Arvind's Newsletter-Weekend edition

1.Auto major M&M shifts to high gear with Rs 37,000 crore investments

Automotive major Mahindra & Mahindra (M&M), which is readying to launch nine sport utility vehicles (internal combustion engine/ICE), seven Born Electric Vehicles (BEVs), and seven light commercial vehicles by 2030, has outlined an investment of Rs 27,000 crore in its auto business between 2024-25 (FY25) and 2026-27 (FY27).

Over the next three years, the company will deploy Rs 37,000 crore, including its auto business, farm business (Rs 5,000 crore), and service business (Rs 5,000 crore).The M&M board has approved an investment of Rs 12,000 crore in its electric vehicle (EV) arm, Mahindra Electric Automobile (MEAL), to fund the EV journey over the next three years.

The Mahindra Group chief executive officer Anish Shah, said the demand of the recently launched XUV 3XO would be met by a combination of the vehicles already manufactured and capacity expansion from the current 9,000 vehicles to 10,500 vehicles, which will need marginal investment and less time. As of May 15, XUV3XO had over 50,000 open bookings, according to an investor presentation.

2.Inside the BJP’s WhatsApp machine

As nearly a billion people vote in India’s elections, there’s one platform many turn to for information: WhatsApp. With nearly 400 million active users across the country, WhatsApp is a critical channel for politicians to get their message out. And no one does it better than the Bharatiya Janata Party, led by Prime Minister Narendra Modi. 

In partnership with the Pulitzer Center on Crisis Reporting and Digital Witness Lab, Rest of World spent several months in northern India to explore how the BJP turned its WhatsApp strategy into an election-winning machine. Just in Mandi, a tiny Indian town with a population of 26,000, party volunteers run a network of more than 400 WhatsApp groups. Our analysis of thousands of messages sent in these groups shows how India’s ruling party is able to maintain a sophisticated operation on WhatsApp, and optimise its political campaign on the platform far away from public scrutiny.

3.Countries are tightening visa rules for students

Until recently, Canada was the country to go to for a large number of Indian immigrants. A number of them headed there in search of quality education, stayed on to work and eventually became citizens of that country. 

That pipeline is drying up. Indian student applications to Canadian universities fell by more than 40% in 2024 after the country limited the international students’ quota by 35%. That’s not the only reason. A shortage of accommodation and a doubling of the guaranteed investment certificate, which is obtained from Canadian banks, to Rs 12 lakh (C$20,635) are dampeners too. The banks usually issue the certificate against a deposit of a like amount. It is meant to ensure that the students have the means to sustain themselves for the duration of their course.

Visa uncertainty is not limited to Canada. Students headed to the US, UK and Australia are also facing tighter entry norms. Last week, Australia steeply hiked the financial capacity requirement to ~Rs 16.3 lakh (A$29,710). 

4.The number of people dying or becoming seriously ill worldwide from lifestyle- and age-linked diseases has risen 50% since 2000. 

It’s a grim statistic that hides good news, largely a result of people not dying of infectious disease or as part of childbirth, so they live long enough to develop high blood pressure or diabetes. Researchers also predicted that global life expectancy will rise by five years by 2050 to over 78, driven especially by a 9.2 year jump in sub-Saharan Africa.

Global healthcare services will have to redirect resources from communicable diseases to dealing with the problems of aging and lifestyle.

5.Art critic Jerry Saltz of New York Magazine: A “Francis Bacon of AI art” will emerge, but today’s work falls flat

Harsh criticism aside, Saltz isn’t saying that AI art has no future. Rather, he thinks contemporary AI art is superficial, derivative, and overhyped — qualities that may change as the space matures. “Art takes a long time,” Saltz told Big Think.
“Painting is still emerging and it’s been with us for 40,000 years.” So, while we may someday see a Francis Bacon of AI art, the space is currently churning out work that functions like a Norman Rockwell painting, which, according to Saltz, tells “you exactly what to think and feel.”

6.Microsoft’s emissions jump almost 30% as it races to meet AI demand

Microsoft’s carbon emissions jumped almost 30% in three years despite efforts to go carbon negative by 2030. The software giant has invested hugely in artificial intelligence and cloud computing, which require energy- intensive data centres to run, Microsoft said in its annual sustainability report. The company’s direct emissions fell 6% between 2020 and 2023, but its supply chain — the manufacture of chips and data centres — accounts for most of its carbon footprint.

Microsoft said it would require “high volume” suppliers to use carbon-free electricity and would invest $10 billion in renewable energy projects to keep its AI goals in line with its climate targets.

7.New Zealand’s sheep-to-people ratio fell again in 2023

NZ’s sheep population continues to dwindle, with new data released by Stats NZ in early May revealing that the nation’s total number of sheep fell by 3% to ~24M for the year ended June 2023. That’s roughly half the figure recorded two decades ago, and 65% less than in 1981, when there were ~22 sheep for every resident. And, as the country’s human population boomed to more than 5.2M in 2023, the country’s sheep-to-people ratio has been sheared to just ~4.6.

8.Big tech’s capex splurge (on Gen AI) may be irrationally exuberant ; The Economist

From the 19th-century railway mania to the telecoms boom at the dawn of the internet age, cautionary tales abound of over-investment in infrastructure fuelled by excitement over a new technology. With the rise of generative artificial intelligence (ai), history is repeating itself. In recent weeks four tech giants—Alphabet, Amazon, Meta and Microsoft—have pledged to spend close to a total of $200 bn this year, mostly on data centres, chips and other gear for building, training and deploying generative-ai models. That is 45% more than last year’s blowout. Tech barons such as Meta’s Mark Zuckerberg admit that it may be years before this investment generates returns. It is an ai arms race.

The tech firms are not only buying infrastructure. In the past few years they have joined a stampede to put venture capital (VC) into OpenAI, Anthropic and other makers of foundational models. Traditional vc firms bellyache that they have not seen such corporate big-footing since the dotcom boom. The tech giants are flush with cash—they can afford to splash out. But, if the past is any guide, a bust is coming and the firms carry such weight in the stockmarket that, should their overexcitement lead to overcapacity, the consequences would be huge.

History is illustrative. In the early days railway track was laid for locomotives that were soon superseded by more powerful ones. As the rolling stock grew heavier, lines had to be replaced with sturdier stuff. During the 1990s telecoms firms increased capital expenditure by three-and-a-half times and laid 600m km of cable, according to Morgan Stanley, believing that people would be willing to pay high fees to go online. But users thought the internet should be free. The bank draws an analogy with today’s data centres, which may be ill-equipped to cope with increasingly powerful graphics-processing units, the chips used to train and run generative ai. The tech giants’ assumptions about people’s willingness to pay for chatbots and other whizzy “gen-AI” tools may be just as misplaced.

All the signs are that big tech has succumbed to irrational exuberance. Runaway spending is one of the risks. Wall Street is already pencilling in expectations that the four firms’ capex could come to an eye-popping $1trn over the next five years (Apple is taking a more cautious approach). Revenues may rise as a result, but so will costs. These include juicy salaries for brilliant engineers and mammoth electricity bills for data centres that can handle the heavy demands of generative ai. Even now, investors are lukewarm about such gambles. In recent weeks they have applauded Google’s capex plans but thrown cold water on Meta’s. Given the way Mr Zuckerberg and others have blown money on Pharaonic projects before, they have good reason to be jittery.

Another risk is that models will be commodified. The cloud-computing “hyper-scalers”, namely Alphabet, Amazon and Microsoft, have built and invested in large proprietary ais that are considered state-of-the-art. They also run smaller, open-source alternatives, including those made by Meta, which are getting better and cheaper. Hugging Face, a hub for ai enthusiasts, lists more than 650,000 models. The more market share these take from the large proprietary models, the lower the likely returns on investment.

A last risk is that scale brings diminishing returns. With more computing power and data, the giants’ models are getting bigger. But nobody should assume that they will get proportionally better as more money is thrown at them. On May 13th Openai launched a new version of its GPT-4 model, called GPT-4o. It is faster and its linguistic skills mean that you get more chat for your GPT. But it was not the brand new GPT-5 that some wonks had hoped for. Will ever-bigger models pass the bang-for-the-buck test?

As in any arms race, the driving force behind the spending is as much defensive as offensive. None of the four wants to be left behind, lest it fall victim to disruption. Fortunately, the damage to society at large is likely to be limited. As with railway tracks and telecoms cables, overcapacity makes things cheaper. In many infrastructure booms, the benefits accrue to the users more than to those who lay the foundations. Do not be surprised if that happens again.