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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.

curious how it works and I think that a lot of kids are. I would love to learn how it can be used in everyday life and how it can be used as an accurate source of information. AI is like taxes, it’s unavoidable and if you don’t learn to evolve with it you’re gonna be left behind. I definitely want to be a part of solving big problems. We need to have a say in AI policies because AI literacy is really important. Thanks for finally asking us what we think. Bye.

He breaks me every time. These were children that we brought into a school in California in December. actors in there. There’s just a lot of children with opinions and the little boy at the end, he just had a lot to say. He is very wise. But these are, those were the views of just some smart, inspiring young people. They’re not just eager to use AI, but I think you can see they’re especially eager to understand and to build things with it. And just as you saw, they have some really clear ideas about how it should and shouldn’t be used in today’s classrooms. But of course, you know, excitement and confidence are not the same as mastery or comprehension.

We do see an unfortunate trend where children do not understand the fundamentals of the systems they’re interacting with. And I think you can particularly see that in younger children who often see generative AI systems. As a kind of magic box that they can… into where you know you type in a text or a question and then outcome images and videos and entertaining things and maybe even the answer to a history essay question I think we need to be really clear that AI is not magic it’s not a magic toolbox it’s a technology system and foundational AI literacy isn’t about teaching children how to use this magic box I think far more importantly it’s like how do we give the child the screwdriver to take that box apart and really understand what’s going on under the cover so while you know supporting children to use AI tools safely ethically and effectively today is important I think far more it’s about equipping them with the knowledge and the tools the confidence to build what is yet to come So therefore our definition of AI literacy when we talk about it, it’s about understanding today’s technology, yes, but it’s far more about understanding the fundamental concepts so that you are armed and ready for what is yet to be designed, and actually so that you can be the designer of what is to come.

So I think that we have underestimated the role we have to play in preparing children today. We don’t want them to be passive consumers of AI. Instead, we really believe that we should be arming them with the tools, the literacies that are required to lead, to design, to create. And our goal is not about sort of robot -proofing our children for what’s coming at them, but just making sure that they are ready to build a better future and they’ve got the tools in their hands. So let’s talk about AI literacy as understanding the foundations of AI. So AI is the foundation of computer science and AI concepts, and that is about understanding the fundamental concepts of AI.

understanding probability, how computers sort of sense the world as data points and data sensors, sensing algorithmic bias and understanding all of the nuances of that. We don’t want that to be an elective or selective choice for just the few. We believe that these concepts have to be elevated to the status of modern literacy alongside maths and reading, problem solving, creativity and collaboration. And I think it’s best if we show you how we plan to do this in classrooms. So I’m going to hand over to Atish, and we’re going to run a live demo, which is always fun at a conference event.

Great, thanks, Tom. And I’m also delighted to introduce AI Dancer, who’s on the table here, who hopefully will do some dancing soon as well. So, yeah, very excited to share. I’m going to share a bit more about how we’ve translated some of these principles that Tom was talking about into the product. So I’m here. excited to shout about our new computer science and AI product which is just fresh off the press which we just announced in January and will hit schools in April but all of this we need to do this very responsibly we saw this kid earlier in the video talk about AI should be safe fair transparent so this is very wise kid right so we really agree at Lego education we’ve established clear guidelines for how this should work so let me step you through some of these guidelines so AI should be safe we do not generate any text or any media we do not anthropomorphize I got that right this time it’s just a fancy way of saying we do not make it think that AI is human we do not want them forming any unhealthy emotional bonds we we ensure that all our digital products are rooted in the principles of universal design of design principles and we are designed to for kids who have neurodiversity we’re designing for kids who have different learning needs so it’s really important that our products are designed in a very fair way transparent all the models that we would would use would which should have very clear data provenance so should understand where the data has come from which has trained those models and understand whether the models have been trained on different geographies on different kinds of kids on different kinds of adults so ensuring that these models have clear data provenance is super critical for us and then finally privacy so I just want to stress that in all our products AI features run locally on the devices nothing ever leaves the device nothing ever goes to us at the Lego group nothing goes to third parties no login is collected there’s in terms of the trading whether the kids are building their own AI models or they’re using pre -existing models nothing ever leaves so safety and student well -being is a red line is a non -negotiable for us so everything we know about decades of education research and the way we use AI is very important to us and I think that’s what we need to show us that kids look best when they are building when they’re using their hands and really creating and we do and we’ve seen this very much at like education and through years of research so now more than ever children need to learn and need to learn together so much of computer science and AI today is stores with kids sitting in front of the screen with the headphones on by themselves learning and I don’t think we see this as a vision for learning for us kids should be building together coding together experimenting together tinkering together and sharing together so that is really our vision of how kids should be learning computer science and AI so when they tackle these when they tackle these new technologies they also have those cross -cutting skills to also deal with us in the real world so bringing this all together at Lego education we have these four values that govern our approach to AI literacy so we prioritize child agency and engagement to ensure students are active participants in their own learning journeys we empower students with the foundations of AI that Tom was talking about that remain relevant as the technology evolves.

We uphold child safety and well -being as it’s non -negotiable for every AI interaction in the class and we foster hands -on immersive and collaborative experiences that inspire creativity and shared learning. So that is really the four principles that are driving all of this. So how do we make this, how do we bring this into a classroom? How do we, with our products, how do we make sure it’s hands -on, it’s understandable and safe for kids? So I would encourage you also after the session to go to the booth, I think it’s in Hall 3, and actually see these products in person, get hands -on with them, try them out yourself. So we’re really helping students to build real AI literacy by demystifying how AI works.

Through these playful features and lessons, learners explore concepts like computer vision, probability ballistic thinking, classification, machine learning, while seeing their ideas come to life. The result is student agency. Kids not just using AI but actually understanding and building with it. So what better way to show you how kids are using it than for me to try to actually make you use it. So here we have a lesson which is about teaching kids about pre -trained classifiers. So this is in the last unit of once they’ve gone to some core principles of computer science they’ve learned about basics and events and loops and data structures. So at the end they are looking at AI and data and here they’re learning about how you can use a pre -trained classifier, the model that already exists, to bring their AI down to life.

One thing you’ll notice here when the code is up here that the camera that they can use, the camera by default is off. So this is all. sort of in line with the principles of AI safety so it’s an explicit action the kids are taking and here when I hit play now okay I’ve got that’s why I have a video okay no worries so what I’m gonna do always fun trying to do a live demo we always have a backup so yeah you can see that as I’m lifting my hands up and down you you’re seeing the different probabilities changing here and what the kids are learning through this is that with traditional computer science you’ve got zeros and ones things can be on and off with AI what they’re learning here is there’s a 80 70 90 percent chance that I’ve lifted my left hand up or my right hand up or both hands up and then that’s triggering the different events so they’ve learned about events in earlier lessons and that’s what I’m talking about triggering those.

So they learn that AI is not always right. They’re learning that the more data that’s trained into the model, the better it gets. And they also learn from an ethics perspective that if the AI model is not trained with enough kids’ examples, it will have biases in it as well. So these are very core principles of AI, but taught in a very simple and playful way and making the AI dancer come to life. So

Ready to excite your students with computer science and AI? This lesson is called Strike a Pose. Students will learn how to customize an AI classifier and program AI -activated events. We’ll kick off with a big question to spark curiosity. How could you train a robot to follow your movements? We will explore the topic through the computer science concepts AI and data. The question is tied to a real -life example, how AI can be trained to recognize images through data. This makes it more relatable to both students and teachers. In groups of four, each student picks a minifigure, which indicates their roles in the collaborative building process. The group will build a robot with movable arms and discuss how it might work.

Then it’s time to get hands -on with coding. Groups will open Lego Education Coding Canvas, enter the lesson pin, and connect their hardware. Students create and train their own AI custom classifier by posing in front of the camera and capturing pose data. With simple pre -made code and their classifier, groups explore making the robot mimic their arm poses. Group members take turns so everyone gets hands -on. Two students develop the build of the robot. While the other two iterate on their code and later they swap. Students present their robot, talk about their iteration process, and discuss how they created and trained their class. At the end of this lesson, students will be able to say, I can create a custom classifier.

I can use PoseData to train a custom classifier. I can describe how to create a custom classifier and use data to train it. This is the third of four lessons in the AI and Data unit, where students explore how computers learn from data. In the following lessons, students investigate how data quality and quantity can improve how their AI detects their poses. At the end, they apply what they’ve learned through an open -ended design challenge. All materials for this lesson can be found on the LEGO Education Teacher Portal lesson plan, ready -to -use classroom presentation and facilitation notes. No extra. No extra prep time needed.

So you got to see how AI model is really used, how the AI dance is really used in the classroom and what you saw also in the classroom there were kids meaningful roles in the building process as they were building out the model but also meaningful roles when they’re coding and also training the AI as well. And all of this also for the kids but none of this can happen without teachers, right? So we cannot simply drop new standards and mandates on educators without the support for them. You saw in the video briefly referenced the teacher portal where the teachers get all the resources and the support they need to bring computer science and AI to kids.

We know that most teachers who are teaching computer science are actually not computer science teachers themselves. They are teaching math, they’re teaching science, they’re teaching English and so they need to be prepared to really scale this up as well. So we really see this not as a problem. It’s not as a challenge in terms of access to tools but an access to confidence. So I think this is a nice, there’s a couple of very nice quotes here but I’m also, it’s a nice quote. I just wanted to hand over to Richa. I’m very pleased to hand over to her, who leads product development on the retail side and is behind the super exciting Smartbricks, if you’ve seen those.

Thanks, Steve. Hi, everyone, good morning. Thank you for having me. So, my name is Richa Menke. I head up interactive play at the LEGO Group. So, we’ve just heard an important call to action in terms of AI literacy. So, preparing children to understand and navigate an AI -powered world. And this matters enormously. But what I’d like to do is spend a few minutes discussing the other side of this question, which is, how do we prepare AI for kids and imagination? And part of the reason we’re here is that we believe our focus on play and imagination not only unlocks exciting new play experiences, it might just be the unlock to a more inclusive and empowering future of AI.

So, childhood, as we know, is formative. it’s not a market opportunity, it’s a developmental window that closes. What enters that window shapes who we become. Our sense of confidence, our curiosity, our relationship with struggle and creation, and very importantly, that shaping can often be invisible. So this is very important to us in what we do in the Creative Play Lab, which is the innovation team at the LEGO Group. So what we do is we look at how do we create more and more relevant play experiences for kids, how do we employ new technologies in service of better play for kids, but always keeping in mind our DNA as the LEGO Group, that hands -on, minds -on play experience that we all love.

So eight years ago, our team asked the question, in a world of digital screens, how could we offer kids, more interactivity in their LEGO play experiences, but without… screen. And we were really, really committed to this and spent eight years getting there. And we just launched in January, the SmartPlay platform, which is a new dimension of Lego play. What this is, is, you know, as the child is playing with the SmartBreak in their models, the play actually responds with appropriate sounds and behaviors. So imagine you have your Star Wars X -Wing, and you know, the way you move it around, you know, if you fly with it, it’ll swoosh, if you drop it, it’ll make a crash sound.

So, you know, it’s really responsive to the kid. And all of this without a screen. Without a screen. That was very, very important to us. And also without AI. And we just, we didn’t need AI in this solution. But, you know, also, we’re not entirely sure if AI is ready for childhood. We really believe that childhood deserves deliberation. And that deliberation might be an unlock, as I mentioned, to the future of AI. So first of all, AI holds tremendous potential when you think about play. When you think of the creative barriers that kids face in play. So for example, I’m sitting with my brick bin, I have a ton of bricks. I don’t know where to start, this fear of blank canvas.

AI could easily offer little prompts that inspire me to play. It could support diverse learning methods. AI could help us better understand a child’s intent so we could offer more better, relevant, meaningful experiences. And one of my favorite aspects, which I think is super interesting, is that generative AI is probabilistic. And in other contexts, like productivity, a hallucination is a bug. But when it comes to play, maybe that hallucination is just a playful feature. So there’s huge potential in what AI could bring to offer better play. But of course, as you know, there are many challenges that need to be addressed. And there’s three… key tensions that we think are really important to address when we think about kids and childhood.

So first of all, it’s this tension between efficiency and imagination. If I can get an answer just like this, I don’t have to wait. I don’t have to struggle. I don’t have to develop my imagination. And does that rob kids of the opportunity to really develop their imagination and more importantly, develop the confidence in their own imagination? Personalization and identity. A child at seven is not the same as who they’re going to be at 17. So if we start personalizing the experience for who they are at seven, are we holding them back? And then finally, assistance and agency. Are we raising kids who are, it’s very easy for them to prompt, but they don’t have the ability to really persevere through.

So if I can get an answer just like this, I don’t have to wait. I don’t have to struggle. These are some of the key tensions that we see. And of course, there’s a lot of opportunities, but we feel the responsibility. to ensure that these are addressed. So when we develop new play experiences, we ask ourselves the question, does this increase or decrease the choices that a child has? So child agency. Does this expand imagination? I’d encourage you to ask yourself the question as you develop AI solutions. Does it preserve that healthy developmental friction where you have to actually think, and finally, just would I want this shaping my child inner voice as a way to really think about what’s right?

And I’d love to leave you with this question that we spend a lot of time thinking about is, as we look at AI systems today, what exactly are we optimizing for and how important that choice is? So if today AI systems, if we optimize for engagement, what we’re going to get is more attention. But what if, what if… If we optimize for childhood, then we’re going to optimize for potential. Thank you very much.

All right. Good morning, everybody. I’m Sadhna Pandey, and I’m the chief of education at UNICEF India. And it’s a pleasure to moderate today’s panel discussion on AI literacy and children. So we’ve heard a lot at the summit about the wonder of tech. It really feels good to talk about the wonder of children and of education. So I want to thank Legol for creating the space for this discussion. We all know that AI has brought a step change in how we live, work, and play. And there’s no doubt that it is impacting children’s lives and how they experience education. The problem is that AI is not just a tool for education. The problem is that it is doing it unevenly.

For a child living in urban Delhi, AI has found its way into their education either through the home or the school. But for a poor tribal girl living in rural Jharkhand, perhaps not so much. Education systems are facing massive learning challenges for which governments are seeking equitable, scalable and evidence -based solutions. Two to three decades of digital learning has yielded small -scale wins and modest impact on learning. And yet we’ve seen the massive impact of AI already on health systems and that gives us tremendous hope. I keep repeating this example because I’m fascinated with it. In the area of radiology, AI has helped the diagnosis of pancreatic cancer 438 days earlier than would have been normally expected.

We were previously diagnosing pancreatic cancer at fourth stage. We can now diagnose it at stage one and it diagnoses it with greater accuracy than any human ever can and this without touching a patient and that makes me feel excited. We are looking for that kind of accelerator in education. Something that’s going to bring efficiency and quality without widening inequality and as you’ve said that remains deeply human centered because we know that learning is an inherently social process. We cannot be naive about this. We are walking a tightrope between something that is scaling so far and evolving so rapidly but anybody who’s worked in the education system knows it’s a big ship it takes a wide berth to turn but even when with that we are looking for a public good out of AI because we need it these are really tough interests to marry but it has been done for vaccine rollout and it is being done in countries like Estonia right now within the education space through all of this you got it bang on we’ve got to keep teachers pedagogy and curricula at the center and more than anything else we need to keep children at the center matching their right to learn by multi modes including tech with their right to protection participation and privacy keep that in mind and we need to keep that in mind and we need to keep that in mind and we need to keep that in mind and we need to keep that in mind and we need to keep But time and again we make the error that we underestimate the capacity of children.

They’re not passive recipients of education. They have tremendous agency. They can consume tech, they can shape it, and no doubt they will lead it in time. So today’s conversation is about agency. How do we build AI that empowers children to become creative, critical, independent thinkers that maximize the potential, take out of the best of AI, but offset its risks? To help us through that conversation, I have Tom and Richard. Welcome again, Tom and Richard. And we’re looking forward to a very robust engagement. this morning. Okay. So Tom, we’re going to start with you. So you talked about AI sometimes feeling magical, that it’s abracadabra and voila, something beautiful appears. And we know how children love magic.

They really become enthralled with it and

Children do indeed love magic, don’t we all? And we all like fast results. And increasingly, We have much shorter attention spans than we had maybe even 10 years ago, and so we’re all looking for quick fixes. I think we often, well, I think we’re overlooking the fact that children have immediate access to data and information now that they trust inherently from the get -go, and they will take a question and feed it back as if it is the gospel. So there is this real danger that AI is indeed seen as a magic box, particularly generative AI, and I think that that’s amazing that children have this inherent curiosity and the Lego group sort of celebrates that curiosity every day.

It’s a wonderful thing. But as I said, I think it’s a real mistake if we don’t teach children to question the magic and actually make magic for themselves. And in order to do that, that’s why we are… so passionate about these fundamentals of AI literacy because if we simply hand children a box that promises quick magical results I think we are really short -selling them so I’d much rather yeah we hand over the screwdriver we hand over the the kind of compass and allow them to take things apart and start to create their own ideas I’m not sure if I addressed your question there but I think that the magic is the magic is something I would we really want children to create their own and I don’t think that we should be under any illusion that they’re going to work this out without an education system that takes and a societal system that takes this responsibility very very seriously and it’s not about taking this responsibility in a few months or a few years time the time is now to maybe stop some things and actually start a fundamentally different approach

losing

the responsibility to protect them.

Thank you. Thank you for the question. Yes, it’s challenging because kids have access all the time. You can’t stop it. As you say, they have a mind of their own. But I think as we’ve seen even with social media that maybe we don’t always understand the long -term consequences. While I can have an immediate reaction and something that makes me happy in the minute, what is that going to do in the long run? So I think this focus on education as a filter to understand the long -term as a kind of compass of what is a better experience I think is incredibly important. So that’s kind of our position in terms of how we would employ AI.

Wonderful. So there’s two things that we need for empowerment. One is foundational skills. The child needs to have a basic level of literacy to be able to engage with language models. The And then the last thing that we need to do is to understand the language. Second, critical web and AI literacy. And the model you put out looks fantastic. Now let’s take the model into a real -world classroom. What is it going to look like in rural Rajasthan where we’ve got multigrained, multilingual, multilevel classes? How do we make this come alive and have relevance for those type of settings?

I think that the best thing you can do, and any teachers in this room will know this, ask children who are looking at you the question, like what type of conversation do they want to have? And in the form of AI, we’ve just produced a template to discuss AI policies with your classes. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do.

And that’s what we’re going to do. And that’s what we’re going to do. And that’s what we’re going to do. assess this question in a very, very smart, thoughtful way. And if we don’t ask them the question, again, we are very guilty of simply publishing something and deciding that it’s in their best interest. Of course we need to guide them, and we’ve got a lot of information that we need to share with them. But let them think their way through this, and the best way to do that is ask the questions. So, yeah, take a discussion around, you know, where does bias show up in their lives? What might that look like if a technology system leant too heavily on a false set of information?

Teaching them sort of the basics of if -then concepts. I think you can do that in any type of classroom, and you don’t need any type of equipment on the table. You need minds to be switched on, and to do that I think you need to ask children the questions, and you need to trust that they’re going to have some thoughts, and you need to help them guide that policy. So that’s something we’d love to see widely spread.

Yeah, maybe just coming in from… So… Prior to Lego, I also worked… with the UN Refugee Agency for many years and also sort of saw these applications of ed tech in quite rural or humanitarian contexts as well. So I think there are interesting ways to bring some of these concepts to life, even in very, I think I heard the phrase frugal AI being used here at the conference. But one of the things I think even for us, just because we have access to these powerful models doesn’t mean we need to put those necessarily directly into the hands of kids as well. So even as we look at sort of education progression from kindergarten right up to grade eight and beyond, the age appropriateness is super important.

So even as we’re looking at the littlest ones and how they learn about computational concepts and AI, a lot of where we start is actually completely screen free. They are working with understanding computer science concepts like sequences and loops and just doing this completely with bricks. And you can imagine some of these contexts, it may be bricks, it may be something else, but it isn’t even like the hardware. or a screen at all. So you can teach concepts of probability and computational thinking even without some of these, if you don’t have these resources. And this actually aligns well with, as we think of age -appropriate progression. But I really challenge the audience as well around this need to want to put things into kids’ hands directly in any context.

I mean, not just in challenging contexts in rural India, but also in other countries as well. Well, let’s not rush for the fastest and the best model, but what’s actually right for the kids as well.

Absolutely. We need to generate a fair amount of evidence before we rush to scale with something like this. Although we have to mediate the fact that smartphone penetration in a country like India is widespread. So access is there. And a school is a microcosm of a local community. So whatever is happening in the whole country, in our home, is going to reflect. in the school, and if it impacts child well -being or if it impacts learning, then the schooling system will have to respond. So Tom, I’m coming back to you again. AI can sometimes feel very passive. You put something in, you get something out. But we know that the best learning happens through engagement.

It’s that journey of discovery that excites the child. So how do we make this thing interactive? What do we need to do to support creativity in the use of AI?

I’ll declare my bias here, which is that I work for LEGO Group, therefore I’m kind of deeply entrenched in a passion for hands -on learning and a deep belief that when you use your hands, and the science backs this up, you are engaging all parts of your brains that lead to learning. You lead to deeper engagement and ultimately… ultimately a deeper mastery of the subject in front of you. We could show through thousands of research studies that we’ve done through the LEGO Foundation or with any of our research partners that spatial awareness skills develop stronger when children are using their hands. The very basics of mathematics in primary years will develop in a stronger way when you’re using manipulatives and you’re thinking through things.

So this use of hands and manipulatives is something we believe in so deeply. So I think artificial intelligence, it’s a concept of technology. We really believe there’s no reason why hands -on learning shouldn’t be brought in here. You saw in the video that we designed for collaboration first. So this is not a one -on -one learning experience. We really want children to learn together. Groups of four. One, two, three, four. Whatever number you put around the table. We want them to be looking at each other and challenging each other. working in groups, learning the fundamentals of collaboration. It’s not always easy. Things will break. You’ll have to start again. You might not like the role you’ve been given.

That’s a great life lesson. So I think AI can sometimes feel the magic box, but also maybe the dark box. And actually, it’s about helping kids understand that there are really clean and to understand technology fundamentals that underlie artificial intelligence and give them curriculum that means something to them. So we introduced a computer science GCSE in the UK back in 2014. I went to school in the UK. It’s where I live. I’m not too proud to say that that was a failure in terms of uptake by students because there were two mistakes that we made. One was a really lack of teachers and there was no teacher training. So there was no… kind of innovation put into the delivery pipeline, but then there was also a real lack of innovation in the courseware and the curriculum that we designed for that GCSE.

And so children just sat very bored in a computer science class learning very outdated principles. So I think the best thing we can do for interactivity and artificial intelligence sort of education is apply this to things that mean something to today’s teenagers and young people. And that means kind of meeting them where they are and sort of helping them apply fundamentals of AI to the life that’s going on around them. And I think that applies both to the child in the classroom and also the teacher. So give them curriculum that sort of applies now rather than

I must say that I’ve seen the joy of the Lego bricks. I’m South African and I would travel to the United States and I would travel to the United States and I would travel to the United States and I would travel to the rural areas of KwaZulu -Natal and there’d be nothing else. there except a hut. You go to the back of the hut and you see a child with two things, the workbook given by South African government and hand -me -down Lego bricks. And you would see that coming alive of head, heart, and mind. And it was beautiful to see. So thank you, Lego, for that. All right. Richa, I’m coming back to you.

We’re excited about the tech, but we’re also worried about safety. And we’re worried about privacy. And our young adolescents, in particular, who also make up the child cohort, are worried about privacy and safety. So in all of the issues that a private entity needs to think about when they’re designing a digital experience for children, where does safety and privacy stand? And how do you create this joyful, meaningful, and meaningful experience for children? Thankful experience while reducing the risk with the tool. like AI?

Thank you. So, as you can imagine, safety, privacy, these are absolutely foundational and non -negotiable as we’ve seen on the LEGO education side and similarly in ours. And just to be clear, none of our LEGO products actually employ AI. So the smart break is not using it because for all of these exact same reasons that we have a very high bar, if you look through the lens of childhood, we have a higher bar that we need to meet. So there is this tension, though, that obviously there’s so much potential for meaningful, incredible, hands -on play developed through AI, but at the same time, we need to ensure that until that bar is met, we would not put that in our products.

Excellent. So for our young people of today who will be consumers of AI, trust, transparency, privacy, sustainability, and voice would be critically important. important that we’re not just handing something to them. They get to shape it and co -create it with us. At this point in time, we have a couple of minutes. So we’re going to take a couple of questions from the audience. Since I’m left -handed, my bias is on the left side. I’m declaring it up front. So I’m going to take three quick questions in the first round, and then I will come across. So I’ll take one from the front, one from the back, and then on this side. Right. Okay. Over to you.

Thank you. Thank you. Fantastic session. My name is Nikhil Bawa. I write about AI and education. I’m just curious about what advice you would have for parents because schools are going to be slow to adapt. And so do you have resources for parents in particular about, because they will, I mean, I’m trying to develop an alternate home curriculum for four hours a week outside. at a school for my kid. Just curious about what you would recommend for parents. You need a combination of structured and unstructured play both, right? I want to know your views on how you’re thinking unstructured play with AI and then play around with also other things like self -regulation, which becomes very difficult for even a team to manage.

So that’s one question and the second is, we’re doing a research on this entire AI adoption at homes which is beyond classrooms. And the initial findings are quite disturbing because it is getting a adopted and adopted just because it’s becoming like a race, especially in India. So I would also like to know if there are some recommendations of various AI play adoption from you guys. Okay, beyond the classroom.

Good morning. Thank you so much. My name is Asha Nanavati. I’m with Alliance Educational Foundation, which runs a charitable small K -12 school in Kerala. They love the Lego products, you know. But I really heard what you said earlier, Richa, about capacity building, about including teachers. We’re a charitable school. All profits go back to the meals, the child. And we don’t maybe have funding for training teachers on AI adoption safety practices. We have play school learners up. So is Lego thinking about doing anything in India? We definitely would love to hear more about that. Thank you.

Can we take a response to those questions? Can I work back? So we have a recommended AI toolkit to take into classrooms. And it’s a facilitated conversation with children around, you know, what do you think about AI? What should a policy be for a school and a classroom? To be honest, I think that is applicable to a group of teachers in a training day as it is to children and a teacher. And I’ve seen really great examples of schools that I know in the UK following a similar approach. I think maybe there’s a theme in all of the questions. Like maybe don’t worry about applying the brakes, right? Things are moving incredibly fast. I wouldn’t go along with what can feel like this very fast river or wave or current.

I think it’s perfectly okay to apply the brakes and say we need to hit pause and we need to have a conversation. And the conversation needs to be about what do we want. And when I say we, I mean the children in the classroom and the teacher. Like what do we want to get out of this experience? And I think have the conversation. Have the conversation first and don’t worry too much about the tools or the software. that you’re worried that you might be missing out on using. And as Richard just shared, we’re not using generative AI in our products, and that’s for a very deliberate reason, because we just don’t know enough yet about safety and privacy.

We have conducted research into that, and we’re following that very closely, but we’re not willing to take any risks. And I think this time of childhood is just too precious to make some shotgun choices that we’re going to pay very heavily for in the future. So I think empower the teacher and the child to have some really formative discussions about what do we want to get out of this, and then maybe look at what’s available.

Le

arning our child agency versus some scaffolding. So as we bring these products also into core classes, classrooms as part of education strategy now. We do understand the needs for teachers to provide a scaffolding as they take them through this learning journey. So we have, for example, at LEGO Education, we follow something called a 5E model of engage, explore, explain, elaborate, and evaluate. But it’s just a fancy way of saying how do you sort of get the kids hooked initially to a big picture question or a real -life example. But you provide the educators and the students sort of a structure as you go through this process of thinking about that question. I think who had that question yesterday, the distance between a question and answer and that space between that’s where magic or inspiration happens, right?

And so giving that space for that to happen. And then when they’re building – and so you’re providing the structure for them to work in groups and build this out. But towards the end, in the elaboration phase and at the end of every unit, there’s something called a design challenge where the kids are not provided that much instruction. They’re given an open -ended prompt. And then they take the concepts and learn. They take the lessons that they’ve learned and apply that in a more open -ended way. outside of the Lego education computer science and AI product we also have something called First Lego League which is the world’s largest STEM annual STEM competition as well and there you see these it’s it’s so inspiring to see these groups of eight kids building a robotics or challenge and then doing a science theme as well but that’s completely open -ended so they will go beyond what a 45 minute lesson is what they would do within a 45 minute lesson and have a lot more agency in terms of what they can create beyond what so the teacher would take them through in in a classroom Ni

khil we have some really great resources actually available online both on Lego and Lego foundation around facilitated play with your child and it’s starting from very early years through to later years

so I’m gonna take two more questions because we coming to the end of the session we need to close we need to close okay now I will take one question but really

Well, I think we heard a lot yesterday that we need to make sure that any tools that are made available are done so in languages that mean something to you on the ground. So I think there are many tools out there that can do automated translation. We hope that the quality is going to be really strong in them. We’re currently producing in English language. Of course, there will be localizations in the future.

All right, colleagues, we need to come to a close because people need to move to the next session. We’re designing for safety, for equity. and while we provide services, we need to match it with demand. And to match with demand, teachers, learners, parents need to be empowered. That responsibility rests with all of us. It’s hard to do many things in an education system. Empowerment is not one of them. We can do that quickly. We can do that with scale and we can do that with equity. So I want to say thank you to our panelists for today for having an engaging conversation and a big thank you to Lego for bringing us together to have a conversation about children, education, and AI.

Thank you so much. The session is closed. Thank you. Thank you. Thank you.