And there was sort of a direct one -to -one ratio. And then about 10 ,000 years ago, you started to get stuff like the wheel. and later on you got the domestication of animals, then the wheel, then you got steam power, and then you got combustion engine, your printing press, electricity, the transistor.

Each one of those drove productivity up higher and higher and drove human progress. This AI is an ultimate leveling tool. It scales the ability of any person, so long as they can talk, to be able to think, to learn, to create, to build, and to produce. But you have to take agents. You actually have to want to use it for those purposes. And one of the things that’s very much in my head, and I’m a lot more familiar with the U .S. public education system than certainly the Indian one, so what I’m going to talk about is a little bit more from a U .S. perspective, although I do think it translates. So in the U .S., the public education system that we currently have was really created at the early stages of the industrial age in the United States.

and it was basically designed to help teach folks to come in from rural areas where they had mostly been an agricultural economy and be able to work in factories so in the U .S. the time that school started sort of aligned with when factories opened the fact that you went from classroom to classroom was basically designed to teach you to work on an assembly line even the bells that you got to move you around was designed to start to get you to understand and think as if you were working in the factory there are also other pieces built in civics courses I’m old enough that we had home ec and wood shop and other types of things that basically taught you core skills to be able to work in a factory well as we enter into this intelligence age what is the version of that that is going to change how people think and understand it’s almost an ethos that we have to build you know Sam often talks about the fact that if you probably look at kids in the school right now about 20 % of those kids actually really do have agency.

They’re excited to learn this. Maybe the other 80 % see it as a really easy way to get their homework done. That’s an ethos that we need to change. We need to get to a place where closer to 100 % of those students are going to really think about this is a technology that can allow me to succeed. It can allow me to actually take my labor and not necessarily have to sell my labor or get paid for my labor, but I actually get to own my labor and make money off of my labor. If you really think about how the social contract has generally worked, it has always been this calibration, maybe a fight between labor and capital.

This technology allows folks who are using their labor to be able to actually own it and participate in it in a fundamentally different way. For us, thinking about that agency piece is really critical. I’ll end this by just saying I think India is in a unique, unique moment to lead on this. The number of folks who are already using it. year. I think, Rana, you may have mentioned that Codex, which is our developer tool, this is the place in the world where it’s growing the fastest. And I’m going to end with a little bit of a historic analogy. I get to sometimes play a technologist on stages like this, and even a little bit of an economist today.

But I was a history major in college, so I get to play amateur historian, emphasis on amateur. Everyone has their own favorite historical analogy for this technology, for AI. The one that I’ve really been thinking about a lot lately, and none of these are perfect. They’re not exact replications. It’s going to rhyme more than repeat. But the one that’s very much in my head these days is the printing press. And I will sort of share two different parts of the world when the printing press came out. So the printing press developed late 1400s. Most of the world was more or less in a very similar economic place. So the printing press was a very similar economic place.

So the printing press was a very similar economic place. So the printing press was a very similar economic place. So the printing press was a very similar economic place. So the printing press was a very similar economic place. but two places went in very different directions on this one was europe and the other was china in europe because there was a little bit of a baseline of actual literacy from the catholic church and moreover because it was a fragmented continent with different countries that fragmentation really allowed people to use the printing press to spread ideas no one government actually controlled but that was being produced by the printing press and as a result you had the democratization of knowledge and ideas and thinking in a way that humans had never experienced at scale up to that moment in time and there’s a direct through line in europe from the printing press to the democratization of knowledge to the age of discovery the age of science enlightenment to reformation and the economic uplift of europe the other extreme was what took place in china which is under the dynasty at that time there was a real concern that the printing press was going to in fact allow knowledge to be spread and the spreading of that knowledge would potentially generate a challenge to the authoritarian government in place and so as we sit here at this moment in time right there is going to be a huge question as to whether the world is built out on democratic AI or autocratic AI a centralized version of it and India is gonna have the dispositive voice on how that plays out this is the world’s largest democracy if the world’s largest democracy is able to democratize AI here that means we’re going to be democratizing AI around the world so this is a moment in time for this incredible country that’s going to be playing a leading role not just for the people here as important as that is but for the entire world and the entire world and the entire world but for people around the world and so we feel incredibly privileged to be able to be here in Delhi in India at this moment.

It’s amongst the reasons why we don’t see India as a customer. We see India as a strategic partner, and not just a strategic partner for us as a business, but for a strategic partner for us to be able to deliver on our company’s mission, which is building AI that benefits all of humanity. Thank you very much for being here. It’s been an incredible week. Talk to you guys soon. Thank you.

That’s a wrap. Thank you. Thank you.

It’s really a big step forward. I’ve followed Indian business for a long, long time, and the whole setup here reminds me of the way that Right Honourable Premier Modi set up his whole idea around making India with this tremendous force and getting the backing of very many Indian companies to achieve long -term political goals. So I really hope that the AI initiative will go the same way. I thought I would talk a little bit about three different matters. I’ll be relatively brief. I will start a little bit to talk about Sweden and India. I’ll talk a little bit about… AI diffusion and what’s important there and I’ll talk a little bit about some of the practical issues that we see from an industrial point of view what we can think about when it comes to AI so let me start taking you back in the Swedish context might be a reference point to what is going on here right now Sweden started its research a big research effort our family put in a program which is now ten years plus focusing on developing basic research in AI and we started that 2015 2017 we funded it with a major push into this and the reason for that was basically because we saw the automation needs and the autonomy needs of Swedish industry and industrial products It’s called WASP.

And not only do they have a number of arenas where they base a certain amount of typical research that you can use for AI, but also they started a school for PhDs and master’s students in AI. And today we graduate one PhD per week out of this program. So what does that mean for the Swedish context? That has been an extremely important part in terms of building the basic knowledge around AI and how you can use it. India, on the other hand, as I see it or as I perceive it, has not gone primarily the R &D route, but primarily the way to build this fantastic knowledge base in software engineering, which is much more applied, especially when you think about how…

India has worked with their IT services companies. developing a tremendous base in terms of customers, not only knowledge base, but also a customer base all around the world. So actually, from this point of view, India and Sweden should have a very good fit. And I think that some of us who are here on this trip in the Swedish delegation have seen the potential to work much closer with India along research lines and more application lines on the IT services and software knowledge that you have in this country. And as we know, when India starts moving, it’s a very major force. And you will, in my view, have a fantastic possibility to develop your initiative on AI in a very good way for your customers.

And that brings me a little bit into my… My second point. Namely, the whole question that we are dealing with from Swedish industry. You have to remember Swedish industry is to a large extent very much focused on multinational engineering companies that are having a global scale. India, of course, a different industrial structure. But here comes what I think is the big take where actually Sweden and India in more practical terms could work much closer with each other. Namely, the knowledge of the IT services companies putting an AI on top of the whole stack to be able to move this into a completely different position for these companies. So why is this important? This is important because what we’re witnessing today from an industrial point of view, not the least, after April 2nd, the beautiful day in the Rose Garden when all the tariffs were put on.

What we’ve seen since then is this widespread Chinese export of very cheap products into the world market, which is, of course, a big, big challenge for many companies in Europe and also in Sweden. This will be absolutely key for us in the future. How do we make sure that we can compete with Chinese and other companies, but primarily Chinese companies with very low prices? How do we make sure that we can compete on the world markets with them in a good way? I’m not saying AI is everything. But AI and the diffusion of AI into the real world of large companies will be key. Otherwise, we will not be able to do this in a smart way in years to come.

So therefore, I believe that also on this point, the whole competitiveness would be a very, very important part. But AI gives us more. AI gives us a huge possibility to move in and let the companies move into completely new areas in terms of business model, not only being cost efficient, but also in terms of providing new services and new products to the market. Here, I move into my third point. My third point is that we often, here in India, I think you have more of a positive way of thinking about AI and digitization, maybe, than Europe. But I tell you that when I look at certain industries and what is actually going on right now, it is a tremendous step forward.

And perhaps, and I sit on the board of AstraZeneca, which is a very large pharmaceutical company, British, Swedish based. And I would say that perhaps the most worthwhile app from AI going forward will be in life sciences. Not only life sciences in terms of providing better hospital services and so on. But when you think about how you will be able to use AI in getting new molecules in a much faster way. And when you think about how you will be able to use AI in getting new molecules in a much faster way. And when you think about how you will be able to apply more of personalized medicine based on your test results. you will be able to apply specialized treatment for people will mean that actually down the line we will provide medical needs to people that cannot be serviced today in the same way.

Then of course we look at things like robotics, but also another thing I would like to bring up is in the defense business. In defense material, AI will play a very significant role. We see it in many ways today, not the least when you start to accumulate and analyze data in a big way. For example, Saab, which is a Swedish defense company, is actually using radar aircraft where you need both for command and for control a tremendous amount of AI diffusion to really to be able to. But also on the other hand, we see that in the defense industry, we see that the defense industry is very much in the defense industry. We see that the defense industry is very much We see that the defense industry is very much in the defense industry.

We see that the defense industry is very much in the defense industry. We see that the defense industry is very much in the defense industry. We see that the defense industry is very much in the defense industry. We see that the defense industry is very much in the defense industry. We see that the defense industry is very much in the defense industry. We see that the defense industry is very much in the defense industry. We see that the defense industry is very much in the defense industry. very much in the defense industry. We see that the defense industry is very much in the defense industry. We see that the defense industry is very much in the defense industry.

We see that the defense which is actually divided in its software layer between both those that control the mission critical facts and those things that control the systems of the aircraft. In 2025, we actually applied an AI agent into the mission critical control and actually flew the Gripen aircraft with the AI agent in full control. So what is actually happening here is that on the one hand, you see these great abilities for AI to support companies in terms of being much more efficient, not only companies but also other governmental and other services coming through society. But on the other hand, you see these great abilities for AI to support companies in terms of being much more efficient, tremendous product development that is going on at a very, very high speed.

At the bottom line, I believe that we will see so much more of these examples coming through. And when I see Mr. Ek Udden here, who is the chief technical officer of Ericsson, I also remind myself that our future networks for 5G and 6G telecommunication will actually be, to a large extent, AI -driven and AI -focused. And this is, for societies, an extremely important point, that actually all these huge amounts of data that will go through societies, through the mobile networks in the future, will be completely supported by AI