Daybreak - India can’t build the next Nvidia now but it can become the place Nvidia needs next

Episode Date: July 10, 2025

Just last year, Nvidia CEO Jensen Huang sat across from Mukesh Ambani at the company’s first-ever AI summit in India.Dressed in his trademark black leather jacket, Huang addressed a packed room of tech founders, policymakers, and academics. He made a bold prediction: India, long known for exporting software, will soon be exporting AI.But this wasn’t just another keynote. It was a power play.At the same event, Nvidia and Reliance announced a major partnership to build AI infrastructure in India -- everything from data centers to foundational models. And Reliance wasn’t alone. Nvidia also inked deals with Infosys, Tata, Tech Mahindra, and Flipkart.This episode dives into why Nvidia is betting big on India, how that fits into India’s own messy AI ambitions, and what’s really at stake when a $4 trillion company becomes a country’s AI backbone.Tune in. *Correction: In the episode, it was mentioned that TCS has 50,000 AI-trained engineers. We’d like to clarify that the accurate figure is that over 1,14,000 TCS associates have been trained in higher-order AI skills. 

Hi, this is Rohan Dharma Kumar. If you've heard any of the Ken's podcasts, you've probably heard me, my interruptions, my analogies, and my contrarian takes on most topics. And you might rightly be wondering why am I interrupting this episode too. It's for a special announcement. For the last few months, I and Sita Raman Ganeshan, my colleague and the Ken's deputy editor, have been working on an ambitious new podcast. It's called Intermission.

We want to tell the secret sauce stories of India's greatest companies. Stories of how they were born, how they fought to survive, how they build their organizations and culture, how they manage to innovate and thrive over decades, and most importantly, how they're poised today. To do that, Sita and I have been reading books, poring over reports, going through financial statements, digging up archives, and talking to dozens of people. And if that wasn't enough, we also decided to throw in video into the mix. Yes, you heard that right. Intermission has also had to find its footing in the world of multi-camera shoots in professional studios, laborious editing and extensive post-production. Sita and I are still reeling from the intensity of our first studio recording.

Intermission launches on March 23rd. To get alert, as soon as we release our first video. episode, please follow intermission on Spotify and Apple Podcast or subscribe to the Ken's YouTube channel. You can find all of the links at the ken.com slash I am. With that, back to your episode. Well, the time has come, the time has come for robots. Robots have the benefit of being to interact with the physical world and do things that otherwise digital information cannot. Physical AI and robotics are moving so fast. Everybody pay attention to this space.

This could very well likely be the largest industry of all. That was Jensen Huang, or AI Jesus, as many have christened him. He is the CEO of what became on Wednesday a $4 trillion company, the first in history, NVIDIA. This was in March this year when Huang was hosting NVIDIA's annual developer conference, GTC 2025. You could call it the Super Bowl of AI. And when Huang proclaims that physical AI and robots are going to be the next biggest multi-trillion dollar industry, he's definitely not saying that lightly.

These machines will soon move amongst us through the world and not just model it. And Envidia is building the nervous system for that new world. But here's the bigger picture. Robotics isn't a cool frontier. It's part of a much larger. wave, one that's pushing Nvidia to a valuation of $4 trillion.

And this is not just a finance headline. This is Nvidia becoming the most valuable chip maker, the most important AI infrastructure provider, and possibly the backbone of the next industrial revolution. But there is one thing that's easy to miss.

Yes, these chips are being designed in California and fabbed in Taiwan, but the demand, meaning the scale, the developers, and the use cases, well, that's becoming more and more global. And India is emerging as one of the most critical nodes in that network. Whether it is training LLMs, automating warehouses, scaling cloud infrastructure, or scaling millions of engineers.

India is not just adopting AI. We are operationalizing it at a scale that few other countries can match. Which is exactly why Nvidia and companies like it, can't afford to ignore India anymore. We may not build the chips, but we could define what the chips are used for. Hello and welcome to Daybreak, a business podcast from the Ken.

I'm Snigda. And I'm Rahil. And we don't usually chase the news cycle, but today we are. Every day of the week, we come to you with one new story that is worth your time and worth understanding. Today is Friday, the 11th of July.

Just last year, Jensen Huang sat across Reliance Industries' Mukeshambani during Nvidia's first ever AI summit in India. He was dressed in his characteristic black leather jacket, and he addressed a rapt audience of tech founders, government officials and academics. India, he said, is just a couple years away from becoming a global powerhouse in AI development and delivery. Until now, India has exported software. Very soon he predicted it will be exporting AI.

That was exactly the kind of thing the room wanted to hear. But no one stood to be exported. benefit more from that vision than Huang himself. You see, this was no PR trip. It was purely strategic. At the same event, Huang and Ambani announced a new partnership between NVIDIA and Reliance to build AI infrastructure in India, everything from data centers to foundational models.

And Reliance wasn't the only one. During that visit, NVIDIA struck a flurry of partnerships across the Indian tech landscape. InfoSys, Tata, Tech Mahindra, Flipkart, each one part of a broader push to make India not just a buyer of AI tools, but a builder. Now, this was a smart move for everyone involved. Back in the US, Nvidia has increasingly had its back to the wall.

On one side, there's a growing list of challengers, companies like AMD, Intel, and a wave of other AI chip startups, all of which have been rushing in to fill the supply demand gap that NVIDIA itself created. But of course, it isn't just commercial pressure. The US government has severely restricted the export of its advanced chips to China, including the H-100 and even the cut-down H-20 chips that NVIDIA designed specifically to comply with earlier sanctions. Now, that's a big hit. The company is reportedly losing out on over $2 billion in potential revenue from the Chinese market alone.

Meanwhile, China has been doubling down on homegrown alternatives, the likes of Deepseek and Huawei's Ascent Chips. The goal is to build an AI ecosystem that doesn't rely on US tech. And they've been doing a pretty decent job of it. Back in January, Deepseek released its R1B3 AI model. And almost immediately, Nvidia shares plunged 17 to 18%, wiping out nearly $600 billion in market value in a single day. day. That's the largest single company loss in US stock market history. So now, Nvidia has its

site set on India. And of course, there is a lot for India to gain in this situation too, because it finally means we will have a foot in the door. India will get the infrastructure and skills it needs to compete in the global AI race. So in a world where doors are slowly closing, India's may just be swinging open. So what's India doing about it? And what's India doing about it? And holding it back. Well, stay tuned to find out. Hi, this is Rahel, the co-host of Daybreak. I'm quickly pausing this episode to share something very exciting with you. We are hiring. We are looking for someone in the early stages of their journalism career, maybe your fresh out of journalism school, or you've done a couple

internships and projects and are eager to take on your first full-time role in audio. I'm looking for a co-host to help launch a brand new podcast from the Ken. This is a full-time role, and you'll get to work closely with me as well as the rest of the audio team right from story pitches to interviews to shaping how the final show sounds. If you're curious, ambitious and absolutely love audio storytelling, we would love to hear from you. All the details will be in the show notes of this episode. It has been doubling down on building sovereign AI.

Earlier this year, the government announced a $1.2 billion AI mission, which was its most ambitious bet on artificial intelligence. till date. The issue, however, is that no one's quite sure about what it's meant to be. There is talk of setting up data centres, funding foundational models, upskilling talent and supporting startups. But there is no clear problem statement, no defined target, no articulated use case. Experts say that largely it has to do with the fact that it is driven by FOMO,

or the fear of missing out. New Delhi is under an immense amount of pressure, mostly self-imposed to show India has credible AI and it can exceed China's. We want to be taken seriously but we just don't seem to know how. But while the government throws things at the wall in the hopes that something, anything at all, sticks, Nvidia's India play is razor shop.

It's partnering up with some of India's most valuable companies and they're all using thousands of Nvidia chips to build LLMs. WIPRO recently said that it has trained more than 2 lakh employees on Nvidia's AI platforms. TCS meanwhile has trained 50,000 as AI associates. More than 5,000 developers in India have joined Nvidia's developer program. So, even before the government has figured out its policy, Nvidia has swooped in and is laying the foundation of India's burgeoning AI revolution. Is that a good thing?

Yes and no. But let us try to really understand why India is still struggling when it comes to AI. Because while there is a lot of buzz, there are still some serious gaps under the hood. Firstly, it is a very fundamental problem. India still isn't making the high-end chips that power AI. A great example of this is what happened to the big project between Vedanta and Foxcon. In 2022, Vedanta, which is an Indian mining and energy consumption, and Foxconn, the Taiwanese company which is best known for assembling iPhones,

announced a joint venture. They said that they would build India's first major semiconductor fabrication plant or what is commonly called a fab. The goal was to build a $20 billion chip-making facility in Gujarat. And it was being sold as a national milestone. A part of India's dream to reduce reliance on imports from Taiwan, China and Korea. But it fell through. Foxconn pulled out of the joint venture in July 2023, citing delays and challenges in execution.

Vedanta apparently lacked technical experience in chip manufacturing. And the Indian government reportedly rejected their funding application because the venture did not have a credible tech partner or proven technology licensing deal. Why this matters is because it was supposed to be India's big leap into the global semiconductor game. And its delay highlights the real challenges. of building a chip ecosystem here. You need to not just have money, but technology partners, experienced engineers,

and global supply chains. And even then, setting up a fab takes years, not months. Tata had plans too in Gujarat's Dolera, but nothing is moving there yet. So, we're still depending on countries like Taiwan and South Korea

to supply the brain chips. These are the ones that train AI models, run smart robots, power data centers. And without them, we can't really come. compete. And even when we do get access to these chips, they are expensive to use. Companies like AWS or Google rent out these powerful chips in the cloud. But it is costly. Forget about

start-ups, students, even universities being able to afford it. Think of it like this. Building AI today is like running a marathon. But in India, we don't have enough tracks. And the few that exist charge premium prices to run on them. And then there is another issue. We don't have our own core AI tools yet. The software that actually helps build AI systems is mostly coming from the US from companies like Nvidia, Google and meta. Imagine if you're building blocks, bricks, cement, even the blueprint came from outside.

You can still build the house, sure, but you're not in control. There are efforts underway like we mentioned earlier. The government is even working on something called India AI compute and we do have supercomputers like Param Siddhi. But these are early days and access is still limited. So yes, India has a talent. Yes, we also have the massive demand. But until we start building the base, our own chips, tools and infrastructure,

we will stay dependent. And in a world where AI is the next big global industry, that is a risky place to be. Nvidia has spotted that gap and is making the most of it. The upside is that they are laying down the building blocks of our AI industry, but the downside is that in the process, it may also end up becoming its gatekeeper. Daybreak is produced from the newsroom of the Ken,

India's first subscriber-focused business news platform. What you're listening to is just a small sample of our subscriber-only offerings. A full subscription unlocks daily long-form feature stories, newsletters and podcast extras. Head to the ken.com and click on the red subscribe button on the top of the Ken website. Today's episode was hosted and produced by Rahal Philippos and I Sinkda Sharma and it was edited by Rajiv Sien.