Three Warnings: From Your Diet to Your Future to The Dollar | Who said What #24
Hello, I am Krishna and welcome to the 24th episode of Who said what? I’m Krishna and this is the show where I dive into interesting comments by notable figures from across the world—whether it’s finance or the broader business world—and dig into the stories behind them.
Today I have 3 very interesting comments for from our Chief economic advisor on junk food, Google’s Head of AI and finally Sanjeev Prasad of Kotak.
Our Chief Economic Advisor on junk food
At a recent CII conference, India’s Chief Economic Advisor, Dr. V. Anantha Nageswaran, made a statement saying:
“Combination of ultra-processed foods and screen time is a huge risk for demographic dividend”
He also said that CSR is not just about spending 2%, but it's integrating practices. He spoke about a bunch of topics but this is something that stood out to me. Plus, we couldn’t find an official video of this talk.
Coming back, his warning was clear: if we continue to ignore what we’re feeding our people — both in terms of food and attention — we may lose out on the very advantage India is counting on to power its future.
What’s the demographic dividend, and why does it matter?
India has a young population. Over half of our people are under 30. In theory, this should be a huge advantage — more workers, more productivity, more growth. That’s the “demographic dividend.”
But a dividend is only useful if you can cash it. And for that, young people like you and me need to be healthy, educated, and employable. What happens if we aren’t?
That’s what Nageswaran is worried about.
He pointed out that we’re not just in a race to meet economic targets like “Viksit Bharat by 2047” We’re also in a race against the hidden costs of modern life — the kind that don’t show up in GDP data until it’s too late.
What exactly are ultra-processed foods — and why is the CEA talking about them?
Ultra-processed foods are products that are far removed from anything natural. Whether it’s the sugary breakfast cereals, packaged chips, frozen ready-to-eat meals, basically food that never really rots. These foods are loaded with added sugars, fats, salt, preservatives, and chemicals — all designed to enhance taste, shelf life, and appearance.
And they’re everywhere.
At the CII meet, Nageswaran wasn’t just worried about rising obesity or diabetes — though both are real concerns. He was connecting this food trend to something bigger: productivity. If the youth of India are eating empty calories and spending hours glued to screens, they won’t be healthy enough — physically or mentally — to sustain a growing economy.
This isn’t a one-off comment — it’s part of a broader theme
He has mentioned this issue more than once. In the Economic Survey released earlier this year — the government’s flagship economic report — the section on health and nutrition flagged rising processed food consumption and its links to non-communicable diseases (like heart disease and diabetes).
I came across a chart from Data for India showing that while the overall calorie intake in rural India has stagnated, the share of packaged and ultra-processed foods has risen dramatically — especially in urban areas.
You can literally see the shift in how India eats: from cereal and pulses… to salty snacks, sugary packaged food. And this isn’t just a nutrition story — it’s an economic one.
Because when a young population starts to eat like an aging, urban one, you can’t expect it to power a manufacturing boom or compete in high-performance sectors.
And it’s not just the CEA — even FSSAI is stepping in
I also came across this news that India’s food safety authority — the FSSAI — issued a new advisory asking food companies to stop using the phrase “100% pure” on their packaging and promotions. Why? Because that claim can be misleading.
In a world where brand labels shout words like “100% real,” “natural,” or “wholesome” — even on products that are heavily processed — the regulator is pushing back. The move signals that the government is slowly waking up to how branding and packaging are shaping food choices, especially for children and teenagers.
What the CEA is saying is: it’s not enough to build factories, raise capital, and chase export targets. If we ignore what our youth are consuming, we might end up with a generation that’s chronically unhealthy — and that’s a drag on the economy no one wants to talk about.
The beautiful mind of Demis Hassabis
After spending a couple of years playing catch-up with the likes of OpenAI, it seems like Google’s finally confident in its own AI abilities. They made a series of frankly ridiculous announcements at their recent I/O conference — including the truly insane Veo3 (here are some samples of what it can do, and they’re bonkers).
And with these breakthroughs, Google has gone on a bit of a PR blitz. And in this case, that’s a fantastic thing, because it gives us the chance to hear from Demis Hassabis, the man behind Google DeepMind, the company’s AI arm.
Demis is worth listening to. See, DeepMind didn’t start chasing AI yesterday — it’s been on the ball for the last 15 years, and it has catalysed large parts of the ecosystem that’s now exploding all around us. Many of the foundations of the magic you’re seeing around you today began at the lab. He even won a Nobel Prize for his work. We’re not talking about someone that’s caught the latest trend, but someone who’s life’s work has become the latest trend.
We’ll look at a single interview today — one he gave to the Hard Fork podcast.
It isn’t the only one around. You should go and watch his other stuff. But there’s enough in this single interview alone to leave us interested.
For instance, we’ve often wondered why we haven’t seen an explosion of AI products, aside from the models that all the major labs are using. It’s clear that basic chatbots are nowhere near the limit of what you can do with AI — in the same way that emailing people is nowhere close to the limit of what the internet is useful for. But then, why aren’t we seeing all those new use-cases pop up? Here’s Demis:
“I think one of the challenges of this space is the underlying tech is moving unbelievably fast. That’s quite different even from other big revolutionary techs like the internet or mobile, where at some point you get some sort of stabilization of the tech stack, and then the focus can be on product—on exploiting that tech stack. What we’ve got here, which is unusual but also exciting from a researcher perspective, is the tech stack itself is evolving incredibly fast, as you guys know.
That makes it uniquely challenging on the product side—not just for us at Google and DeepMind, but for startups, for anyone really, small or large. Where do you bet right now, when that could be 100% better in a year, as we’ve seen?
So you need deeply technical product people, designers, and managers who can intercept where the technology may be in a year. You want to design a product that’s going to come out in a year, so you need a deep understanding of the tech and where it might go to figure out what features you can rely on.”
Imagine you’re trying to build a car. Right now, the best engines available are close to what ran a Ford Model T a century ago. In a year’s time, however, even mediocre engines will be as good as anything inside an F1 racecar. How would you even start designing your car? Even the basics, like getting the right tires in place, or finding the right coolant, would be a multi-year R&D process.
That’s what we’re seeing with AI. The engine of any AI product — the foundational model at its core — is evolving too fast for products to keep up.
There’s another thing at play: something like the internet was, by and large, a communications technology. Any use case you were trying to develop required extremely specific scaffolding — which you would have to code into place. AI, on the other hand, is a general purpose technology. Extremely diverse problems could require the same ‘intelligence’. As Demis explains:
“How are these things related, other than the fact that I’m interested in all of them? That was always the idea with building general intelligence — truly general. The way we’re doing it should be applicable to almost anything, right? Whether that’s productivity — which is very exciting and can help billions of people in their everyday lives — or cracking some of the biggest problems in science. 90% of it, I’d say, is the underlying core general models — Gemini, especially 2.5.
In most of these areas, you still need some applied research, some special casing from the domain, maybe special data, whatever it is, to tackle that problem. Maybe we work with domain experts in the scientific areas. But when you crack one of those areas, you can also put those learnings back into the general model, and the general model gets better and better.
So it’s a very interesting flywheel.”
In the new world we’re stepping into, even if you need to develop specific AI for some narrow use case, you can just feed its learnings back to the general model, making it even better. What does the internet look like, in this new era? Do we eventually just have a handful of super-apps that can do everything you might ever imagine? Who knows.
Demis, at least, is gearing up for Artificial General Intelligence — which is the sort of stuff you see in the most futuristic sort of science fiction.
But what does this look like? Are we even close to getting there? Broadly, even Hassabis doesn’t know:
“... there’s uncertainty about how many more breakthroughs are required, and about the definition of AGI. I have quite a high bar for AGI, which I’ve always had. For me, AGI should be able to do all of the things the human brain can do — even theoretically. That’s a higher bar than what the typical individual human could do, which is obviously very economically important and would be a big milestone, but in my view, not enough to call it AGI.”
Basically, it’s a computer that’s capable of everything a human mind is theoretically capable of. Emphasis on “theoretically”. AGI isn’t a question of what you see the average person around you doing. Everything that you’ve ever heard anyone do — all the weird leaps that the greatest brains we’ve ever known can make, from Einstein, to Picasso, to AR Rahman — would potentially be possible for a computer.
Meanwhile, computers will still do all the things they’re already better than us at — from instantly solving complex mathematical problems, to digesting large datasets, to keeping tabs on thousands of sensors at once.
What do we need to get there? Demis talks about two things:
“... true out of the box invention and thinking — sort of, inventing a conjecture rather than just solving a math conjecture. Solving one's pretty good, but actually inventing, like, the Reimann Hypothesis or something as significant as that, that mathematicians agree is really important, is much harder.
And also, consistency. Consistency is a requirement of generality, really. It should be very very difficult for even top experts to find flaws, especially trivial flaws, in the systems — which we can easily find today.”
How do we get there? DeepMind is trying out something called “evolutionary programming”. What’s that? Demis explains:
“So it's basically a way for uh systems to explore new space. Like, what things should we, in genetics, mutate to give you a kind of new organism. You can think the same way in programming or in mathematics. You change the program in some way, and then you compare it to some answer you're trying to get. And then the ones that fit best, according to some sort of evaluation function, you put back into the next set of generating new ideas.
We have our most efficient model — sort of flash model — generating possibilities, and then, we have the pro model critiquing that and deciding which one of those is most promising to be selected for the next round of evolution.”
Let us give you a second to decode that. All biological life you see, and everything it can do — from the human brain, to bird’s wings, to the trunk of an elephant — was created through evolution. This is a powerful process — it’s capable of creating completely new ways of being. That’s what DeepMind is now trying to create new kinds of intelligence.
And it’s doing that using AI itself. It’s letting AI imagine completely new ideas around how AI might function. And it’s using AI to test them. If there’s something that shows genuine promise, it stays. All other ideas are binned. Basically, DeepMind is beginning to create a body of all sorts of new, interesting ideas on how AI can run, which are proven to work — and this whole process is now automated.
That is, in short, how you get to an intelligence explosion.
There’s a lot more in here that we could go into — from what AI does to your job, to what a kid today should do to prepare for an AI world. We recommend you check all of it out. It’s a crazy world we’re going into, and trying to anticipate the changes coming your way is perhaps the best thing you could do for yourself.
Sanjeev Prasad on US yield and the dollar
Sanjeev Prasad, MD & Co-Head of Kotak Institutional Equities, recently said something in a their research report about US bond yields and the dollar.
He’s basically saying this: The US is dealing with its own mess i.e. rising yields and a ballooning deficit but if the dollar starts to wobble, it’s not just America’s problem anymore. That becomes everybody’s problem.
So let’s take this line by line. Let’s break down what’s really going on here and try to understand what he’s saying.
US bond yields are rising—but that’s mostly America’s headache
Let’s start with bond yields.
Every time the US government wants to borrow money, it issues a bond. Investors buy these bonds, essentially lending the US money in return for a fixed interest rate. That interest rate—the “yield”—is the “US bond yields.”
Now lately, these yields have been rising fast. Why?
Sanjeev points to two things:
One, the US has been running up a massive fiscal deficit—it’s spending way more than it earns in taxes, so it needs to borrow more and more. That means more bonds are being dumped into the market.
Two, there's growing uncertainty about where the US economy is headed: Is inflation really under control? Will the Fed cut rates anytime soon? What if growth slows but inflation doesn’t drop? You never know what Trump might say next.
When investors start to worry, they ask for higher returns to lend money. So the yield on US bonds climbs.
Now here’s the key bit: this rise in bond yields is mostly a US problem. Because higher yields mean the US government will now have to pay much more interest on new debt. Over time, that will blow a huge hole in the federal budget. Sanjeev even hints that this will affect the US’s “fiscal and debt position,” especially since older bonds at lower rates are maturing and being replaced with costlier ones.
It’s a bit like someone with a huge home loan suddenly seeing their EMI shoot up when their fixed-rate deal expires. That stress lands squarely on their own plate.
So rising bond yields?It’s a problem for the US. But for the rest of the world? Maybe not just yet.
But the Dollar Index (DXY)? That’s everybody’s problem
Now, here's where things get interesting.
While US bond yields are largely the US’s own headache, there’s another metric that’s much more contagious: the DXY, or the US Dollar Index.
This is a number that tells you how strong the US dollar is compared to a basket of other major currencies—mainly the euro, yen, pound, and a few others. When DXY goes up, it means the dollar is flexing its muscles. When DXY falls, the dollar is losing strength.
Right now, DXY is still strong. But Sanjeev is warning: if it starts to fall meaningfully, the entire global financial system may need a reset.
Why does this matter?
Because for years now, the dollar has acted as a global vacuum. Countries like China, Japan, and the oil-rich Gulf states—basically the big savers of the world—have been pumping their surplus money into the US. They bought trillions worth of US Treasury bonds. They funded America’s debt addiction. And in return, they got stability, liquidity, and predictable returns.
We have spoken about this a bunch of times on The Daily Brief and on this show about how US dollar became the world’s reserve currency.
But what if that story is starting to crack?
Sanjeev argues that the dollar’s strength has been hiding how shaky the US economy really is. It still enjoys “haven” status—that is, in times of trouble, investors still trust the dollar and pile into it. But if DXY starts sliding—either because the US economy weakens, or because the world begins to question the long-term sustainability of US debt—that illusion breaks.
And when the dollar loses its grip, the consequences spill everywhere.
How a falling dollar reshapes the entire global money map
Here’s how Sanjeev lays it out.
If DXY starts declining sharply, three things could happen:
Global investors—especially from outside the US—reduce buying US assets. Imagine you're a foreign fund manager holding a bunch of US stocks or bonds. If the dollar falls, your investment loses value when converted back into your own currency. You might start thinking: why take the risk? Why not invest in markets closer to home or in assets that don’t carry currency losses?
Foreign holders of US assets might see actual losses. For example, suppose a Japanese pension fund owns US bonds. If the dollar weakens against the yen, even if the bond pays good interest, the yen value of that bond drops. That’s a real capital loss. This might trigger selling.
Global capital flows might shift direction altogether. For decades, money has flowed into the US—because of safety, strength, and returns. But if confidence drops, that flow might slow or even reverse. More capital might go into Asia, Latin America, or commodity-rich regions.
To use an analogy: imagine the US was a massive magnet pulling in money from everywhere. If the magnet weakens, those metal bits (global capital) start drifting away. That’s what Sanjeev is flagging.
And what about India?
Now comes the part that hits home.
Sanjeev and his team say that rising US yields may not immediately affect the RBI’s monetary policy decisions. India’s bond yields, for now, are holding steady. Inflation is under control. The rupee, while weak, hasn’t collapsed. And India’s current account deficit—while rising—isn’t at panic levels yet.
But if DXY falls, India will be affected in complicated ways.
Let’s unpack that.
India depends heavily on dollar-based trade. We import most of our oil and a lot of electronics and raw materials—all priced in dollars. So the USD-INR exchange rate matters a lot.
Now imagine the dollar weakens globally, and the rupee doesn’t strengthen proportionally. That could mean India’s real exchange rate (REER) becomes misaligned. Our goods might look more expensive to foreign buyers. Exports could suffer.
Or flip the scenario. If the rupee does strengthen in line with the dollar’s fall, some exports become less competitive anyway, and importers gain. But that puts pressure on domestic manufacturers.
The larger point is: a resetting dollar changes the global pricing system. India, like everyone else, will have to adapt.
Sanjeev gives some comfort here. He points out that India has three key buffers:
A “lowish” current account deficit and healthy foreign exchange reserves.
Reasonable inflation.
A “fair” INR value when you look at it through the REER lens—meaning, the rupee isn’t wildly overvalued or undervalued.
Please let me know if you have any feedback :)
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