Even though only two people watch this show, we love doing it because it helps us understand the hidden meaning behind what people are actually saying. It makes us wonder—why would someone say that?
Welcome to Who Said What! Here, we take interesting comments from notable people, break them down, and dig into the bigger stories behind them. We’re working on improving the show and making it even better. 🙂
Today, we’ve got four interesting comments to share with you.
Are you working hard or hardly working?
So, you’ve probably heard this gem from L&T chairman SN Subrahmanyan: How long can you stare at your wife? Come to the office on Sunday. Work 90 hours a week.
Now I don’t get why people are mad at him. What’s wrong with this? Maybe just maybe he loses the staring competition with his wife. Also why, why the hell wouldn’t you want to spend your Sunday looking at PPT slides? Who wants to wake up late and spend a lovely time with their family—that sounds boring.
But jokes aside, he’s literally paid in crores. He has a vested interest, but expecting the same amount of dedication from employees, especially freshers, with a peanut salary seems a little unreasonable. Btw, the salary for a fresher today is still the same as it was 20 years ago.
Maybe he didn’t mean what he said. Maybe he just wanted to steal Narayan Murthy’s thunder.
Sam Altman knows the road to AGI
So, Sam Altman, the CEO of OpenAI, recently wrote in a blog post:
We are now confident we know how to build AGI as we have traditionally understood it.
Umm, I really don’t know what to make of this. Does he know how to build AGI? Will he ask GPT how to do this? When people talk about AGI, no two people mean the same thing, but loosely, AGI refers to machines that can think and act like humans. AGIs, like humans, can constantly evolve and learn from mistakes—just as we do. AGI would mean machines that could teach themselves calculus one day and become a world-class chef the next.
If he’s saying he knows how to build this, I’d take it with a pinch of salt. Maybe another fundraising round is around the corner. OpenAI has already raised billions, with a valuation of around $150 billion. And it’s not just them—Anthropic, the company behind Claude, is rumored to be raising $2 billion, while Perplexity AI recently closed a $500 million round, pushing its valuation to $9 billion.
The stakes are high because training models like GPT-4 cost over $100 million, and the next generation could easily cross a billion. It’s a costly game, and Altman’s bold claim might just be part of staying ahead in the AI race.
For decades, AGI has been more of a theoretical dream than a practical reality. Researchers have debated its feasibility, with skeptics saying it might take 50 or even 100 years to achieve.
Today’s AI is excellent at processing data—lots of it—but it’s clueless about how the real world works. For instance, if you tell an AI to make coffee, it wouldn’t understand that it needs to find a mug first, unless it’s specifically programmed to.
There’s still no consensus on what intelligence is. Is it just problem-solving? Does it include consciousness or self-awareness? How do we even measure if an AGI is truly “general”? These aren’t just academic questions—they’re foundational to whether AGI is even possible.
And while Altman’s claim is bold, it’s worth considering the broader conversation around AI’s limitations. This brings me to an interesting comment by economist Tyler Cowen in a podcast with Dwarkesh Patel. In the episode, Cowen points out a fundamental challenge:
“Humans. Here they are. Bottleneck, bottleneck.”
Cowen’s argument is rooted in the idea that even with advanced AI systems, human factors—our institutions, behaviors, and societal readiness—are often the real constraints. He explains that integrating technologies like AI isn’t just a matter of creating them but also navigating the social, political, and cultural systems that either enable or hinder their adoption. Even if AGI were built tomorrow, these human bottlenecks could slow its diffusion and impact for years.
I don’t know where Altman’s confidence comes from when he says he knows how to build AGI 🙂 While writing this, I came across this tweet:
Is Trump a little crazy?
Trump made the news again. I mean, that’s an everyday affair, but this particular thing caught my attention. He said he wants to buy Greenland. He also wants Canada and the Panama Canal.
When I first saw this headline, I just went, What the hell does he even mean? How can you just wake up one day and say something like this? I couldn’t make sense of the Canada thing at all, but the Greenland idea seems pretty interesting.
Interesting because that’s the only one where buying it makes some decent sense. This is based on my limited research on the topic, so my understanding will likely deepen as I read more in the coming days.
But here’s why the Greenland deal seems sensible.
Greenland isn’t just some barren ice-covered island. Sure, 80% of it is covered in ice, and only about 57,000 people live there, but this place is loaded with untapped potential. First, its location is gold. Geographically, it’s sandwiched between North America, Europe, and Russia, making it a critical spot for anyone who cares about Arctic dominance.
The U.S. already has a military base there—Pituffik Space Force Base—used for missile detection and space surveillance. But that’s just scratching the surface of its strategic importance.
The Arctic is melting, and while that’s bad for the planet, it’s changing global trade routes. The Northwest Passage, once blocked by ice, is now opening up, creating faster shipping paths. Greenland sits right at the entrance to these routes, making it a key location. On top of that, the Arctic is becoming a battleground for power, with the U.S., Russia, and China all competing for control. Owning Greenland, or having more say over it, would give the U.S. a big advantage.
Then there’s the question of what lies beneath the ice. Greenland has vast reserves of rare earth minerals—43 out of the 50 minerals deemed critical by the U.S. government.
These minerals are essential for making everything from electric vehicles to advanced military tech. In short, they’re the stuff that keeps the modern world running. There’s also a massive amount of oil—an estimated 52 billion barrels sitting offshore.
Now, Greenland banned oil exploration in 2021, but with the world’s insatiable thirst for resources, who knows how long that policy will hold?
Economically, Greenland is a mixed bag. Its annual GDP is just $3 billion, which is tiny—roughly a seven-thousandth of America’s GDP. Denmark, which technically owns Greenland, spends about $500 million a year just to keep things running there. The largest industry? Fishing. That’s not exactly what you’d call a thriving economy.
This is where Trump’s deal-making mindset might be onto something. Buying Greenland could theoretically benefit both the U.S. and Greenlanders. For Denmark, which already has limited military resources in the Arctic, this could mean getting rid of a financial and strategic liability.
Greenland isn’t a colony Denmark can sell off at will. It has significant autonomy and controls its natural resources, so any deal would require Greenlanders’ consent. While they’ve entertained thoughts of independence, they know managing a resource boom could overwhelm their small population, leading to challenges like corruption and inequality. Imagine a tiny town handling Saudi-level oil wealth—it’s that kind of scale.
Trump’s approach—threatening military force or tariffs—only alienates the people he needs on board. Greenlanders value respect and autonomy, not coercion. If this deal were ever to happen, it would require making Greenlanders enthusiastic partners by offering a future they genuinely believe is better.
For now, the idea feels like one of Trump’s headline-grabbing stunts. But Greenland is more than a quirky proposition—it’s a geopolitical and resource goldmine where Arctic dominance and future security intersect.
People not migrating to cities is a good thing?
Recently, Kashish and Pranav from the team wrote about migration in The Daily Brief, our daily show. Migration—its causes and consequences—turned into the topic of the day for us at the office. What kicked off this topic was an intriguing commentary by Dhananjay Sinha, Head of Research at Systematix Group. He raised some fascinating, and frankly, less obvious questions about the decline in migration—questions that challenge the conventional narrative. Questions that are not obvious but should be asked.
But before I dive into it, let me first explain what migration actually means.
Migration, at its core, is about movement—usually from rural areas to urban centers, driven by the hope of better job opportunities, higher wages, and improved living standards. But in recent years, a new trend has emerged: migration declining. The reasons for this shift are far from clear-cut, which is what makes it so intriguing.
The Economic Advisory Council to the Prime Minister (EAC-PM) recently published data suggesting that rural India is doing quite well. Their study, titled ‘400 Million Dreams!’, found that rural-to-urban migration had dropped significantly—by 53.7 million people, or 11.8%, over the past decade.
Now, that sounds like really good news, right? People aren’t migrating to cities—maybe because rural areas are doing extremely well?
That’s what the EAC-PM attributed this decline to: improved government services in rural areas, like better healthcare, education, infrastructure, and connectivity, which they believe are giving people fewer reasons to leave their hometowns.
It’s a comforting hypothesis—the idea that rural India is thriving and people are staying back because they no longer feel the need to flock to overcrowded cities for survival.
But Dhananjay Sinha isn’t entirely convinced. He argues that this narrative might be oversimplifying the situation. In his view, the story of reverse migration might not be about rural abundance at all. Instead, it could reflect something more concerning: the diminishing appeal of urban centers.
Let’s look at some of the data. The EAC-PM study highlighted that remittances—money sent home by migrants—have declined in many states like Bihar, Uttar Pradesh, and Madhya Pradesh, which are traditionally known for outbound migration.
Fewer remittances might mean fewer people leaving in the first place, challenging the idea of thriving rural economies. It suggests that people may not be staying back because they’re finding great opportunities in rural areas, but because cities are no longer the magnets they once were.
Sinha also points to stagnating urban growth as a possible factor. Urban centers, which once symbolized opportunity and upward mobility, are now grappling with slowing economic activity, rising costs of living, and limited job creation. Combine this with the rise of automation and the effects of the pandemic, and you have a scenario where urban India might not seem worth the risk for many rural workers.
And if rural areas were actually becoming more attractive, rural wages would be growing much faster. But looking at the data, rural wage growth is barely keeping up with inflation. So, it’s unlikely that people are staying back because of decent opportunities in rural areas—rural wage growth paints a very different picture.
And then there’s the question of rural infrastructure. The EAC-PM cites government programs like rural electrification and the Pradhan Mantri Awaas Yojana-Gramin as key drivers of reverse migration. But Sinha points out that these developments, while important, don’t fully explain the trend. For instance, 86% of rural India was already electrified by 2001, long before migration trends began reversing. Similarly, while the PMAY has added millions of houses in rural areas, the growth rate of these projects hasn’t been as transformative as one might expect.
So, what’s really going on here? The truth probably lies somewhere in between. But nobody can really say why the rural-to-urban migration is declining.
That’s it for this edition, do let us know what you think in the comments and share with your friends to make them smarter as well.