The Innovation Beneath AI: The US-India Partnership powering the AI Era

Thank you. Thank you. Thank you. this infrastructure right now and closing the gap between commitments and capacity. This is where the real opportunity lives. Moderating today’s session is Ujwal Kumar, founder and CEO of Quantum Alliance and co -founder of Cognosy AI. Quantum Alliance works with universities, industry and governments to get top talent working on the foundational problems beneath AI, from critical minerals to energy to semiconductors. He will be joined by Tuan Ho, Unicorn founder turned venture capitalist, now partner at X Fund. Jeff Binder, serial entrepreneur with multiple Fortune 500 exits, now at Harvard Venture Partners. Prince Thavan, IAS officer and executive director at REC Limited under the Ministry of Power. Rushali Gaut, global director of climate operations at Google.

Dr. Tobias Helbig, V .I. and VP of Innovation at NXP Semiconductors. Ujwal, over to you. We’ll start with a quick picture for the panelists if you can all rise Thank you

Thank you everyone We are up against Jan, we are up against her boss. So, but, let’s have fun in this panel. And the broader idea, like we have been hearing all about AI models, what AI can do, and this panel is more about, we are talking about AI at scale now, what it needs, what it would make fulfill when we talk about AI, like AI -driven companies, when we are talking about AI -driven solutions. Let’s talk about this now, as AI is forcing creative destruction of how the world builds infrastructure, energy, semiconductors, critical minerals, physical edge systems, data center. US and India are now building this together, rare earth corridors in India’s union budget. Google committed $15 billion to India and accelerated focus on clean energy.

Jensen at Davos called this the largest infrastructure build -out in human history. Two weeks ago, 54 countries launched FORGE, the first global framework for the minerals that power AI. Yesterday, on this very summit, Sundar Pichai laid out Google’s $15 billion commitment to India, a gigawatt -scale AI hub in Vizag, four new subsea cables between US and India. The models are getting attention, the infrastructure is getting the money, and we exactly have the right people to figure out where is all this going and what do we need further. Thank you. To start with, XFund was the early investor in Vulcan Elements. Now it is backed by 1 .4 billion US dollar government partnership to bring America’s rare earth magnet supply chain.

What, according to you, the US -India critical minerals corridor look like from the investor side?

First off, thank you for having us here. I’m really glad you pulled this panel together. I think your points earlier about the focus that we tend to put on discussing AI models and everything in the model layer, but we don’t really talk about what exists underneath that, is actually a really unique topic to cover and one that I and XFund, has generally been extremely excited about. so the way I look at that is that in this strive that we have to build intelligence we tend to talk a lot about the industrial revolution that it will create we often have to understand we often look at the industrial revolution that will be required in order to support the creation of that infrastructure there are a lot of inputs required for AI infrastructure so you’ve got energy you’ve got energy the power grid, power generation has to be clean, sustainable, renewable and the demands for AI infrastructure are going to require us to really solve large problems as to how to supply that power you’ve got, everybody’s talking about critical minerals now you mentioned Vulcan elements right You know, Vulcan Elements was a business that we invested in.

It was a Navy veteran out of Harvard who had spent a lot of time looking at supply chain issues for the U .S. military and noted that, you know, 95, over 90 % of, you know, magnets, rare earth magnets were coming through China. It creates a strategic vulnerability for the United States. And the reason why it creates a vulnerability is because, if you think about it, there are so many things that we need, that we build that require magnets. You can’t build hard drives. You can’t build motors. You can’t, I mean, nothing that moves can be built without them. We talk a lot about chips. You can’t manufacture chips without magnets. And so I look at, you know, problems like that, and for the first time, you know, I’m not going to be able to build a magnet.

I think you’ve got guys like me, venture capitalists, looking at… the opportunity to invest in building up that type of infrastructure to solve those sorts of problems. But that’s just one, right? You have to figure out how do you source it? Where do you get the materials from? And so when you look at things happening on the geopolitical scale, for the first time we are, at least in the United States, we’re looking at these trade deals to try to figure out where we’re going to supply the materials. Like how are we going to completely rebuild our power grid? How are we going to build up the capacity for refining those materials? Where are we going to source them from?

Where are we going to have to get them from? As we’re looking at data centers, how can we make them more sustainable, more power efficient? In order to support the AI needs that we have right now, like power consumption for data infrastructure, infrastructure is already, I think it’s about… It’s approaching 10 % plus. How are you going to meet that demand? And so from an investor perspective, yeah, we’re going to look at all of the cool AI products that entrepreneurs are looking to build. But on the other side, what is very exciting for us is looking at all the low -hanging fruit that exists for all of the inputs of industries that have not been innovated in for decades.

Power grids that have not been upgraded for the better part of a century. It creates huge opportunity for us as investors. And you mentioned US -India. Yeah. I… I find a lot of opportunity in the U .S. and India working more closely together to try to figure out how on both sides of the world we can build great companies to meet that need.

Thanks, John. You spoke about needs. You spoke about the innovation. You spoke about what the early stage startups should be focusing on. I’ll move to Jeff, who has built companies from scratch and made multiple Fortune 500 exits. I would ask him what would it need for young entrepreneurs to build and scale in this space and do it successfully.

Thank you for having us and putting this together. I know that we have more people here than Sundar has at his keynote. So I heard Sam Altman only had 10 yesterday, so we’ve already outdone him. So, you know, I think it’s such an interesting time. I was there in the early web days in 99 and 2000 and 2001, and, you know, the excitement around the Internet obviously fueled a massive tech boom. And ultimately a fiber build -out, an infrastructure build -out, and it took years for all of that infrastructure to be absorbed, and ultimately it was. I think the difference this time around is that the tool sets themselves that entrepreneurs have available to them are smart. And they can bridge some of the challenges, especially since we’re talking about partnerships between the U .S.

and India. But, you know, oftentimes, especially when you get to things like user interfaces, there are cultural differences from the development work that would happen in India for an Indian audience or the U .S. or China. That’s always made it more difficult for collaboration, sort of on the front end. And many of the products that entrepreneurs are working on are often, you know, front end facing, consumer facing, at least initially. They’re generally not building a lot of B2B platforms. That happens later when you get the experience as to what’s necessary in a business environment. And I think that AI is going to change drastically the ability to leverage sort of cross -border talent, in particular with India and China and other places that were harder to leverage before.

It’s certainly from a quality perspective, SQA and back -end development, I think entrepreneurs have been able to leverage India and other places for the last couple decades. But it’s been harder to get the front end of a product to sort of match the cultural necessity of a given market. And I think that’s going to change. And I think for entrepreneurs, it means that they have a massive amount of leverage that they didn’t have before. And it means that we’re going to have a flood of new ideas that are actually brought to market and work fairly well and allow entrepreneurs to deliver products with probably a tenth the capital, depending on the product, obviously. If you’re doing magnets, you’re sort of stuck with the physical properties and refining and some of the things that you can’t do from an IT perspective.

But. I think for entrepreneurs, it’s an extraordinary opportunity. And those that will win. in my mind over the next few years are going to be the ones that leverage the tools most quickly because it’s not possible any longer to develop in the way that people were developing two or three years ago. If you do that, you’re going to be way late. And so now it’s about not so much your product, but learning what the state of the art is, which is literally changing every day in AI. And it’s a golden age, I think, for entrepreneurs. I think it’s going to be much, much more difficult for investors as an environment because the wealth of ideas are going to get much further along.

And that makes it more difficult, not less difficult, I think, to be an investor because you have more mature products. The entrepreneurs are going to be more mature and the entrepreneurs will have more leverage. And they may be able to make it to market much earlier than they would have otherwise, which means where they might have gone for a second round of seed capital, they may be able to get to market and be into revenue with a single small round of seed capital or no seed capital. And that makes that whole early, early stage ecosystem of angel and venture investing much more challenging. And so I think it’s just a great time. I do think that there’s a huge risk, and I don’t think it affects entrepreneurs or young entrepreneurs, but I do think there’s a huge risk of an overbuild.

It feels a lot like the leverage in terms of optimizing hardware and infrastructure is only going to get better, and it’s potentially going to leave us with actually a – I know right now we’re worried about power, we’re worried about compute, we’re worried about data centers, but I would project if we sat here two years from now, will be looking at a grand overbuild with a real challenge around ROI and how to make all these investments work. And so that’s going to be another positive for the entrepreneur because those resources are going to become very inexpensive relative to even what they are today. And so in that sense, I think it’s a great day for young entrepreneurs.

Thanks, Jeff. Jeff, picking up from you about leaving from some of the AI tools, going to market faster, build out, ROIs, now we move to the right time, actually, when you spoke about ROIs. One of the things I was very curious about, all the world leaders coming here and putting a big bet on India. So, like, we just heard Sundar yesterday talking about $15 billion. New C cables between, like, with India. new innovation hubs. Rosalie, you are leading the clean energy transition with Google. I wanted to understand what Google’s, AI’s scale demand basically in terms of energy and why you are placing such heavy weight on India.

Okay, good. Thank you. Thank you all for joining and I appreciate it. I am being pitched against my boss, so I’m going to try and keep it as entertaining and as nice and valuable as I can. That’s a very interesting question in terms of the scale and why India. But I’ll build on a few things that both of you spoke about. One of the interesting things about this particular AI innovation timeframe you’re looking at is it’s what I call across the full stack. So you’re looking at a lot of things that are happening, which typically we talk about software, AI models, applications. That’s the shiny objects everybody talks about and very exciting. But then the amount of work that’s happening on underneath that, which is why I love this session, too, is beneath the AI.

The physical infrastructure layer of it is fascinating. And that goes from everything from the foundational layer that you’re talking about, which is your materials, your data center construction, your access to energy, to water, to all those foundations. So then how do you construct things the right way? We forget about the physical. These are all buildings, quite a few of them. How do you construct them the right way? And then how do you operate them the right way? And then the use of that. And so what we are seeing is just tremendous value and innovation across the entire stack of AI. Which I. Which I, as an engineer, find very, very fascinating. So in terms of Google, I think the.

The privilege and responsibility that Google has is how do we bring about the most value across that full stack, both from a business perspective but also from the impact perspective. And so a lot of the investments you’re seeing, you’re seeing across those pieces, right? So if you walked across this summit, you would hear different pieces of it. Our expo was mostly featured on the product side, so AI for education, AI for healthcare, AI for agriculture. Culture, how do you use AI in domains, contextualize it, and all of that has a layer of a country and where that context is. And then the announcements you talked about were a lot more on the physical side. So it’s what’s required for data centers.

You need good design, good builds, but then you also need network. And so the sub -C cable announcement is part of that. And if you read a little bit, it’s fascinating. It’s an India -America connection, but it goes one way we are building is across Africa. So that’s a big reason. It’s a big reason to bring on board. And then the other way it goes from Singapore and Australia. So it’s a fascinating network, which, again, you can only build data centers, but what’s the point if you can’t actually use it and network and bring them closer to wherever the edge cases are? So super excited about those pieces. Now going to your point about why India.

So why not India, I think, is what I would start with. But most people know it’s a billion -plus user. It’s a great growth market. It’s a lot of young population who we think are going to be the frontier of the growth. It’s a lot of population who also is very eager about tech and tech adaptation. So if you think about what happened with fintech and the phones and digital tech, a lot of the APAC countries, Asia and Global South, jumped ahead. I see people who didn’t even have credit cards. Now everybody uses GPay and UPI and all of those, right? So there’s a whole revolution where you can skip and build. And I think that’s another big exciting part of investing in India is can a generation of innovators come up?

Who don’t have the linear growth that we’ve seen in other regions but can leapfrog it? and I from an operational perspective feel super excited the same way about clean energy you can talk a little bit more Prince about that but India is one of the fewer places where the math on clean energy just works there’s growth, so there’s tremendous demand, lots of solar wind potential tremendous research going on in battery long duration storage, good policies and then the biggest issue what we’ve seen in the US is grid but they’re trying to build a high frequency grid which is fabulous, which then you bring in the innovation on that layer and that’s the unblock and if only you could solve permitting issues then you’re solving the whole stack that’s the excitement, it’s where the math works where the business case works, where you’ve got the talent and the innovation potential and then you also have the users

wow, that’s amazing I do understand now thank you Thanks. So moving from that side, we heard about the demand side, and I’d love to take the insights from Prince, who is actually building the digital public infrastructure for the power sector, and they have been doing some incredible work, which I’ve seen in the past few weeks, particularly about P2P trading. And Prince, with all the initiatives about grid reforms and the trading platform which you are launching at this summit, how do you think the AI’s energy demand is going? How are you supporting it? Your insights.

Thank you. Thank you, Joel. Thank you, everybody, for being here this morning. Let me first start by putting the AI. Thank you. compute demand in context. I honestly, resonating from what Duan had also said in his remarks, I feel that AI essentially will not scale unless your power is programmable. Okay, and that is, so the AI, I would say, I don’t want to call it race, but the AI build will depend a lot on, not on chips, as we might think. We do have the capacity and capability world over to solve that problem. But I think the binding constraint would be grids. It would be how intelligent and resilient your grids are. And I believe that is where, what is going to define the development of most of the compute infrastructure.

Now, what, India has essentially started doing is, we are redefining the architecture. Okay, so we are redefining how we view the grid. India already has one nation, one grid, which is essentially meaning one frequency. And now we are also having one digital interoperable layer that is being brought in by the India energy stack. So what does this mean? What does the stack essentially do? So the India energy stack, it basically creates the interoperable rails for systems to interact with each other. If you have a data center, it is not just creating high demand, but it is creating high peak demand that needs the grid to respond. And that is where you need coordination at scale.

So what is going to be scarce in the times to come is not electrification, as Roshani said. We have enough math works when you talk about solar power, when you talk about wind, even hydro. So that is where the math does work. But what needs to be ensured is coordination at scale. And that is what the India Energy Stack is essentially doing by laying down those foundational building blocks. Now, what we started with was a first showcase of how you can use the stack to essentially source energy from distributed energy resources like the solar rooftop panels, which we have on top of our households. We can literally transact in energy the same way that we transact using GPay, UPI payments.

Or using other such applications, Paytm, PhonePay, etc. So similarly, just imagine. that the data center, instead of relying on long -term PPAs and then hoping that the grid will deliver, can essentially source its power from millions of such distributed rooftop assets dynamically at scale. Just imagine the power of that happening. So it can literally be generating livelihoods for a lot of people who may not even be in geographical proximity to the data center. So individual retail households can essentially monetize their rooftop solar power by supplying to such data centers. How does the stack enable it? The stack lays down standard rules for measurement, identification, and settlement all in near real -time. So that’s how the architecture of the grid itself is changing.

let me the grid evolves generally in decades as to one said we have not invested heavily in the grids world over might be that China is an exception there but India has started doing the plumbing work it has started doing the hard work on that layer and generally AI evolves in quarters but the grid would evolve in decades how would you keep pace right and so that is where the India energy stack comes in where we push that development frontier and we enable people to talk to each other on the grid so AI would need not just electrons not just chips not just electrons it actually needs intelligent electrons and that is where the India energy stack sits in I think that should be in the times to come one of another reasons beyond economics that companies like Google or other companies would take bets on India.

And let me also tell you, you did recount Sundar’s message about $15 billion, but there’s also Reliance’s message about a trillion dollars in the next seven years. So let’s not forget that as well. I’m just putting stuff in context.

Two minutes to one. li

ke India. And by the way, India is very, very well represented in Cambridge, which is how I probably met half the people on this panel. But it really does create these global scale opportunities to reinvent, to create this other, to support this other industrial revolution beyond just what the AI and the intelligence is allowing us to do. T

hanks, Juan. Yeah, that’s exciting. Now with that, we want to move to Dr. Tobias. We have been talking about physical layer infrastructure. He has been working in semiconductor innovation since last 20 years, building it across US, Europe, India. I wanted to ask him, what does the next innovation looks like to you? Or what are you working on at this point? Where are you placing? your bet.

Yeah, thank you very much for the question. Thank you so much for having me here. It’s great. And I would like to build a little bit, Jeff, on what you said earlier where you had this, are we on the right track? What the heck are we doing? And let’s zoom out for a moment. 1942, the head of IBM made a statement. There’s a world market for about five computers. And he was right, given the kind of computers he was looking at. We know better now, some years later, there’s laptops, PCs, there’s mobile phones, there’s basically a computer in every device. There’s billions of computers. Now what we discuss is, hey, AI, huge disruption. Power hungry like hell.

Shall we build some new computers? Shall we build power plants? Or how do we run it with renewable energy? and I get this nagging feeling is this really it or are we missing what came after these five computers in what we’re discussing if I take benchmarks like here’s my brain and it takes 20 watts there’s a fly which is a pretty agile intelligent robot below a milliwatt there’s something there’s something which is going to happen which is different than what we’re discussing here at the moment and that is what’s driving us as a semiconductor company in building on what starts now and driving it out into the real world so we today have products where on whatever 10 watts or so you can run very meaningful LLMs you can interact, you can drive the intelligent into the edge, into our real world that goes hand in hand with what’s happening around here moving from, hey, I can perceive something, is it a dog, a cat, to I can think, generative AI, I can create something out of those models to the point that I can create agents, stuff which acts on my behalf out there in the real field, which drives the intelligence and this disruption you’re looking at here at the moment and which is driving all these conversations, drives it close to us into the real world to the point that these devices, these robots, these whatever you want to call it, they’ll be able to learn.

So what we discuss here, and this is a huge challenge, I totally agree with all statements made before, we’ll see a next phase. It will see this moving into the real world, moving close to me, moving into autonomous systems, which ultimately change my life and change industries. And there is this second wave building up and my expectation, to some extent my hope, is from now on, where we sit as a company, is that this huge thing you’re already discussing with data centers is the five computers. And what is coming is these billions of edge devices which we will also see in the AI space. And just giving an example, I’m running marathons with a watch with me.

I charged it before I left in Germany and it still stays 12 days battery power. And there’s a lot of intelligence in that watch. This is where we are going. So the one is feed the beast and make it happen. The second is avoid that the beast is hungry and look at totally different models which will come in the next phase. Thank you.

This is very interesting. Now we are talking about taking AI out of data center now. Any comments from the fellow panelists?

I agree with him. I think that the IBM analogies are very good. Very good one. I think we are all focused on the core and centralization. And as we’ve seen in many markets, they move from centralization to decentralization to hybrid approaches. And so that’s, I think, an incredibly astute observation. I do think edge devices ultimately have to be the core component in the full proliferation of AI. And so that means that, you know, as he said, small amounts of power can generate lots of value. It doesn’t necessarily have to be tokens in the center of a data center. So that goes to my concern that I think that – and look, I think all of the resources that are being built will eventually be consumed.

That’s not a – that’s a given. It’s a question of when and what – on what ROI they’ll deliver as they’re being – being consumed and used. And I think that’s a huge risk because – agents at the edge, which are probably going to end up being in the end a much more likely modality a decade from now. And it’ll be interesting to watch for sure.

Okay. I do have a small – and I completely agree, actually. That’s truly, as Jeff said, it was an absolutely astute observation. But you know where you can see this being played out in practice even today? And that’s when you talk about finance. Okay. So finance world knows this. So today, because I work for a non -banking financial company, and one of our main products is infrastructure financing, where data centers are a product that we finance. And Roshali was in a panel discussion that spoke about the trifecta of AI energy and finance. But you know the finance bros, they have figured it out because today if you go for financing of a data center, you won’t get debt financing for GPUs.

GPUs are mostly financed by equity because there is obsolescence risk in GPUs. You would get debt financing for the brake motor, maybe even for sourcing power, but you won’t get debt financing for GPUs. And there you have it because they are seeing the big picture being played out there. So completely on board there, yes.

Again, Rukhsani has been…

No, no, no, I’m good.

No, no, no. We want to hear from you. Please, go ahead.

No, I think the risk of strata assets, the way you said, and the ROI is real, like in a sense of where you’re investing and what. But I think your point is very astute. There are portions of this will be obsolete. There are portions of this which will be very easily replaced, whether it’s on the chip side or whether how you write the programs. Even the models, right? You went from large scale, smaller. How do you build them? but also what I’m hoping is the bets on some of the hard infrastructure are just good things to do like I think to me the fact that we are seeing a transition to renewables or seeing a transition of the grids being operated in a better way, some of the boring bits that people didn’t pay attention to is how do you run things efficiently those I think are good pieces of this and then it goes to you right size it, we’ll get over the FOMO and the extra investments and it’ll probably get right sized into where in the stack you really want to invest with the ROI

Thank you, so with this I’d like to take it a little bit more deeper, like we spoke about some of the opportunities we agree on something we may not on some Tuan, you invest early on founders I wanted to check with you and understand with you how do you, can you tell us that is there a mismatch between what is getting funded and what needs to be funded?

That’s a good question. Is there a mismatch between what’s getting funded and what needs to be funded? Well, I mean, probably. Yeah, I mean, I think, well, okay, going to the theme of this, I think there is more likely to be a mismatch between what is getting funded in the sort of like the pure AI world, if we’re talking about the foundational models. I think, Jeff, I think you had made this comment a little bit earlier. You look at a lot of the AI companies out there, and it’s a little bit like the dot -com era where you’ll see 100 companies, and the reality is that in five years, there will be five of them that are left.

I think one reason why I like focusing on infrastructure -type businesses is because I think… I think there’s more durability. and clarity to exactly what the problems are that you’re trying to solve. I mean, every great startup begins with a really well -understood problem and a product, what they call a product -market fit, like a founder that’s able to build a great solution to that problem that has some sort of market validation in need. And what I find really exciting about infrastructure businesses is I think the problems are a lot clearer in terms of what you’re trying to solve. To your point, there’s a lot more risk in the GPUs. There’s a lot more risk in the models that you’re building, that you’re building around them.

And the reality, too, is that those things are also going to change a lot faster. I mean, if you look at a data center, as an example, a data center ultimately is a giant box that provides a lot of power at scale and it needs to be able to efficiently… efficiently cool what’s inside it. of it. In terms of what GPUs or compute you put inside, I mean, that can change over many, many generations. But the utility of the infrastructure you’ve built there will always have value. So, I don’t know if that answers your question.

To add to that, I think that if you look at the dot -com era, measuring, with the exception of hardware companies, which were in switches like Cisco and other players, it was very difficult to determine whether a product was good or not. For those who remember MySpace before Facebook, it looked like MySpace was going to own the social media space. Of course, most, half the people in here probably don’t even know who MySpace is. It’s much different now. There’s a measurability component in all aspects of AI that didn’t exist in the dot -com era. You know, you had commerce platforms, but it wasn’t clear what made one commerce platform better than another. The consumer would ultimately decide that over time and through iterations.

And if you remember, Amazon for a long time was known for one -click ordering. Well, none of us really want to do that because we don’t want to make a mistake and find out that we bought the wrong thing. I think now it’s different. Almost every aspect of artificial intelligence deployment from the foundational aspects all the way to the top of the stack are measurable. And so that’s going to make the success and failure of businesses much more clear, much sooner than it was in the case of the Doctomer. And I think that’s going to be ultimately the element that shakes out companies very quickly. And then to the point about obsolescence and GPUs, we don’t know what the hardware roadmaps look like, even inside of a Google or a Jensen’s company, NVIDIA.

Or somebody else that’s out there. And power, which is the fundamental thing I think we’re talking about foundationally. can be grossly disrupted by those advances because if somebody has a breakthrough on chip design that’s now 10 or 50 or 100x what somebody else deployed, their data center is now almost instantly, at least from a financing perspective, obsolete. And so that’s a huge danger, I think, for investors in those foundational areas.

Thank you. Dr. Tobias, you have also been involved in the innovation ecosystem very strongly. What is your take on this? What are you seeing because you are also involved in India? I’ve seen your company running hackathons and competitions. I’d love to know more from you.

Adding to what just was discussed, we have a tendency to overestimate the next two years and impact and underestimate what’s happening in 10 years. And at the moment, we are going into this with huge bang. which even maybe have these ups and downs things even much bigger. From my perspective, all what we are discussing on AI is absolutely real. This is a huge disruption. This is changing industries. This is changing lives. This is changing professions. Wherever there is data, there is change. And that in the end is driving what we are doing by developing the products we have, which is semiconductors products, by being in India for that since literally decades. Development centers on our DNA history as a company of Motorola, Freescale, NXP, here in the Noida, Delhi region, in Bangalore, and so on.

So very much working on that. And on your question from an innovation perspective, well, we all know the hype cycle. And that’s tough. Because it always means that there is disruption. And there is a trap of disillusionment. And we’ve seen it. for all major breakthroughs, especially when they are being hyped up like hell. There’s the self -driving cars. There’s other things. In the end, these things get real. They have the substance. They happen, and they transform things. And AI will. The way there, and also in the question, hey, what’s the risk? What’s the bad, and what’s coming from the sidelines? I think we will see still troughs of disillusionments and surprises. There was one some while ago when this wave had a deep -seating moment.

Such moments will come again. And there will be a recovery from that, I’m also sure. So I’m in innovation since literally decades. I love it. It’s a roller coaster. We overestimate, we get shocked, and we get it right.

Thank you. With that, I’ll go to Sari. I was very excited when I saw Google Logo launching Google Climate Technology Center. Okay. And I would like you to quickly give your insights, like what is it about and what would the innovators be looking for it?

Yes, thank you. So super excited. This week we announced in partnership with the Office of Principal Scientific Advisory for the Government of India, Google’s Center for Climate Tech. So there’s a couple, you know, how did we get here? Because that’s interesting to you is we see a lot of innovation. I live in Silicon Valley. I was raised in India, across back and forth. I’ve lived across the world. There’s different innovation which comes from big institutes, big academic settings, big companies. But there’s also innovation that comes from different corners of the world. What we loved about the PSA philosophy was they’re trying to get more Tier 2 and Tier 3 cities and also a wider spread of universities and academia that can get involved in this.

So, you know, besides your premier one. So that was very enticing. The other thing is, how do we take innovation down to the root? which I think also helps with some of the hype cycle because you’re making it local and you’re also making contextual to where those cities are. So with that in mind, what our center is looking for, we have a couple big pillars. One is skilling. We think there’s green skilling. A lot of focus on AI skilling, but in terms of green skills, which are decarbonization, clean energy, in terms of just we are looking at materials, chemistry, there’s a lot of new things in those spaces which haven’t been brought into college curriculum or university curriculum.

So we want to build upon that. A lot of the construction and investments are happening in tier two cities, so we think it’s a great way to get a more diverse pool skill in that. So that’s number one pillar. The second one is low carbon materials. So you go to embodied carbon, something you’re all very passionate about. So how do you drive innovation in construction, which is going to be huge? And again, it’s not just data centers. What you learn from data centers can be for real estate, for commercial buildings. So it’s to do with low -carbon steel, low -carbon cement, and low -carbon materials as you see them go through that construction cycle. And the third one we have looked at is right now that we have is sustainable aviation fuel, which is a little different from data centers.

It’s not that, but I think it’s like a good growing area, which we are, again, one of the philosophies we have is where can we find first -of -a -kind pilots and places where we can build, bring the Google brand and innovation. And we think sustainable aviation fuel in a growing country that is like now has one of the fastest growing airports and air traffic, that would be a good one too. And our hope is as we go through this, we are trying to see very outcomes -based, so not pure research, but pilots and actual update.

Thank you. Very quickly, Tuan, do you have any closing 30 seconds?

I was going to say there, one thing that I don’t think we had a chance to do. We didn’t discuss as much, but it is important. especially as we’re at an event like this is government financing. I think what’s really another thing that’s been really exciting about this is having a tech conference like this where you have the Prime Minister and multiple heads of states coming from around the world to say like, these are things that we need to invest in, these are things that we need to support, is I think from a tech VC side of things something that we’re not used to seeing. But I also think it’s very exciting. Both in the United States you’re seeing hundreds of billions, hundreds of billions of dollars being invested by the federal government into infrastructure.

And you’re seeing similar investments being made in countries like India, countries outside of, China’s been doing this for a while, but you’re seeing this happen around the world. And so yeah, I think, I mean, where are we right now? There is the . industrial, like I said at the beginning, there’s the industrial revolution that AI is ushering in, but there’s also the industrial revolution that the requirements of AI are also going to require or is also going to usher in. So I think it’s going to be a bright future for us all.

Thank you. I think that’s a great closing for us, and I enjoyed talking to all of you. I really had so much fun. Thanks, and your insights are amazing. Hopefully the innovators looking here, they got something out of it, and we’ll see some new people coming to all of us doing the innovations. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.