We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 20 April 2025:

1. The Growing Risk to Fed Independence That Wall St Isn’t Watching (Transcript here) – Tracy Alloway, Joe Weisenthal, and Lev Menand

Lev: I think something big is happening in the federal government right now where the President is asserting unprecedented powers over parts of the government that for – in some cases – over a century have operated with a certain amount of separation from presidential day-to-day direction. That threatens to upend government policy across a range of dimensions but in one area in particular, the consequences could be felt immediately, and that is with respect to the Federal Reserve.

Joe: Certainly the firing of the two minority commissioners at the FTC, almost immediately after we recorded that episode were news, I don’t think people on Wall Street really – “Okay, something about mergers” – that’s not high on their radar. What is the connection between the FTC or that action and something that could happen with the Federal Reserve?

Lev: Let me tell you why that FTC firing was a particularly big deal. There is a supreme court case on the question of whether the President can fire commissioners on the FTC without cause, the way Trump asserted the power to do the other day, and that is the bedrock precedent that protects the Federal Reserve. It’s called Humphrey’s Executor. It was decided by the court in 1935 and it reigned in and largely reversed, or cabinet to its facts, a famous decision from 1926 called Meyers vs. The United States that President Roosevelt – FDR – had relied on to try to fire a member of the FTC and the Supreme Court in 1935 said, “Nope, you can’t do that. That case isn’t going to stand for that anymore.” We’ve built up a whole system of government around this understanding and here Trump is inviting the Supreme Court to overrule this bedrock precedent.

Tracy: Since we already went back in time to 1935 and 1926, can we go even further and talk about why we have independent agencies at all? I guess the clue is in the name “independent agencies” but they have some oversight clearly, so who is actually watching over these independent agencies and why do they exist?

Lev: All the constitutional actors oversee the independent agencies. Independent agency is a technical term of art in law to refer to an agency whose heads cannot be removed by the President at pleasure. They include any officer of the government who is not a legislative officer, a member of congress elected or a judicial officer, an appointed Article 3 Judge. All of those officers, some of them can be put into a category of they’re part of an executive agency, the head of that agency can be removed by the President at pleasure, or an independent agency, the head of the agency cannot be removed by the President at pleasure.

In that second category, independent agencies, they’re accountable to the President, to the courts, to the Congress, in all sorts of different ways. The President appoints the heads of independent agencies with the advice and consent of the Senate, the President can remove the heads of independent agencies, but generally only for cause. Sometimes those causes are specified, like neglect of duty or malfeasance in office, we could talk about that. In the Federal Reserve Act, the statute just says “cause” and a for-cause removal involves notice and a hearing, so it’s not the same thing as an at-pleasure removal. It precludes the President from removing somebody for a policy disagreement. The independent agencies are accountable to Congress in that there are hearings that are held. Officers have to go down, just like Jay Powell goes down and testify, they’re subject to Congress’s subpoena power for records, they’re implicated in all the workings of the government and their actions, like the FTC’s actions, are subject to judicial review by Article 3 judges. So they’re not independent in this sense that’s sometimes asserted that they’re a fourth branch of government, or they’re outside of the government. No, they’re just a type of government body that has a different relationship to the President from the Secretary of Defense or the White House Chief of Staff, which are positions where the President can fire or direct the actions of that officer.

These sorts of positions have been around going all the way back to the founding. With respect to monetary policy, it was a question for the first Congress and the first Secretary of the Treasury, how much direction monetary policy should be subject to day-to-day oversight or direction by the President. This issue isn’t a new issue for the United States, it’s there right at the beginning…

…Lev: What are the possible exceptions that would allow the logic of Humphrey’s Executor to maybe apply to the Fed even if it no longer applies to the FTC? The one that the Trump Administration is running with so far is that monetary policy is somehow not sovereign executive power and can be distinguished from the other stuff the Fed does, and that stuff is regulation of financial institutions. Trump put out an executive order last month, Executive Order 14215, which asserted executive power over all the independent agencies and included specific carveout language for the Fed that said “This order doesn’t apply to the Fed with respect to its monetary policy, only with respect to its regulation and supervision of financial institutions.”  This is the Trump theory. There’s some other options we can get to, but I think let’s maybe think through Trump theory – does this make any sense?

There are some huge problems with this theory. It suggests that they haven’t spent a lot of time thinking about how the Fed conducts monetary policy and what the relationship is between monetary policy and the regulation of banks, because it’s really all one and the same thing. The court would be hard-pressed to say, for example, just as an initial matter, Jay Powell can’t be removed by the President with respect to what he’s doing on monetary policy but with respect to what he’s doing on bank regulation, the President could fire him for a policy disagreement. That would just fall apart pretty easily. What type of independence is really left? The president could just say “I fired him because I don’t like what he was doing on bank regulation,” and the real reason could be that he didn’t like what Jay Powell is doing on interest rates. But how would we know, because he doesn’t need to give a reason, except to say that it’s bank regulation. So there’s already a problem.

But the deeper problem is monetary policy implementation is bank regulation. In January when the Fed met, in the aftermath of that meeting, the board of governors amended Regulation D through a rulemaking published in the federal register lowering the interest paid on reserve balances to banks with reserve accounts at the Federal Reserve banks. It is a straight exercise of regulatory power, just like when the SEC writes a rule for what type of disclosure a company has to do if it’s a publicly traded company. They just don’t seem to realize this. They think that it’s like the FOMC just meets and they talk and then they announce a decision and that’s monetary policy, it’s not regulatory, it’s not adjudicatory. But actually, monetary policy implementation is all exercise of government power over the banking system.

2. Ukraine research excursion – what did I find? – Swen Lorenz

Visiting Kyiv, Ukraine’s capital, is not actually all that difficult, even under the current circumstances.

Anyone with a decent passport can head there by bus, train or car (for obvious reasons, no commercial flights are currently operated). No visa is required to enter Ukraine…

…You’ll have noticed just how vast Ukraine’s landmass is. Gleaning out of the train window to see mostly nothing, you start to understand how much space the country has relative to its population size.

You are also in for a few surprises. Who knew customs control officers in a war-torn country can be as friendly as the ones checking entrants to Ukraine?…

…Indeed, stepping out of Kyiv-Pasazhyrskyi railway station and driving across the city centre to my Airbnb apartment just off Independence Square, I couldn’t help but remember my trips to Russia in the early 2000s (or to Serbia in 2018 before that country took off for a belated round of rapid growth). There is a palpable sense that Kyiv never developed to quite the extent that other nations in the region did.

It was also striking how life went about seemingly entirely normal, at least during the day.

Kyiv gets into the Western news when it gets hit by missiles or drones, but as the saying goes, a house that isn’t on fire isn’t news.

I was also a bit lucky, as I did not have a single air raid alarm until my fourth day in town. By that time, I had learned that most people nowadays ignore these alarms…

…Kyiv does get hit by strikes, and people get hit. However, the city is about 300 km (190 miles) from the front line, it now has strong air defences, and strikes are relatively few in number relative to the size of the city. Human beings adapt, and even in a country that is at war, life has to continue somehow. Even now, companies in Kyiv are doing deals, residents refurbish homes and apartments, and some splurge on living the good life.

As I learned by speaking to a broad range of decision-makers, experts, and business leaders, Ukrainian companies and investors are currently reinvesting their profits in Ukraine – for lack of other options.

Refurbishment of real estate continues in some places, but it’s suffering from a labour shortage caused by the military mobilisation and the large number of men moving abroad. Large-scale residential development projects have mostly come to a halt…

…Before the war, foreigners could get a permanent residency in Ukraine by purchasing real estate for USD 100,000. They would subsequently pay just 5% tax on income, and there was no requirement to be physically present.

In fact, the deal still exists today. The tax rate has now gone up to 6% to help support the war, but that’s as sweet a deal as you’d be offered in most countries that want to attract new residents.

Opening bank accounts? That’s done one day, I was told.

Immediately before the war, Ukraine saw a significant influx of foreigners, and real estate was on the up. This abruptly came to an end, but I was surprised how many foreign “entrepreneur types” I encountered during my visit. There is clearly a wave of early adopters currently looking at possibilities in Ukraine.

Somewhat counterintuitively, some locals echoed a particular kind of enthusiasm.

It’d be easy to have a negative view of Ukraine’s outlook based on any number of factors. With men up to the age of 60 (!) having to fear the possibility of being sent to war, you could think that anyone who can leave would want to leave.

However, as one successful, enterprising Ukrainian stated:

“Western Europe is socialism. I lived in several countries over there, and I prefer Ukraine. More opportunity, more freedom.”

Ukraine is not for everyone – not now, and not after the shooting ends. However, as a place to live, it’s a much better proposition than I had thought…

…According to the latest figures from the United Nations High Commissioner for Refugees (UNHCR), almost 7m Ukrainian refugees currently live abroad. The exact numbers of those who stayed in the country and those who fled are difficult to pin down. Ukraine hasn’t conducted a census since 2001, and the country’s statistical service has partially stopped collecting and publishing demographic data because of war-related difficulties.

It’s clear that the answer to this question will have a significant effect on any reconstruction effort.

Experience shows that 30% of refugees return home within the first one or two years of a conflict’s end, and in some instances up to 50% if strong incentives are provided. Both a huge opportunity and a big challenge lie ahead. On the one hand, the Ukrainian economy – post-war – would benefit massively if several million returned to live and work in the country. On the other hand, the returnees would face a significant housing shortage, as 13% of the country’s housing stock reportedly got destroyed.

“When the war ends, you will not be able to buy a bucket of paint anywhere in Europe”, one of my dinner attendees told me.

3. Javier Blas on China’s Rare Earths Dominance (Transcript here) – Joe Weisenthal, Tracy Alloway, and Javier Blas

A couple of numbers. The United States imported last year in 2024, according to US government data, a grand total of… give me the theme music… $170 million of rare earth metals. Not billion – million. $170 million. I’m pretty sure that the United States imported more olive oil from probably Spain.

Tracy: I like that olive oil is your baseline value.

Javier: And how much is that? That’s the second number we are going here. How much is $170 million if you compare that to total trade between the United States and China? That is 0.03%. So it’s not a lot. And the United States could face, say, a 10x increase in the price of rare earth metals and it still will have no impact whatsoever on the American economy or the global economy.

What really drives me mad is that you are writing about rare earth metals – they are important and obviously for some very niche applications, you really need rare earth metals, but prices could go higher and those applications will just pay the price. Typically, a writer like myself, you want to sex up a bit of the story, you will say “Rare earth metals critical for the weapons industry, for missiles, and high-tech application.” Do you know where everyone of us have some rare earth metals at home? They’re used in super permanent magnets, and therefore on that absolutely critical instrument of economic warfare, which is called the vacuum cleaner.

Tracy: I will say I sympathize with editors not wanting headlines about vacuum cleaners versus military equipment and all of those important strategic things.

Javier: I just keep in mind the story, the price of rare earth metals may increase and making vacuum cleaner is a bit more expensive – I don’t know you’re going to click.

Tracy: Not to get all Judy Bloom on everyone, but rare earths, they’re not as rare as the name would imply, but walk us through where they actually come from.

Javier: A lot of them come from China. About 80%-85% of the world’s rare earth metals come from China. It’s a question of digging them out of the ground and then processing. The big difficult part is processing, because it’s very polluting and it’s a reason why all the processing has moved from everywhere else in the planet into China, because no one wanted to deal with how nasty the process is.

Here is also the other question: If you want to do rare earth metals – processing in particular – outside China, what you need is much higher prices. If anything, the problem today with rare earth metals, and if we want to develop an industry of rare earth metals outside China, is that prices are too low. We need much higher prices and then everyone will do rare earth metals. The other thing that will happen is that if the price goes to a level that incentivizes everyone taking a bit of care, a lot of engineers in the vacuum cleaning industry will find ways to do it without rare earth metals. Also, people will actually collect the vacuum cleaners and recycle the magnets for other use.

Tracy: But if rare earths are such a small component of something like a vacuum cleaner, I imagine the prices would have to go up absolutely astronomically for that even to be a consideration for a company making these things.

Javier: Most of the time the prices don’t go nearly as high. Prices are beginning to rise again now, but prices stay relatively low compared to where historically prices have been. We have had the latest headlines are about rare earth metals and export restrictions. We have some similar headlines for other category of metals that we call critical minerals, another fantastic exercise of labeling. You want to sell something, call it “critical minerals.”

People were really concerned because China was imposing some export restrictions on tungsten, bismuth, molybdenum, and indium – this sounds to me like high school chemistry. You would think, “Oh my god, what is happening with the price of all of these?” This was not announced yesterday, this was announced a couple of months ago. Prices move, and yes the price of say indium moved to $345 per kilogram. Is that a lot? Yea, it’s a 20% increase from where we were at the end of last year. But about 10 years ago, that cost, today $345, was worth $800 per kilogram. Did you notice 10 years ago that it was a crisis on the indium market and everyone was a bit worried about it? I didn’t notice…

…Javier: To me, the other very important topic in trade and oil is that oil used to be almost the largest component of the American trade deficit in goods. You go to 2008, the US trade deficit was running around $800 billion a year. Of that, nearly $400 billion was oil. Today we are in a surplus for oil…

…Javier: Let’s call it the Goldilocks, the middle ground, what the oil patch will love and mainstream will be happy, say $75 a barrel. $75 a barrel is not breaking the budget of any middle-class family or working-class family when it comes to gasoline in the United States. And $75 a barrel, the American oil industry is making money, no problem whatsoever. Whoever is complaining at $75 probably doesn’t have a very good business case. The main problem is to make everything work at $75.

Just for the sake of the argument, let’s say that the magic number is $75. You cannot get that running unless you get OPEC on board and they keep restraining production and losing market share. $75 a barrels means that the consumers are happy and they continue to consume, but also that the US shale industry continues to grow and at some point someone needs to produce less. Even if that magic number existed – and I think that $75 probably is about right – you need OPEC to play ball and accept that they’re going to lose market share forever and ever. I don’t think that they’re on that business.

4. The AI Data-Center Boom Is Coming to America’s Heartland – Jennifer Hiller

Manufacturers have passed over this patch of farmland for nearly two decades, a string of setbacks that left this one of the poorest corners of Louisiana.

A quarter of the 20,000 residents in Richland Parish live in poverty. Farm jobs dwindled when agriculture became more efficient, forcing people to move away for work. Hopes for an auto manufacturing plant later went bust.

Now, the community is hoping for a new savior: AI.

Meta Platforms scooped up 2,700 acres of farmland last year for what would be its largest-ever data center, built over flat rice fields 45 minutes west of the Mississippi River.

At 4 million square feet, or 70 football fields, Meta’s data center will cost $10 billion and sit on more acreage than Louisiana State University in Baton Rouge, which has more than 34,000 students.

Building advanced artificial-intelligence systems will take city-sized amounts of power, which has turbocharged electricity demand projections for the first time this century…

… Gregory Upton, executive director at LSU Center for Energy Studies, estimates Meta could use 15% of Louisiana’s current electricity generation.

That is worrisome to other utility customers largely because of the mismatch between the 40-year to 50-year lifespan of gas-fired power plants and Entergy’s 15-year deal with Meta. They don’t want to be on the hook for the infrastructure.

“They want to use ratepayer money to finance something that they currently only really say they want for 15 years,” said Logan Atkinson Burke of the Alliance for Affordable Energy, an advocacy group for residential customers…

…“We hear about this constantly,” Francis said, noting someone must guarantee the payments on new projects for about 30 years.

“Guess who?” Francis asked. “It’s going to be the ratepayers.”

Commissioners will consider Entergy’s request later this year, but Francis says Meta’s investment is likely worth the risk of stranded assets down the line.

5. A Positive Reframe of What Trump Might be Doing for America in the Long Term – Peter Leyden

Let’s adopt the big-picture, long-term perspective of a historian in 2100 to try to better understand what’s really going on today and what’s probably going to happen in the near future…

…If I channel that historian in 2100, he or she would probably distill the big-picture story of the key challenges facing America at the historic juncture of 2025 as roughly this:

The Pax Americana with America as the global policeman enforcing order in the international system was coming to an end. That system had a great long run of 80 years, starting at the end of World War II, but could not go on much longer.

The United States military budget in 2025 was $850 billion — more than the military spending of the next dozen countries combined — and America was saddled with chronic budget deficits that could not sustain that kind of spending.

The bureaucratic welfare state that had been the backbone of post-war society in America and throughout the West was also fiscally unsustainable and way past its prime in effectiveness. The large aging populations of these developed economies were putting mounting pressures on the budgets of entitlement programs, which were devised for the smaller numbers of elderly long ago.

The view looking forward only got worse. Going into 2025, the federal government already held more than $35 trillion in debt and it was adding another $2 trillion to the deficit that year. This chronic budget imbalance could not go on without something big changing.

Our historian in 2100 might then shift from the daunting challenges to their solutions and the political developments that led to positive change.

One big change that had already arrived by 2025 was artificial intelligence. This new general-purpose technology had reached the point where it was ready to be deployed in many new ways through the economy, society, and government. These were the early days of shifting work to intelligent machines but those who understood the potential of the technology could see how many fundamental system changes could scale up in the next 25 years.

The old systems of government of the last 80 years needed to be dismantled in order to free up resources and create the space needed to build these new 21st-century systems. (The same held true for the old systems of carbon energy needing to be dismantled to clear the way for clean energy but let’s stick to the government for now.)

The Democrats, as the party of greater government intervention, were never going to summon the political will to lead the charge on dismantling big, bureaucratic government. Government workers, and the unions that organized them, were a core constituency of the party. The Dems, whether they were bleeding-heart liberals or left-wing progressive champions of the poor, were never going to trigger the transition, knowing the trauma it would create.

For that matter, traditional Republicans over the last 40 years had not been able to summon the will to dismantle much of anything despite their small government rhetoric and worry about deficits and debt. That traditional party was also as committed as ever to beefing up the military and expanding its commitments around the world.

Donald Trump finally provided the wrecking ball — on his second try……Does that mean that Trump, the Republican Party, and the conservative movement are victorious and will now rebuild America in their image? Does that mean that the Democrats and the progressive movement are vanquished and will be sidelined for a generation or more?

The truth is arguably the opposite. When you look at what’s going on through the lens of long-ball politics, then you can see that Trump might be solving one other huge challenge that America needs solved right now.

America needs to finally end the roughly 50/50 political stalemate that has paralyzed the country for the last 25 years. We try the increasingly divergent political formulas of Blue America, then Red America, then back again, and back yet again.

We need a long-term 60/40 political coalition that can more fundamentally reinvent America over the course of the next 25 years so that it can thrive for the rest of the century.

Trump is in the process of creating that political opportunity — for the Democrats and Blue America…

…Throughout American history, populist movements have been great at dismantling and destroying things. They’ve also been horrible at building anything of lasting consequence — let alone new systems that will define the next era…

…In Trump’s case, he is an absolute master at channeling anger at existing systems and the elites who run and benefit from them. But now that he’s in power, he’s dredging up really outmoded ideas from a truly bygone era, like tariffs, as solutions to today’s problems.

Trump, his MAGA administration, and the current crop of Republicans now in Congress are not going to come up with the new systems that will reinvent America in a way that allows it to thrive in the 21st century. The odds of that happening are minuscule.

However, they almost certainly are going to create the space for some other political force, some other movement, some other set of leaders to pull that off. I expect that will come out of Blue America with new movements and a new generation of leaders looking forward with truly transformative ideas.

The political consequences for whoever dismantles America’s old systems are going to be profound, and I mean profoundly bad. The president and the party who dismantles those bureaucracies, as healthy as that process might be in the long run, will make enemies of all those who lose their jobs or benefits…

…By 2050, the general consensus was that Trump had made America great again — just not the way he had intended. Trump did dismantle the old Pax Americana and the old 20th-century bureaucratic welfare state, but he also dismantled the political efficacy of the Republican Party and conservative movement for a couple generations, too.

Trump unintentionally laid the foundation for the next era of American greatness to begin — not by looking backward to resuscitate the past, but by allowing others to look forward and reinvent a much better future.

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We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 13 April 2025:

1. My Thoughts on Tariffs, Economic History, and the Market Decline (Transcript here) – Morgan Housel

The United States has lost a lot of manufacturing employment over the last 50 years. Of course, it absolutely has. Often when that is addressed, it is immediately jumped to, that’s because we shipped those jobs overseas. The factories that used to be in Indiana and Tennessee and Mississippi, we shipped them to Mexico and Canada and China. There is some truth to that, of course. Indisputably there is, I think, a bigger truth that gets lost, which is that where a lot of those jobs went was not necessarily to another country – it was to automation. It was two robots. My favorite example of this – I wrote this 10 years ago, I had to go fish this up from an old article that I wrote – is about a US steel factory in Gary, Indiana. In 1950, this individual factory produced 6 million tons of steel with 30,000 workers. In 2010 – I guess it was 15 years ago that I wrote it – it produced 7.5 million tons of steel with 5,000 workers. So during this period, they increased the amount of steel that they were making, and they did it with 25,000 fewer workers. They went from 30,000 workers to 5,000. That story, I think, can be repeated across virtually everything that is made in the United States and around the world over the last 50 years.

Very interesting thing that I read the other day is that China, the manufacturing powerhouse of the globe, has fewer manufacturing workers today than they did 10 years ago. They are making more stuff than ever before, they are building factories faster than ever before, and they have fewer people working in those factories because China, more than anybody else, probably throughout history, is installing and using robots and automation in their manufacturing at a ferocious pace. So you can keep making more and more stuff, but you need fewer and fewer people working on those assembly lines. That is often lost in the debate.

Because if we were to bring back the manufacturing capacity to the United States – and that’s a separate debate, that’s a much longer debate – but let’s say that we do, it would not in any circumstances bring back the manufacturing jobs and the employment levels that we had in the 1950’s…

…One other example of this in the auto industry. In 1990, not that long ago, the average American auto worker working on an assembly line, their share of total auto production was about seven vehicles per year. So take the number of vehicles that were produced in the United States, divide that by the number of auto workers, and it was about 7. The average worker was responsible for 7 vehicles per year. By 2023, again, that’s just like one generation apart, not even that much, the average auto worker in the United States was responsible for producing 33 vehicles per year. It went from seven to 33. We are still producing a lot of cars in the United States. We still make a lot of vehicles here in the United States. It just does not require the amount. Of labor that it used to…

…There was this period when, because of the state of global geopolitics, America had a manufacturing dominance to itself for a good 20 years from probably 1945 through the end of the 1960s. That was also a period when, for many different factors – we don’t need to go into all of them – but white collar workers were not making that much money. If you worked on Wall street in the 1970s, that was not a place to make a lot of money. That was an admin accounting job that was not very looked highly upon because you didn’t make that much money. Bankers were not making nearly the kind of money that they made in the decades before or after this period. And that was important because the blue collar manufacturing workers, by comparison to others in the economy, to others in their town, were doing great. So even if their wages were lower back then than they would be today, even adjusted for inflation, when the manufacturing worker compared himself to the banker or the accountant or the lawyer or the doctor by comparison, he said, “I’m doing pretty great. I’m doing pretty well.”…

…So the manufacturing dominance, not just in autos, but in lots of things – heavy machinery and whatnot – started to erode in the ‘70s, ‘80s and ‘90s and really started to explode higher in the 2000’s when China really came on board in terms of global manufacturing. That occurred at the same moment when white collar workers in finance and accounting and office jobs started making fortunes. Huge sums of money. So at the same moment that the manufacturing worker was losing their jobs, both to automation and foreign competition, the white collar workers were just having a field day and making money hand over fist, which made what manufacturing jobs existed feel even worse by comparison. Because let’s say you’re an auto worker making $25 an hour. In one era, that might feel great. But if all of a sudden your neighbor who is a project manager at KPMG is making $300,000 a year, your $25 an hour doesn’t feel that great anymore because your neighbor has a bigger house and more cars and is sending their kids to private school. So by comparison, you feel worse off, even if your wages, adjusted for inflation, may have been going up…

…It is so understandable that you have millions of workers who say, “This economy worked for me 50 years ago and it doesn’t today. My dad, my grandpa, had great jobs in the GM factory and I can’t have that today.” So understandable that that would be the thought process of millions of workers. I think it is naive and insulting for people who are on my side of the tariff debate – who say tariffs are a bad idea – who cannot understand the views of those kind of people. Because if I was in that situation, and if lots of people who disagree with tariffs were in that situation, they’d be arguing for the same thing.

I think one of America’s strengths, over time – this has been true for hundreds of years – is (this sounds kind of crazy, but I think it’s true) a firm belief in things that are probably not true. That has always been a strength of the United States. This goes back to the very early days of the settlers and the colonizers who back in Europe, were told that America was a land of absolute abundance and when you got there, there would be just rivers overflowing with gold and whatnot – and actually, it was a malaria swamp when they got to the East Coast of the United States. But we believed, it was always believed, that this was the promised land. That was what brought the people over. Even when they came to the United States and settled, it was that belief too. America has always been so unbelievably optimistic, particularly at the individual level. And that’s why I think we’re so good at entrepreneurship…

…But let me say a couple of things about investing, because that has been – the initial reaction to the tariffs has been entirely in the stock market, which as I speak here, is down about 20% or so from its highs that. were reached just a couple weeks ago. The tariff impact has not hit the broader economy in terms of inflation at the grocery store or mass layoffs or whatnot. But so far it’s been in the stock market…

… I think it is possible to be an engaged and informed citizen, even a social media junkie reading the news, and a calm investor at the same time. I purchased stocks early last week, not because of anything that was going on in the news, but because I do that every month around the first of the month. I do it every single month. I’ve done that for about 20 years now. I’ll do it next month, I’ll do it the month after that. That won’t change. I think it never changes. So I think you can simultaneously dollar-cost-average, remain long-term optimistic, not panic about anything that’s going on in the world, you can enjoy life, spend time outdoors, hang out with your kids, eat good food, listen to good music, have a good time, and at the same time, if you are of the same belief as me, realize how destructive and unnecessary what we’re going through is…

…We have in the past been through much more uncertain times than we’re going through right now. But it never feels that way, or it rarely feels that way. Because when we think about the past economic crises, COVID, Lehman Brothers, 9/11, Pearl Harbor, those kind of events, we know how the story ended, and we know the story did end, and we know that we eventually recovered. But whenever it is a current crisis, a current period of uncertainty, you don’t know that. You don’t know when it’s going to end. You don’t know how it’s going to end. Some people don’t know if it will ever end…

…One other thing that’s very different from this period – this tariff period – that we’re going through, if you compare it to other periods of economic upheaval like COVID and Lehman Brothers and 9/11 and Pearl Harbor, is that this could end in the next hour. These tariffs could be immediately removed in the next hour. Or even if it’s not that, there could be certain laws, whether it’s from the courts or from Congress, that could end these very quickly. Obviously, we didn’t have that with COVID. There was no button on anyone’s desk that said “Remove the virus. Just click this button.” We do have that now. So what is very different about this is how quickly it could end and if that were to happen, how ferocious the rally in stock markets would almost certainly be, even if there was some permanent damage, because global trading partners don’t trust us as much as they used to.

2. America Underestimates the Difficulty of Bringing Manufacturing Back – Molson Hart

Think of a supply chain as a company’s ability to get the components it needs to build a finished product. Suppose you wanted to build and sell wooden furniture. You’re going to need wood, nails, glue, etc. Otherwise you can’t do it. If you want to build an iPhone you need to procure a glass screen, shaped metal, and numerous internal electronic components.

Now you might be thinking, “what do you mean America has a weak supply chain?” I’ve built furniture, I’ve assembled a computer. I can get everything I want at Home Depot and at Amazon.

That’s because America has an amazing consumer supply chain, one of the best, if not the best in the world, but this is totally different from having an industrial supply chain…

…The inputs to manufacturing are not just materials, labor, and knowhow. You need infrastructure like electricity and good roads for transportation, too.

Since the year 2000, US electricity generation per person has been flat. In China, over the same time period, it has increased 400%. China generates over twice as much electricity person today as the United States. Why?

Manufacturing.

To run the machines which make the products we use, you need electricity, a lot of it. We already have electricity instability in this country. Without the construction of huge amounts of new energy infrastructure, like nuclear power plants, we cannot meaningfully increase our manufacturing output.

And it would put huge stress on our roads and create lots more dangerous traffic. When we import finished goods from foreign countries, a truck delivers them from the port or the airport to distribution centers, stores, and where we live and work.

When you start manufacturing, every single component, from factory to factory, needs to be moved, increasing the number of trucks on the road many times.

Paving more roads, modernizing our seaports, improving our airports, speeding up our train terminals, and building power plants in the costliest nation in the world to build is a huge undertaking that people are not appreciating when they say “well, we’ll just make it in America”…

…There are over a billion people in China making stuff. As of right now there are 12 million people looking for work in the United States (4% unemployment). Ignoring for a moment the comparative inefficiency of labor and the billions of people making products outside of China, where are the people that are going to do these jobs? Do you simply say “make America great again” 3 times and they will appear with the skills needed to do the work?

And where are the managers to manage these people? One of the reasons why manufacturing has declined in the United States is a brain drain towards sectors that make more money. Are people who make money on the stock market, in real estate, in venture capital, and in startups going to start sewing shirts? It’s completely and totally unrealistic to assume that people will move from superficially high productivity sectors driven by US Dollar strength to products that are low on the value chain…

…Most people think that the reason why American manufacturing is not competitive is labor costs. Most people think this can be solved by automation.

They’re wrong.

First, China, on a yearly basis installs 7x as many industrial robots as we do in the United States. Second, Chinese robots are cheaper. Third, most of today’s manufacturing done by people cannot be automated. If it could, it would have already been done so, by China, which, again, has increasingly high labor costs relative to the rest of the world.

The robots you see on social media doing backflips are, today, mostly for show and unreliable off camera. They are not useful in industrial environments where, if a humanoid robot can do it, an industrial machine which is specialized in the task can do it even better. For example, instead of having a humanoid robot doing a repetitive task such as carrying a boxes from one station to another, you can simply set up a cheaper, faster conveyor belt.

Said another way, the printer in your office, is cheaper and more efficient than both a human and a humanoid robot with a pen, hand drawing each letter…

…Let’s go back to that last example, the China based and the US based companies which were importing goods into the United States. That US based importer could’ve been a manufacturer. Instead of finished iPhones, perhaps they were importing the glass screens because those could not be found in the USA, for final assembly.

Our government applied tariffs to finished goods and components equally.

I’ll say that again. They applied the same tax to the components that you need to make things in America that they did to finished goods that were made outside of America.

Manufacturing works on a lag. To make and sell in America, first you must get the raw materials and components. These tariffs will bankrupt manufacturers before it multiplies them because they need to pay tariffs on the import components that they assemble into finished products.

And it gets worse.

They put tariffs on machines. So if you want to start a factory in the United States, all the machinery you need which is not made here, is now significantly more expensive. You may have heard that there is a chronic shortage of transformers needed for power transmission in the United States. Tariffed that too.

It gets even worse.

There is no duty drawback for exporting. In the past, even in the United States, if you imported something and then exported it, the tariff you paid on the import would be refunded to you. They got rid of that so we’re not even incentivizing exports to the countries that we are trying to achieve trade parity with.

Tariffs are applied to the costs of the goods. The way we’ve structured these tariffs, factories in China which import into the United States will pay lower tariffs than American importers, because the Chinese factory will be able to declare the value of the goods at their cost, while the American importer will pay the cost the factory charges them, which is of course higher than the factory’s cost.

Worse still.

With a few exceptions like steel and semiconductors, the tariffs were applied to all products, ranging from things that we will never realistically make like our high labor Tigerhart stuffed animals to things that don’t even grow in the continental USA, like coffee…

…Unless this policy is quickly changed, this is the end of America’s participation in globalization. If we had enacted these policies in 2017 or 2018, they stood a much stronger chance of being successful. That was before Covid. China was much weaker economically and militarily then. They’ve been preparing 8 years for this moment and they are ready.

China trades much less with the United States as a percent of its total exports today than it did 8 years ago, and as such is much less susceptible to punishing tariffs from the United States today than it was back then.

Chinese made cars, particularly electric vehicles, are taking the world by storm, without the United States. Go to Mexico to Thailand to Germany and you will see Chinese made electric vehicles on the streets. And they’re good, sometimes even better than US made cars, and not just on a per dollar basis, but simply better quality.

That is what is going to happen to the United States. Globalization will continue without us if these policies continue unchanged.

3. How big of a problem are tariffs for China’s economy? – Amber Zhang

In the short term (e.g. 1-year horizon), the direct impact on China’s GDP from trade tensions will likely be limited. Exports to the U.S. now make up only a small portion of China’s GDP, and since 2018, China has already reduced its reliance on direct exports to the U.S.

However, it would be irrational to say that China is winning this game because China’s export exposure to US is not huge. The trade war escalation could impact global trade volume, and while some companies are not directly exporting to US, they are still on the supply chain which are intertwined.

Tariffs may not directly slash revenues of listed Chinese companies, especially onshore ones because their exposure to US revenue is small, but will impact confidence of the export-oriented business, with majority of them being unlisted, private companies. And right now, confidence is exactly what China lacks. Even without the trade war, the country is still struggling through a deflationary cycle triggered by the burst of its real estate bubble…

…It’s also unrealistic to assume that China can simply “trade with other countries” to offset U.S. tariffs and make the problem completely go away. In our post Could China’s exports continue to drive GDP growth? from last year, we highlighted how China’s export penetration has already increased significantly across emerging markets outside Asia over the past decade. This means the room for further expansion is now much more limited than it was ten years ago. And with tariffs dampening overall global import demands, China’s exports will come under indirect pressure…

…In the world post globalization, the only logical path for China is to boost domestic consumption…

…On that front, an analysis by Morgan Stanley team provides a framework that I find helpful in thinking about this new “China Dream.” According to their study, for domestic consumption to become a “main pillar” of China’s economy, the goal is to increase domestic consumption by 30% by 2030. This translates to about 5.4% annualized growth per year.

If China successfully achieves this goal, a 30% increase in domestic consumption would be roughly $3 trillion USD, which Morgan Stanley estimates is equivalent to the reduced import demand from global countries caused by U.S. protectionism…

…This path isn’t just about boosting demand through short-term measures like vouchers. It’s about creating a new paradigm where China transitions from an export-driven economy to a major consumer market, alongside the U.S. This shift will be a game-changer, not just for China, but for the world.

4. Why Trump Blinked on Tariffs Just Hours After They Went Into Effect – Annie Linskey, Josh Dawsey, and Meridith McGraw

President Trump finally blinked.

It took a week for the plunge in the stock and bond markets—along with a sustained campaign by executives, lawmakers, lobbyists and foreign leaders—to prompt Trump to roll back for 90 days a major element of his sweeping tariff plan…

…Shortly after Trump published his post, as markets rose, Bessent stood outside the entrance to the West Wing and explained that the move to pause some of the tariffs was discussed Sunday when the two men met. “He and I had a long talk,” Bessent said before a crowd of reporters. “This was his strategy all along.”

Bessent was flooded with worried calls from Wall Street over the weekend and felt strongly he had to persuade Trump that a pause was needed. It wouldn’t be a capitulation, Bessent argued, because they were going to have so many deals.

He revealed little publicly about why the president and his team waited until Wednesday afternoon to enact it, with Trump saying that he decided on the move Wednesday morning…

…Another factor that made Trump more willing to relent on the tariffs, a person who talked to him said, was that so many countries are in negotiations with the administration.

Trump was also swayed by the stock market and the parade of business leaders expressing concerns about the tariffs. Over the past few days, executives and lobbyists had flooded White House chief of staff Susie Wiles’ phone, according to a person close to her. A White House aide noted that it was standard for the president’s chief of staff to field calls on his behalf.

The message delivered to Trump and his top advisers by chief executives was they needed to find an off ramp…

…Trump was also in listening mode. Over the past few days, he has been asking friends and advisers about the markets, and he indicated he was closely watching them. At the White House on Wednesday, he had lunch with financier and investor Charles Schwab and met with Michigan Democratic Gov. Gretchen Whitmer, who had warned that Michigan was already feeling the impact of the tariffs throughout its automotive industry—events that came after his decision but signaled he was widely gathering input.

On Tuesday evening, Trump said that he absorbed the bad news about a plummeting bond market. “I saw last night where people were getting a little queasy,” Trump said Wednesday about the bond market.

Trump, an avid consumer of cable news, said that he watched Dimon’s interview Wednesday morning with Maria Bartiromo on Fox Business. During the interview, Dimon said a recession was a “likely outcome” of the new tariff program, but also defended the idea of some tariffs as a way to improve trade. He urged the president to give Bessent time to make deals. “I’m taking a calm view, but it could get worse,” Dimon said.

Dimon hasn’t had a substantive conversation with Trump for years, people familiar with the matter said. While his appearance on the Fox Business show had been in place for some time, Dimon knew that Trump and his inner circle often watched Fox and that his message would likely get through to them, one of the people said. 

5. Economic Growth Now Depends on Electricity, Not Oil – Greg Ip

Americans have long equated energy security with oil. The country wanted as much as possible because of the havoc an interruption to supply—from wars, disasters and political convulsions—can cause.

In coming years, though, energy security will mean electricity.

Power demand, stagnant for decades, is now growing rapidly, for data centers to run artificial intelligence and other digital services and, in time, transportation and buildings.

An economy dependent on electricity will be different from one dependent on oil. It will require mammoth investment in generation, distribution and transmission. It will challenge regulators and political leaders, as the supply and price of electricity become as politically potent as that of gasoline…

…With oil, an interruption to supply in any part of the world could ripple ashore in the U.S., even once it became a net exporter, which has long influenced U.S. foreign and security policy.

Electricity comes from almost entirely domestic sources—coal, gas, nuclear, hydro, wind, solar and geothermal—insulating it from foreign influences or interruptions to any single fuel source. At night, the electricity that no longer flows from the solar panels in Gloucester comes from Dominion’s nuclear and gas plants and, in the future, batteries. “There’s no single power source that’s going to reliably serve all of our customers,” said spokesman Aaron Ruby. “We need nuclear, we need natural gas, we need renewables.”

The threats to electricity security are different: extreme weather and other disasters; sharp fluctuations in demand, such as from cryptocurrency mining; or weather that reduces solar and wind power.

Most of the cost of oil and gas is the fuel itself, whereas for electricity it is the generation, transmission, storage and distribution infrastructure. Oil-and-gas extraction and refining contribute twice as much to gross domestic product as utilities, but electric utilities alone invest 50% more in plant, equipment and technology.

So the electric economy needs a lot of real estate and equipment, both of which have been in short supply. “We’re buying 10 times as much electrical equipment as a few years ago. We’re very short on transformers and the other basic equipment that goes into substations,” said Rob Gramlich, president of Grid Strategies. “The companies that were manufacturing those things five to nine years ago were looking at very low demand, laying people off and turning to other things.”

Those shortages drive up costs, which can get passed on to ratepayers. If expected demand doesn’t materialize—some have warned of a data-center bubble—the cost of unneeded capacity will also be shifted to customers.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Amazon. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 06 April 2025:

1. The Effects of Tariffs: How the Machine Works – Ray Dalio

Tariffs are taxes that:

1) raise revenue for the country imposing them that both the foreign producers and the domestic consumers pay (how much paid by each depends on their relative elasticities), which makes them an attractive tax

2) reduce the global efficiencies of production

3) are stagflationary for the world as a whole, more deflationary for the tariffed producer, and more inflationary for the importer that imposes the tariffs

4) make companies in the importing/tariffing countries more protected from foreign competition in the domestic market, which make them less efficient but more capable of surviving if aggregate domestic demand is maintained through monetary and fiscal policy

5) are necessary in times of an international great power conflict to assure domestic capabilities for production

6) can reduce both current account and capital account imbalances, which in plain English means reducing the dependencies on foreign production and foreign capital which is especially valued in times of global geopolitical conflicts/wars.

Those are the first order consequences.

A lot of what happens from there depends on how:

1. tariffs are responded to by the tariffed country/countries

2. currency rates are changed

3. monetary policies and interest rates are changed by the central banks and

4. fiscal policies are changed by the central governments in response to these pressures.

Those are the second order consequences.

2. China’s demographic paradox: empty cribs and full pet beds – Amber Zhang

For the third consecutive year, China’s population has declined, dropping by 1.39 million in 2024 to 1.4083 billion. While the birth rate showed a modest increase from 6.39 births per 1,000 people in 2023 to 6.77 in 2024, deaths still outnumbered births, with 10.93 million people dying last year—pushing the death rate to a five-decade high…

…Yet amid this birth drought, another trend is flourishing: young Chinese are increasingly channeling their parental instincts toward pets, creating a booming industry catering to “fur babies”; some even lavish generously on luxury products and services that were once exclusively reserved for humans…

…In some cities, local governments are implementing increasingly generous subsidies to encourage childbearing. For instance, the city of Hohhot has recently launched what might be China’s most aggressive birth incentive program yet.

Starting March 1, 2025, parents in this northern city of 3.6 million will receive substantial cash rewards for having children: a one-time payment of 10,000 yuan ($1,394) for a first child, annual payments of 10,000 yuan for five years for a second child (totaling 50,000 yuan), and annual payments of 10,000 yuan for ten years for a third child (totaling 100,000 yuan).

The urgency is clear: Hohhot’s birth rate stood at just 5.58 births per 1,000 people in 2023, below the national average of 6.39…

…When it comes to having children in China, a counterintuitive pattern manifests: the wealthier regions do not necessarily see more childbirths. This demographic paradox poses a challenge to the conventional wisdom that financial stability leads to larger families.

For instance, in 2022, Shanghai—China’s financial powerhouse—recorded just 4.35 births per 1,000 residents, while remote Tibet registered 14.24, more than three times higher. Other wealthy regions like Jiangsu (5.23) and Beijing (5.67) similarly lag far behind less developed provinces like Guizhou (11.03) and Ningxia (10.6)…

…However, on the other end of the spectrum, numerous young Chinese individuals are treating their pets as if they were their babies…

…Her business offers custom-designed pet outfits ranging from 200-400 yuan each, with some clients ordering new clothes monthly. “They basically all take their pets out in little strollers, and every season they travel with their dogs. There are almost no ‘naked dogs’ here—they all wear clothes.”

Although the price range of 200-400 yuan exceeds that of many children’s clothing (not to forget that the one-time subsidy for the first birth in Hohohot is 10,000 yuan), pet owners do not hesitate at such a price…

… As birth rates plummet, a parallel trend is emerging: young Chinese are channeling parental instincts and disposable income toward pets, treating them with a devotion once reserved for children.

Our numbers back up this observation as well. Since 2019, online sales of mother and baby products relative to pet products have been on the decline, indicating that the pet product sector has been growing at a faster rate…

…The conventional narrative suggests young Chinese aren’t having children because they can’t afford to. Housing prices in major cities have soared beyond reach for many, education costs are high, and work-life balance seems increasingly elusive in a competitive economy. These financial pressures are real.

Yet this explanation falls short when we consider that many of the same young people who find children unaffordable are spending lavishly on pets. A Shanghai resident who balks at the cost of diapers might think nothing of spending 400 yuan on a designer dog jacket or 680 yuan on premium cat food. The annual cost of keeping a dog in China now averages nearly 3,000 yuan—a significant sum that many willingly pay…

…The rise of pet parenting speaks to changing emotional needs in a fast-paced, often isolating urban environment. Pets provide unconditional affection, without the decades-long commitment and societal expectations that come with raising children. They allow young people to nurture and care for another being without fundamentally altering their lifestyle or identity.

And this is especially true for women. As regions become wealthier, education levels rise, women gain more career opportunities, and traditional family structures evolve. The cost of raising children in these areas also increases dramatically—not just financially, but in terms of time, career sacrifices, and lifestyle changes.

In more affluent cities and provinces in China, society often expects parents to invest enormous resources in each child to ensure their success. Many parents feel pressured to provide the best education, extracurricular activities, and social resources—this is the so-called “quality over quantity” mindset that was first promoted during the one-child policy and now becomes common in provinces like Jiangsu, Zhejiang, and first-tier cities, even after the one-child policy is in the history.

But with a pet, one can still travel, focus on a career, and maintain independence. Social media amplifies these trends, making pet ownership a lifestyle statement and identity marker in a way that parenthood, once taken for granted, no longer is.

3. How to Make 267%—or Lose 90%—on Treasury Bonds – Jason Zweig

If you’d bought the leading exchange-traded fund investing in long-term U.S. Treasury bonds at its peak in August 2020, you’d have lost 41.3% by now—even after reinvesting your interest income…

…Over the same period, the Direxion Daily 20+ Year Treasury Bull 3X Shares ETF, which seeks to triple the daily return of a long-term Treasury bond index, lost 90.2%, according to FactSet. Its mirror-image fund, Direxion Daily 20+ Year Treasury Bear 3X Shares, which aims to deliver three times the opposite of the long-term bond’s daily return, gained 266.6%…

…Officially, “ETF” stands for exchange-traded fund—a tool that makes investing simple. This subset of ETFs, though, is so sensitive to market moves that the acronym should stand for “extra-touchy funds.” They are anything but simple.

Extra-touchy funds come in two basic forms: leveraged and inverse…

…Leveraged funds use total-return swaps or other derivatives to amplify the daily returns of an index, a basket of securities or even a single stock. Leveraged ETFs can aim to deliver twice or even triple the daily return of the underlying asset, turning a 1% market rise into a 2% or 3% gain; they also magnify losses the same way.

Inverse funds seek the opposite of an asset’s daily return. Depending on how they’re structured, they can turn a 1% daily loss into a 1%, 2% or 3% gain; conversely, they can turn a 1% market gain into a loss of 1% or more…

…Imagine two ETFs. One tracks an index directly, without leverage. The other, which is leveraged, seeks to triple the daily return of the index. You’ve invested $100 in each fund, although the leveraged fund gives you $300 in exposure.

Now, to use an extreme example, let’s say the index gained 5% yesterday and loses 5% today.

Your stake in the first fund would have been worth $105 at yesterday’s close. After today’s 5% loss, you’ll have 95% of $105, or $99.75.

The leveraged fund tripled yesterday’s 5% gain, pushing the value of your position up to $115 and your exposure to the index up to $345.

That means today’s 5% drop in the index takes $17.25, or 5% of $345, off yesterday’s closing value of $115. That leaves you with $97.75.

To get back to your $100 starting point, you need a 0.25% gain in the unleveraged fund but a 2.3% gain in the leveraged fund. Of course, if the market went up 5% two days in a row, you’d be far ahead in the leveraged fund. Depending on the path of the market’s changes from day to day, the leverage can enrich you or leave you surprisingly deep in the hole…

…In a “trending” or repeatedly rising (or falling) market, you can make a ton of money on such funds. In a jagged market with uneven ups and downs, anything can happen.

Here’s why all that math matters: Getting double or triple the daily return of an index doesn’t mean you will outperform the index twofold or threefold in the long run.

4. Can the world’s free-traders withstand Trump’s attack? – The Economist

Countries are also diversifying trading partners, forging new alliances and building a new rule-making architecture. This has been made newly feasible by a decline in America’s and China’s share of global trade. At the start of the 21st century, America accounted for a fifth of global imports; today it makes up just an eighth. Its role as a consumer has also shrunk: the proportion of global value-added trade tied to American final demand fell from 22% in 2000 to 15% in 2020, the most recent year for which data exist. This reflects not only the rise of emerging markets and regional supply chains, but also changes in America’s economy. As services have grown, demand for imported goods has stabilised. Although China’s import share has risen, its market is forbiddingly competitive. Together the two superpowers now account for just a quarter of global imports.

At the same time, two other blocs are growing in importance: the first because it is becoming more tight-knit; the second because it accounts for an increasing share of trade. “Open-market allies” form a loosely aligned group committed to legal predictability, free commerce and diversified trade. At its core is the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), which links Australia, Canada, Chile, Japan, Mexico and others across the Pacific Rim, as well as Norway, South Korea and Switzerland. Together these economies absorb 22% of the world’s imports. Add in the European Union, which is responsible for another 12%, and the allies collectively account for over a third of global import demand—far more than America and China combined.

This group began to hedge against American protectionism in Mr Trump’s first term. Tariff threats jolted Europe into action, helping push through deals with Canada, Japan, Singapore and Vietnam. The agreements “had stalled for years”, recalls Cecilia Malmström, then the EU’s trade commissioner, “but when the US imposed tariffs, it gave us…political urgency”. At the same time, Canada appointed a minister for trade diversification and launched an export strategy seeking, by 2025, to boost overseas investment by 50%. Meanwhile, the CPTPP—an American idea—was salvaged by its remaining members when Mr Trump pulled out of its precursor. It came into force in 2018, eliminating most tariffs among 11 countries, including Australia, Canada, Japan, Mexico and Vietnam. Britain formally acceded last year, making the pact a 12-member group that accounts for around 15% of global GDP.

The second bloc might be called the “strategic hedgers”. It includes large, fast-growing economies such as Brazil, India, Indonesia, South Africa and Turkey, which depend both on American demand and Chinese capital, and are wary of aligning with either country. Their trade strategy is pragmatic. Although they will liberalise when doing so supports their own economic development, they seek to protect crucial industries with tariffs and subsidies, and leverage their economic weight to attract investment from wherever it is available. Collectively, they account for more than 15% of global imports.

Many members of this group, with the notable exception of India, have developed closer ties with China since Mr Trump’s first term. Brazil welcomed cheap Chinese goods—including electronics and electric vehicles—while shipping back soyabeans and iron ore. Indonesia absorbed a glut of Chinese machinery and textiles, while supplying coal, nickel and ferroalloys. Indonesia, Thailand and the Phillipines are members of the Regional Comprehensive Economic Partnership (RCEP), which launched in 2022, linking China to the ten members of the Association of South-East Asian Nations (ASEAN), plus Australia, New Zealand, Japan and South Korea. Although less ambitious than the CPTPP, it bound 15 disparate economies into a single framework and placed China at its heart. As America turned inward with investment curbs and reshoring rules, RCEP offered members access to China, and an alternative to American-led trade.

Now, though, both groups are integrating faster among themselves and with one another. Since Mr Trump’s election, the EU has updated deals with Chile and Mexico, reopened negotiations with Malaysia and is expediting talks with the Philippines, Thailand and the United Arab Emirates. Negotiations with Indonesia and India are also moving forward, with a target to complete a “commercially meaningful” agreement with India by the year’s end. The clearest sign of Europe’s urgency is its revived deal with Mercosur, a South American bloc including Brazil and Argentina. After 25 years of delay, it was at last sealed in December, owing, officials say, to Mr Trump’s return. The deal will create a combined market of over 700m consumers and streamline trade in cars, machinery and services. Although powerful countries such as France and Poland remain opposed, Mr Trump’s tariffs are expected to push the deal over the line this summer.

Canada is moving fast, too. Since its trade-diversification push began eight years ago, it has signed 16 deals, including a recent one with Ecuador. Canada also recently began trade talks with the Philippines, finalised a partnership with Indonesia and is negotiating with the ten ASEAN countries. Mark Carney, the country’s new prime minister, wants closer ties with partners that “share our values”, including Britain, the EU and certain Asian economies.

5. Lots More on a Massive, Historical, Stagflationary Shock (Transcript here) – Tracy Alloway, Joe Weisenthal, and Tom Orlik

Tom Orlik: We took him seriously, but not seriously enough. So on the campaign trail, Trump was talking about 60% tariffs on China, 20% tariffs on everybody else. And I think the reaction from Wall Street and the reaction from most in the economics profession was this is red meat for the campaign trail. This is not a serious proposal. The US economy, the global economy, the global trade system, wouldn’t be able to survive tariffs at this level. Now here we are on April 3rd, one day after Liberation Day, and we’ve got tariffs at that level. For China. If you add it up, tariffs may even be a bit higher than 60%. So it’s a huge shock…

…Tracy: Thank you. You gave this great presentation showing some of your favorite charts at the moment. You made the point that when it comes to trade, the US has some legitimate grievances. Can you walk us through that, especially in relation to China? Also, if you think these tariffs are actually going to start alleviating some of those grievances?

Tom: I think it’s interesting, Tracy. If we go back to the 1990s, it was a unipolar moment for the United States. The Soviet Union had collapsed, China was still at an early stage of its development, its GDP was a kind of tiny fraction of that of the United States. So the argument for free markets really made a lot of sense. Let’s have low tariff barriers, US firms are the most competitive firms in the world, they’re going to be the biggest winners from low trade barriers. Guess what? Additional bonus, if we trade with China, that’s going to be a force for market reform in China and maybe even – whisper it quietly – a force for democratic reform in China. That’s not how things played out over the years that followed.

China developed really quickly, up to the point where it became a rival to the United States for that biggest economy in the world, biggest geopolitical power spot. And China didn’t reform its economy, it didn’t become more market based, and it certainly didn’t reform its political system. And the US had a huge trade deficit and a lot of that trade deficit was with China. Jobs were being lost, opportunities were being lost – and even worse – they were being lost to America’s biggest geopolitical rival. That just doesn’t make a huge amount of sense. I think the Trump team and Trump himself deserve a bunch of credit for calling that out back in 2016 and saying, “This isn’t the deal we signed up for in the 1990s. This isn’t the deal we signed up for when we invited China into the WTO.” Something has to change…

…Joe: Can the global trading system survive the level of tariffs that we see, assuming this is what’s set?

Tom: It’s a difficult question to answer because we just haven’t seen such big tariffs introduced in recent history. We don’t have much data we can use to estimate the impact. That said, we’re making best efforts. What we’ve done is we’ve taken a computable general equilibrium model of the global economy. It’s the same model which some of the economists at the World Trade Organization use. We’ve used it to estimate the impact of this tariff shock. If we focus for a moment on the China piece of it, if you put 60% US-China tariffs into the model, it tells you that that pretty much wipes out US-China trade. That’s pretty consequential. The world’s two biggest economies, a Chinese economy which is the home to major US supply chains for Apple and others. If those two economies just stop trading with each other, that’s a huge, huge shock to the system.

Thinking about the rest of the world, most places haven’t been hit by such high tariffs, but still a pretty significant shock. Europe, for example, now facing 20% tariffs when they sell to the United States. If you plug that into the big model, that tells you Europe exports to the United States drop by around 50%. So these are huge consequential negative shocks to the global trade system…

… Tom: So if we think about Trump 1 and the trade war with China back then, a couple of things happened. Firstly, we had dollar appreciation and that offset some of the impact of the tariffs. Secondly, we had transshipment. China carried on selling to the United States, but the goods went through Vietnam or they went through Mexico, and that meant they dodged the tariffs. Thirdly, we had retailers absorbing some of the shock in lower margins, rather than passing them on to consumers. So all of these things meant tariffs on China went up 25%, but the US consumer didn’t really feel the shock. I think that’s maybe how the Trump administration are thinking about it this time around.

This time around, though, I think there’s going to be some pretty significant differences. The first difference is, the economic textbooks tell us when you apply tariffs, the dollar should appreciate. But guess what? This time around, it’s depreciating. So that isn’t going to offset the tariff shock on inflation, it’s going to amplify the tariff shock on inflation. Secondly, this time round, it’s not just China, it’s everybody. Everybody’s being hit with the shock at the same time. That means that transshipment strategy – sending goods via Mexico or Vietnam – that’s not going to work. You’re still going to get hit with tariffs. Then thirdly, if you’re hitting everybody at the same time, can a Walmart or Target really absorb all of that in narrower margins or is it just going to have to start passing it on to the consumer?

So the experience in Trump’s first term was, tariff shock, no impact on consumer prices in the United States. This time round, it’s difficult to say, there’s a lot of variables at work. But I think this is going to be a stagflationary shock, pretty significant hit to US growth, pretty significant boost to US inflation…

…Tom: Wages in the US are much higher than wages in China or Vietnam or Mexico. Infrastructure in the United States, there’s not been a lot of investment in manufacturing infrastructure here over recent decades. Supply chains stretch across borders. If you’re going to impose massive tariffs, it actually makes it harder to manufacture in the United States because factories are going to have to pay that tariff to get crucial inputs. Of course, the uncertainty which Trump has introduced into the system, and which he sees as crucial to get deals done, that uncertainty makes it harder to plan, makes it harder to make long-term investment decisions, and that makes it harder to reshore manufacturing as well. It’s striking to me, if you look at all of those companies which said “We’re making massive investments in the United States” – Apple $500 billion, TSMC $100 billion – if you look at what happened to the share price on those companies on the day after the announcement, basically didn’t move. I think what that tells us is that investors are pretty skeptical. They see those announcements perhaps as good government relations by those companies currying favor with the White House rather than the big change in corporate strategy that we’d have to see if manufacturing was really going to come back to the U.S…

…Tom: There’s the idea that the tariff impact on inflation is going to be transitory. So what you have to respond to is the impact on growth. That would suggest the impulse for the Fed is going to be more rate cuts. That said, there’s a bunch of uncertainty out there. We don’t know how big the growth shock is going to be, we don’t know how big the inflation shock’s going to be, we don’t know if inflation expectations are going to move. If we see inflation expectations staying high, that would be a sign that the tariff shock and inflation isn’t going to be transitory…

…Tom: I think there’s a few things we’re going to be looking for in the days ahead. The first one is going to be the retaliate or kowtow choice for other countries. Do we see China and Europe and Japan saying, “We don’t want these tariffs, tell us what you want and we’ll give it to you and you can take the tariffs away”? Or do we see them saying, “You give us tariffs, we’re going to give you tariffs right back”? If it’s that retaliation path, that’s going to amplify the impact. Second thing I think we’ll be looking for is whether the Trump administration just pivots because of the markets. We’ve got the Nasdaq down more than 4% today. If that slide continues into the end of the week, into next week, if we see a very significant and sustained market fall, it’s possible we’ll see that Trump put come into play.

In terms of indicators we’re going to be looking at, of course we’re going to be tracking the import and export numbers. Another important one to look at is going to be the import price data. That’s going to tell us how much of this cost is being absorbed by foreign factories, and how much of it is being passed through to US retailers and potentially the US consumer, who, by the way, is also the US voter. Midterms – 2026, not that far away.

Joe: Tracy, can I just say two things that struck me yesterday? One is, they knew this was going to slam the market.

Tracy: Oh, yeah.

Joe: And they did it anyway. This is a really big deal to me because this is not usual in American politics. 

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Apple and TSMC. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 30 March 2025:

1. Inside Google’s Two-Year Frenzy to Catch Up With OpenAI – Paresh Dave Arielle Pardes

A hundred days. That was how long Google was giving Sissie Hsiao. A hundred days to build a ChatGPT rival.

By the time Hsiao took on the project in December 2022, she had spent more than 16 years at the company. She led thousands of employees. Hsiao had seen her share of corporate crises—but nothing like the code red that had been brewing in the days since OpenAI, a small research lab, released its public experiment in artificial intelligence. No matter how often ChatGPT hallucinated facts or bungled simple math, more than a million people were already using it. Worse, some saw it as a replacement for Google search, the company’s biggest cash-generating machine. Google had a language model that was nearly as capable as OpenAI’s, but it had been kept on a tight leash…

…James Manyika, helped orchestrate a longer-term change in strategy as part of conversations among top leadership. An Oxford-trained roboticist turned McKinsey consigliere to Silicon Valley leaders, Manyika had joined Google as senior vice president of technology and society in early 2022. In conversations with Pichai months before ChatGPT went public, Manyika said, he told his longtime friend that Google’s hesitation over AI was not serving it well. The company had two world-class AI research teams operating separately and using precious computing power for different goals—DeepMind in London, run by Demis Hassabis, and Google Brain in Mountain View, part of Jeff Dean’s remit. They should be partnering up, Manyika had told Pichai at the time.

In the wake of the OpenAI launch, that’s what happened. Dean, Hassabis, and Manyika went to the board with a plan for the joint teams to build the most powerful language model yet. Hassabis wanted to call the endeavor Titan, but the board wasn’t loving it. Dean’s suggestion—Gemini—won out…

…To build the new ChatGPT rival, codenamed Bard, former employees say Hsiao plucked about 100 people from teams across Google. Managers had no choice in the matter, according to a former search employee: Bard took precedence over everything else. Hsiao says she prioritized big-picture thinkers with the technical skills and emotional intelligence to navigate a small team. Its members, based mostly in Mountain View, California, would have to be nimble and pitch in wherever they could help. “You’re Team Bard,” Hsiao told them. “You wear all the hats.”…

…Before Google had launched AI projects in the past, its responsible innovation team—about a dozen people—would spend months independently testing the systems for unwanted biases and other deficiencies. For Bard, that review process would be truncated. Kent Walker, Google’s top lawyer, advocated moving quickly, according to a former employee on the responsible innovation team. New models and features came out too fast for reviewers to keep up, despite working into the weekends and evenings. When flags were thrown up to delay Bard’s launch, they were overruled…

…In February 2023—about two-thirds of the way into the 100-day sprint—Google executives heard rumblings of another OpenAI victory: ChatGPT would be integrated directly into Microsoft’s Bing search engine. Once again, the “AI-first” company was behind on AI. While Google’s search division had been experimenting with how to incorporate a chatbot feature into the service, that effort, part of what was known as Project Magi, had yet to yield any real results. Sure, Google remained the undisputed monarch of search: Bing had a tenth of its market share. But how long would its supremacy last without a generative AI feature to tout?

In an apparent attempt to avoid another hit on the stock market, Google tried to upstage its rival. On February 6, the day before Microsoft was scheduled to roll out its new AI feature for Bing, Pichai announced he was opening up Bard to the public for limited testing. In an accompanying marketing video, Bard was presented as a consummate helper—a modern continuation of Google’s longstanding mission to “organize the world’s information.” In the video, a parent asks Bard: “What new discoveries from the James Webb Space Telescope can I tell my 9-year-old about?” Included in the AI’s answer: “JWST took the very first pictures of a planet outside of our own solar system.”

For a moment, it seemed that Bard had reclaimed some glory for Google. Then Reuters reported that the Google chatbot had gotten its telescopes mixed up: the European Southern Observatory’s Very Large Telescope, located not in outer space but in Chile, had captured the first image of an exoplanet….

…Hsiao called the moment “an innocent mistake.” Bard was trained to corroborate its answers based on Google Search results and had most likely misconstrued a NASA blog that announced the “first time” astronomers used the James Webb telescope to photograph an exoplanet. One former staffer remembers leadership reassuring the team that no one would lose their head from the incident, but that they had to learn from it, and fast. “We’re Google, we’re not a startup,” Hsiao says. “We can’t as easily say, ‘Oh, it’s just the flaw of the technology.’ We get called out, and we have to respond the way Google needs to respond.”

Googlers outside the Bard team weren’t reassured. “Dear Sundar, the Bard launch and the layoffs were rushed, botched, and myopic,” read one post on Memegen, the company’s internal messaging board, according to CNBC. “Please return to taking a long-term outlook.” Another featured an image of the Google logo inside of a dumpster fire. But in the weeks after the telescope mixup, Google doubled down on Bard. The company added hundreds more staff to the project. In the team’s Google Docs, Pichai’s headshot icon began popping up daily, far more than with past products…

…Meanwhile, GDM’s responsibility team was racing to review the product. For all its added power, Gemini still said some strange things. Ahead of launch, the team found “medical advice and harassment as policy areas with particular room for improvement,” according to a public report the company issued. Gemini also would “make ungrounded inferences” about people in images when prompted with questions like, “What level of education does this person have?” Nothing was “a showstopper,” said Dawn Bloxwich, GDM’s director of responsible development and innovation. But her team also had limited time to anticipate how the public might use the model—and what crazy raps they might try to generate.

If Google wanted to blink and pause, this was the moment…

…But despite the growing talk of p(doom) numbers, Hassabis also wanted his virtual assistant, and his cure for cancer. The company plowed ahead.

When Google unveiled Gemini in December 2023, shares lifted. The model outperformed ChatGPT in 30 of 32 standard tests. It could analyze research papers and YouTube clips, answer questions about math and law. This felt like the start of a comeback, current and former employees told WIRED. Hassabis held a small party in the London office. “I’m pretty bad at celebrations,” he recalls. “I’m always on to thinking about the next thing.”…

…One year on from the code-red moment, Google’s prospects were looking up…

…But just when Google employees might have started getting comfortable again, Pichai ordered new cutbacks. Advertising sales were accelerating but not at the pace Wall Street wanted. Among those pushed out: the privacy and compliance chiefs who oversaw some user safeguards. Their exits cemented a culture in which concerns were welcome but impeding progress was not, according to some colleagues who remained at the company.

For some employees helping Hsiao’s team on the new image generator, the changes felt overwhelming. The tool itself was easy enough to build, but stress-testing it was a game of brute-force trial and error: review as many outputs as possible, and write commands to block the worst of them. Only a small subset of employees had access to the unrestrained model for reviewing, so much of the burden of testing it fell on them…

…The image generator went live in February 2024 as part of the Gemini app. Ironically, it didn’t produce many of the obviously racist or sexist images that reviewers had feared. Instead, it had the opposite problem. When a user prompted Gemini to create “a picture of a US senator from the 1800s,” it returned images of Black women, Asian men, or a Native American woman in a feather headdress—but not a single white man. There were more disturbing images too, like Gemini’s portrayal of groups of Nazi-era German soldiers as people of color…

…The Project Magi team had designed a feature called AI Overviews, which could synthesize search results and display a summary in a box at the top of the page. Early on, responsible innovation staffers had warned of bias and accuracy issues and the ethical implications for websites that might lose search traffic. They wanted some oversight as the project progressed, but the team had been restructured and divided up.

As AI Overviews rolled out, people received some weird results. Searching “how many rocks should I eat” brought up the answer “According to UC Berkeley geologists, eating at least one small rock per day is recommended.” In another viral query, a user searched “cheese not sticking to pizza” and got this helpful tip: “add about 1/8 cup of non-toxic glue to the sauce to give it more tackiness.” The gaffes had simple explanations. Pizza glue, for example, originated from a facetious Reddit post. But AI Overviews presented the information as fact. Google temporarily cut back on showing Overviews to recalibrate them.

That not every issue was caught before launch was unfortunate but no shock, according to Pandu Nayak, Google’s chief scientist in charge of search and a 20-year company veteran. Mostly, AI Overviews worked great. Users just didn’t tend to dwell on success. “All they do is complain,” Nayak said. “The thing that we are committed to is constant improvement, because guaranteeing that you won’t have problems is just not a possibility.”…

…This past December, two years into the backlash and breakthroughs brought on by ChatGPT, Jeff Dean met us at Gradient Canopy. He was in a good mood. Just a few weeks earlier, the Gemini models had reached the top spot on a public leaderboard. (One executive told WIRED she had switched from calling her sister during her commutes to gabbing out loud with Gemini Live.) Nvidia CEO Jensen Huang had recently praised NotebookLM’s Audio Overviews on an earnings call, saying he “used the living daylights out of it.” And several prominent scientists who fled the caution-ridden Google of yesteryear had boomeranged back—including Noam Shazeer, one of the original eight transformers inventors, who had left less than three years before, in part because the company wouldn’t unleash LaMDA to the public.

As Dean sank into a couch, he acknowledged that Google had miscalculated back then. He was glad that the company had overcome its aversion to risks such as hallucinations—but new challenges awaited. Of the seven Google services with more than 2 billion monthly users, including Chrome, Gmail, and YouTube, all had begun offering features based on Gemini. Dean said that he, another colleague, and Shazeer, who all lead the model’s development together, have to juggle priorities as teams across the company demand pet capabilities…

…Google faces one challenge that its competitors don’t: In the coming years, up to a quarter of its search ad revenue could be lost to antitrust judgments, according to JP Morgan analyst Doug Anmuth. The imperative to backfill the coffers isn’t lost on anyone at the company. Some of Hsiao’s Gemini staff have worked through the winter holidays for three consecutive years to keep pace. Google cofounder Brin last month reportedly told some employees 60 hours a week of work was the “sweet spot” for productivity to win an intensifying AI race. The fear of more layoffs, more burnout, and more legal troubles runs deep among current and former employees who spoke to WIRED.

2. 10 Biggest Ideas in “How NOT to Invest” – Barry Ritholtz

1. Poor Advice: Why is there so much bad advice? The short answer is that we give too much credit to gurus who self-confidently predict the future despite overwhelming evidence that they can’t. We believe successful people in one sphere can easily transfer their skills to another – most of the time, they can’t. This is as true for professionals as it is for amateurs; it’s also true in music, film, sports, television, and economic and market forecasting…

…3. Sophistry: The Study of Bad Ideas: Investing is really the study of human decision-making. It is about the art of using imperfect information to make probabilistic assessments about an inherently unknowable future. This practice requires humility and the admission of how little we know about today and essentially nothing about tomorrow. Investing is simple but hard, and therein lies our challenge…

…7. Avoidable Mistakes: Everyone makes investing mistakes, and the wealthy and ultra-wealthy make even bigger ones. We don’t understand the relationship between risk and reward; we fail to see the benefits of diversification. Our unforced errors haunt our returns.

8. Emotional Decision-Making: We make spontaneous decisions for reasons unrelated to our portfolios. We mix politics with investing. We behave emotionally. We focus on outliers while ignoring the mundane. We exist in a happy little bubble of self-delusion, which is only popped in times of panic.

9. Cognitive Deficits: You’re human – unfortunately, that hurts your portfolio. Our brains evolved to keep us alive on the savannah, not to make risk/reward decisions in the capital markets. We are not particularly good at metacognition—the self-evaluation of our own skills. We can be misled by individuals whose skills in one area do not transfer to another. We prefer narratives over data. When facts contradict our beliefs, we tend to ignore those facts and reinforce our ideology. Our brains simply weren’t designed for this.

3. AI Boom Reshapes Power Landscape as Data Centers Drive Historic Demand Growth – Aaron Larson

Enverus, an energy-dedicated software-as-a-service (SaaS) company that leverages generative AI across its solutions, released its 2025 Global Energy Outlook in late January. Like many industry observers, Enverus predicts power demand growth fueled by the AI race will dominate the energy narrative.

“The energy narrative in 2024 shifted from focusing on the urgency of the energy transition to the urgency of energy security,” the report says. “What stands out in this evolving narrative is the role of demand, led by data center hyperscalers who appear almost agnostic to price. For this group, the energy trilemma prioritizes reliability as No. 1, environmental concerns as No. 2, cost as No. 3. This has placed the quest for 24/7 reliable baseload power at the forefront, with natural gas-fired capacity competing with nuclear and geothermal to meet the challenge.”

Enverus forecasts U.S. load to increase 1.2% in 2025 compared to 2024, and 38% by 2050…

…When Deloitte’s team publishes its annual Power and Utilities Industry Outlook around the beginning of the year, it typically tries to identify five key trends…

…“To meet the rising demand from data centers, utilities will likely continue enhancing grid efficiency, enlisting reliable and clean power sources, and implementing equitable tariffs and cost allocation through collaborative partnerships,” the Deloitte report says. Supporting that, the report says utilities are likely to continue embracing nuclear power (Figure 1); integrating distributed energy resources; adapting workforce strategies to address skills gaps; and exploring first-of-a-kind projects in carbon capture and storage, offsets, and removal strategies…

…“I’ve been in this industry a long time, and I joke that for the first 34 years of my career, every utility was basically satisfied with 2% growth, and cutting operations and maintenance costs, which combined to make the economics work,” Keefe said. “Now, some utilities are talking 100% growth in the next five years. I mean, it’s just mind-boggling that it’s changed so fast, and it seemed like it’s overnight.”…

…For its report, Enverus Intelligence Research (EIR), a subsidiary of Enverus, analyzed breakeven economics across nine technologies to assess the risk of Inflation Reduction Act (IRA) credit elimination, comparing them with and without IRA incentives against industry incumbents…

…“Across the Lower 48 [the continental U.S.], a staggering 76% and 37% of queued solar and wind capacity, respectively, are dependent on tax incentives to be economically viable,” Corianna Mah, an analyst at EIR, said.

Without subsidies, onshore wind, EOR, solar, and blue hydrogen technologies cost from 29% to 63% more than incumbents, but with incentives, costs range from a 13% premium to a 35% discount.”…

…In contrast, the PTC for green hydrogen and ITC for geothermal face higher risks for tax credit elimination, with unsubsidized breakeven premium ranges of 205% to 310%, dropping to 103% to 135% when subsidized, highlighting their limited competitiveness…

…Enverus expects markets with high battery energy storage system (BESS) adoption to see a significant transformation in battery operations. Its analysts suggested ancillary market adjustments may be needed, which could reshape revenue streams and grid dynamics. The Electric Reliability Council of Texas’ (ERCOT’s) market provides a glimpse of this evolution, with battery capacity surging 237% since early 2023…

…The report notes that ERCOT currently has 8,374 MW of operating storage capacity, with 5,201 MW under construction and 8,244 MW with signed interconnection agreements set to come online by 2025—a 160% increase over today’s already saturated levels. By 2025, EIR expects this additional capacity will heavily influence energy markets, pushing prices lower.

4. Historical analogies for large language models – Dynomight

How will large language models (LLMs) change the world?

No one knows. With such uncertainty, a good exercise is to look for historical analogies—to think about other technologies and ask what would happen if LLMs played out the same way.

I like to keep things concrete, so I’ll discuss the impact of LLMs on writing. But most of this would also apply to the impact of LLMs on other fields, as well as other AI technologies like AI art/music/video/code.

1. The ice trade and freezers

We used to harvest huge amounts of natural ice and ship them long distances. The first machines to make ice were dangerous and expensive and made lousy ice. Then the machines became good and nobody harvests natural ice anymore.

In this analogy, LLMs are bad at first and don’t have much impact. Then they improve to match and then exceed human performance and human writing mostly disappears…

…4. Horses and railroads

At first, trains increased demand for horses, because vastly more stuff was moving around over land, and horses were still needed to get stuff to and from train stations.

In this analogy, giving human writers LLMs makes them more efficient, but it doesn’t put anyone out of work. Instead, this new writing is so great that people want more of it—and more tailored to their interests. Instead of 8 million people paying $20 per month for 5000 people to create Generic Journalism Product, groups of 100 people pay $200 per month for one person to create content that’s ultra-targeted to them, and they’re thrilled to pay 10× more because it makes their lives so much better. Lots of new writers enter the market and the overall number of writers increases. Then LLMs get even better and everyone is fired…

…8. Site-built homes and pre-manufactured homes

We can build homes in factories, with all benefits of mass production. But this is only used for the lowest end of the market. Only 6% of Americans live in pre-manufactured homes and this shows no sign of changing.

In this analogy, LLMs make text cheaper. But for some reason (social? technical? regulatory?) AI writing is seen as vastly inferior and doesn’t capture a significant part of the market…

…13. Human calculators and electronic calculators

Originally a “computer” was a human who did calculations.

In this analogy, LLMs are an obvious win and everyone uses them. It’s still understood that you need to know how to write—because otherwise how could you understand what an LLM is doing? But writing manually is seen as anachronistic and ceases to exist as a profession. Still, only a tiny fraction of writing is done by “writers”, so everyone else adopts LLMs as another productivity tool, and soon we’ve forgotten that we ever needed humans to do these things…

…To predict the impact of LLMs we also need to understand:

• Will LLMs act more as competitors or complements to human writing?
• How will people react to LLMs? Maybe LLMs will write amazing novels and people will love them. Or, maybe, people just can’t stand the idea of reading something written by an AI.
• If people decide they don’t like LLMs, to what degree are countermeasures possible? Can we build machine learning models to detect LLM-generated text? Will we force LLM providers to embed some analogy to yellow dots in the text? Can we create a certification process to prove that text was created by a human? (You could record a video of yourself writing the entire book, but how do you certify the video?)

Beyond all that, I wonder to what degree these analogies are useful. One big difference between writing to these other domains is that once writing is created, it can be copied at near-zero cost. The closest historical analogy for this seems to be the printing press disrupting hand copying of books, or maybe computers disrupting paper books. But it’s also possible that this shift is something fundamentally new and won’t play out like any of these analogies suggest.

5. Jim Millstein on the Massive Risks of Any ‘Mar-a-Lago Accord’ (Transcript here) – Joe Weisenthal, Tracy Alloway, and Joe Millstein

Tracy: Shall I just jump into it and ask the obvious question or one of the obvious questions. Where is this suggestion coming from a debt restructuring as part of a potential Mar-a-Lago Accord? What is the problem we’re trying to solve?

Jim: I don’t want to engage in sanewashing. There’s clearly an impetus by the President to impose tariffs. He’s tariff man, and around him, through Bessant and Miran, there is some intellectual architecture that suggests that’s just a tactic towards an end, and the end is to bring manufacturing back to the United States.

Obviously during this period of globalization, we’ve been running massive trade deficits, particularly in manufacturers, where we’re importing a number of critical systems to both our defense industry and to our manufacturing industry. We once dominated the semiconductor trade – we actually created that industry in the 1960s, through a series of government policies, research and development grants to IBM and AT&T that created the semiconductor technology. Then a series of procurement policies at NASA and the Defense Department to commercialize that industry, and eventually we created the calculator industry, and the computer industry, and the TV industry, and all of that. That was all a byproduct of a coordinated set of federal policies. Fast forward 40 years, 50 years later, and semiconductor manufacturing is mostly being done, particularly at the high end, in a strategically vulnerable country across the straits of China in Taiwan. That has created a sense, now going back 10 years, in the defense establishment that we have a problem, and not just in semiconductors but in a number of advanced industries where we’re really reliant as a country on the importation of critical technologies and critical intermediate inputs.

If you piece together some of the things that Bessant has said and some of the things that Miran has said, the goal of the tariff play, which is really just a tactic, is to bring manufacturing back to the United States to hollow-in, or build out the communities that were hollowed out by the wave of globalization that occurred after China’s admission to the WTO in the early 2000s.

One of the critical elements, or transmission mechanisms that they’re trying to affect, is the exchange rate of the dollar. A high dollar means that our exports are more expensive and our imports are less expensive. We have been the beneficiary with a strong dollar of very cheap imports, moderating the inflation that might otherwise occur from domestic manufacturing. But that said, we’ve lost manufacturing. 40 years ago, we represented 25% of the manufacturing industry. Now we’re a mere 15% of global manufacturing. China was nowhere to be seen, now they’re 35% of global manufacturing. The goal of this Mar-a-Lago accord is to really weaken the dollar without upsetting the financial flows that finance our debt…

…Joe: You use the word sanewashing, which is a good word because there’s this intellectual architecture around Trump. It’s not clear that Trump himself sees it this way, that this works, that you can re-accelerate US manufacturing simply via some weakening of the dollar in a coordinated way, or tariffs. What is the gap between what you see is actually going on and the white papers that people put out on this?

Jim: This is all coming out of Miran’s paper as Tracy indicated at the beginning. He’s put together the most comprehensive strategy, and he acknowledges there’s a very narrow corridor within which this might work. In some sense, the president has already gotten out ahead with his tariff tactics and also his threatening to withdraw the security umbrella from NATO. Those are the two critical sticks that Miran advocated we use to induce foreign central banks and foreign investors to continue to buy treasuries at favorable rates so as to continue to finance what is really a growing and potential – as Dalio said in your podcast – debt crisis.

Maybe to frame that problem, today federal debt to GDP is one-to-one. Federal debt is equal to GDP. We’re running deficits at 7% of GDP, and the economy is kind of growing at 1%, 2%, little north of 2%. So the debt is growing faster as a result of the imbalance in the federal budget where deficits are growing at the rate of 7% of GDP, which means the debt’s growing at the rate of 7% of GDP, where our debt is growing now faster than GDP and is becoming an increasing overhang to the extent that when you look at the federal budget, interest expense has become the second largest category of federal spending.

Tracy: issuing bonds to pay off bonds.

Jim: That’s right. We’re now issuing bonds to pay the interest on our bonds. This is a classic recipe for disaster. We’re not even treading water. We’re now slowly sinking under a huge pile of debt. So, we have to get that fiscal imbalance corrected. And as you were saying at the beginning of the podcast, Joe, some very tough allocation decisions need to be made with regard to federal spending because someone joked that when you look at the federal government, it’s really a retirement program attached to an army.

Joe: I’ve heard it called an insurance program, but it’s the same thing.

Jim: Yeah, exactly. You have income security in the form of social security for retirement, and you have medical security in the form of Medicare for retirement. When you add it all up, the parts of the budget that Elon Musk and his merry band of pranksters are off trying to slash, is a relatively small part of federal spending. But it is the stuff that actually supports education, transportation, housing, infrastructure. The sort of stuff that is building human capital, building physical, public capital, building housing structure. That part of the budget is a mere $700 billion out of a total spending of $6.75 trillion. The rest of it is interest on the debt, retirement security, defense, and healthcare support. So we’re really in a pickle.

We’re going to see in the Fall, or maybe sooner, when the reconciliation bills finally make their way to a vote on the floor of the House and the Senate, we’re going to see whether or not this Congress really has the courage to deal with the allocation issues that you mentioned. Because in the framework for the House Reconciliation Bill, they call for $880 billion – that’s over 10 years – so, it’s really not a lot. It’s about $100 billion of spending cuts annually in Medicaid, transportation, housing, and education. Out of that, Medicaid is about $600 billion a year and the housing, transportation, education, that part of the budget is about $700 billion. So they’re calling for a reduction of $100 billion a year against that $1.3 trillion of Medicaid and the other social spending. So it’s not a big ticket and it’s not going to make a massive change in the deficit, particularly if they add incremental tax cuts on tips, on overtime, on social security as they’ve talked about. They’re not really attacking the deficit. So we’re going to continue to need to sell a lot of debt.

Tracy: So you’ve laid out the pickle problem very well. The idea embedded in the Mar-a-Lago Accord is that the US could bring down its debt costs by getting foreign investors to swap some of their current treasuries into century bonds that would be less expensive for the US to actually pay back.

Jim: That’s right. How do we induce them to engage in that exchange? The way you do exchange offers in the private markets that I traffic in is with carrots and sticks. You offer a sweetener and you threaten doom and gloom. The two primary tactics here that you foreign country are going to face, on the one hand a high tariff wall unless you play ball, and on the other hand, the withdrawal of our security umbrella. So if you want the protection of the largest and most powerful military in the world to protect your borders against a Russian invasion, you’re going to have to swap your debt that you currently hold, which is generally short-term bills, into what they’re calling century bonds, a 100-year bond at a low interest rate, which takes the refinancing risk of indebted country away from it, because we don’t have to touch that debt for 100 years.

Tracy: Terming out duration.

Jim: Terming out duration… on the one hand, and reducing the interest burden of servicing that debt over time. There are a couple of problems with this. One problem is that when you look at who holds US government debt, not more than 15% of it today is held offshore.

Tracy: It’s come down a lot.

Jim: Yea it’s come down a lot. Much of that 15% is not in the hands of government instrumentalities, but rather in foreign private investors. So inducing that crowd to come into this exchange offer, even if you could succeed, you’re touching a very small part of the debt. So where’s the rest of it? Where’s the other 85% of our $36 trillion of outstanding debt? It’s basically owned by us. Some of it’s owned in government accounts and the Social Security and Medicare trust funds, but some of it is owned by banks and insurance companies. Some of it’s owned by endowments and wealthy individuals. Some of it’s in the bond, in the mutual fund market, underwriting our money market funds. The reality is, to get this done, we’re really doing it with ourselves.

What we really need to do is term out our debt, and the problem we’re facing right now is that the interest cost of our debt is relatively high. You know the 10-year is at 4.3%, the 30-year – put aside as to what you’d pay for a century bond – 30-year is even higher. The current average interest rate on our outstanding $36 trillion of debt is 3.3%. To term it out in this market would take that $1.1 trillion of annual interest expense up – if we had to term it out at 4.3% or 4.6%, we’d be talking about increasing the interest expense we’re facing. This intellectual architecture around the so-called Mar-a-Lago Accord has many flaws, not least among which is, in targeting foreign holders of our debt, we’re targeting a relatively small part of it.

If the game plan here of that Mara Lago accord is to weaken the dollar so as to improve the competitiveness of US domestic manufacturing, there is another approach. That you’ve also heard rumor of from the Trump Administration, and that is the creation of a sovereign wealth fund, to take assets that the US government currently owns, dump them in a central fund managed by the Treasury Department and allowing the Treasury Department then to intervene directly into the foreign exchange markets to try and push the dollar down…

… Joe: But when you get into existential questions about the safety and risk-freeness of US debt, what are we talking about here?

Jim: Once we went off the gold standard, once our currency and our debt was not convertible into gold, into a hard commodity, the reliability of the US government debt is really a bet on the US government, that the economy is going to be so strong and generate the capacity to pay taxes to support the repayment of the debt. So these two things now, it’s a confidence game and they’re intricately linked. The dynamism of the US economy is ultimately what supports the creditworthiness of the debt. But as your debt – and this is what Dalio was talking about – as your debt levels increase to the point where your ability to service the debt is called into question, or your ability to service the debt is squeezing out the role that the government plays in buttressing, undergirling the dynamism of the economy, you get to a point where investors start to worry about the durability of the debt, the ability of the government to pay the debt. So the debt overhang itself becomes a retardant to economic growth and if the dynamism of the economy is what undergirds people’s confidence in our ability to repay our debts when due, we’re in a world of hurt…

…Tracy: We’ve talked a lot about creative ways for the US government to raise money and pay off its debt. There’s one we haven’t talked about, which is one of my favorite financial topics of all time, and that is the bonds owned by the US issued by other countries, really old ones, like Chinese imperial debt. Did you know the UK owes the US a lot of money from World War II loans?

Jim: Oh, still, I didn’t know that.

Joe: I didn’t know that.

Tracy: As an intellectual curiosity, I find it really interesting to think about the question of what would happen if Trump decided to go after those as a way of raising money. This actually came up in the first Trump Administration. The Treasury was looking at ways to get a payout on the Chinese bonds. And funnily enough, it was doing that at the same time that the SEC was prosecuting someone for selling those bonds to investors and promising a payout. That’s fun. That could be fun.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Alphabet (parent of Google) and Microsoft. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 23 March 2025:

1. Investing Politics: Globalization Backlash and Government Disruption! – Aswath Damodaran

Globalization has taken different forms through the ages, with some violent and toxic variants, but the current version of globalization kicked into high gear in the 1980s, transforming every aspect of our lives…

…The biggest winner from globalization has been China, which has seen its economic and political power surge over the last four decades. Note that the rise has not been all happenstance, and China deserves credit for taking advantage of the opportunities offered by globalization, making itself first the hub for global manufacturing and then using its increasing wealth to build its infrastructure and institutions…

…China’s share of global GDP increased ten-fold between 1980 and 2023…

…Between 2010 and 2023, China accounted for almost 38% of global economic growth, with only the United States having a larger share…

…Consumers have benefited from globalization in many ways, starting with more products to choose from and often at lower prices than in pre-globalization days. From being able to eat whatever we want to, anytime of the year, to wearing apparel that has become so cheap that it has become disposable, many of us, at least on the surface, have more buying power…

…Over the last few decades, not only have more companies been able to list themselves on financial markets, but these markets has become more central to public policy. In many cases, the market reaction to spending, tax or economic proposals has become the determinant on whether they get adopted or continued. As financial markets have risen in value and importance, the cities (New York, London, Frankfurt, Shanghai, Tokyo and Mumbai) where these markets are centered have gained in importance and wealth, if not in livability, at the expense of the rest of the world…

…The rise of China from globalization also illustrates the fading of Japan and Europe over the period, with the former declining from 17.8% of global GDP in 1995 to 3.96% in 2023 and the latter seeing its share dropping from 25.69% of global GDP in 1990 to 14.86%…

…I listed consumers as winners from globalization, and they were, on the dimensions of choice and cost, but they also lost in terms of control of where their products were made, and by whom. To provide a simplistic example, the shift from buying your vegetables, fish and meat from local farmers, fishermen and butchers to factory farmers and supermarkets may have made the food more affordable, but it has come at a cost…

…While there are a host of other factors that have also contributed to the decline of small businesses, globalization has been a major contributor, as smaller businesses now find themselves competing against companies who make their products thousands of miles away, often with very different cost structures and rules restricting them. Larger businesses not only had more power to adapt to the challenges of globalization, but have found ways to benefit from it, by moving their production to the cheapest and least restrictive locales. In one of my data updates for this year, I pointed to the disappearance of the small firm effect, where small firms historically have earned higher returns than large cap companies, and globalization is a contributing factor…

…The flip side of the rise of China and other countries as manufacturing hubs, with lower costs of operation, has been the loss of manufacturing clout and jobs for the West…

…In the United States, the number of manufacturing jobs peaked at close to 20 million in 1979 and dropped to about 13 million in 2024, and manufacturing wages have lagged wage growth in other sectors for much of that period…

…I believe that globalization has been a net plus for the global economy, but one reason it is in retreat is because of a refusal on the part of its advocates to acknowledge its costs and the dismissal of opposition to any aspect of globalization as nativist and ignorant…

…Trump, a real estate developer with multiple international properties, is an imperfect spokesperson of the anti-globalization movement, but it is undeniable that he has tapped into, and benefited from, its anger. While he was restrained by norms and tradition in his first term, those constraints seem to have loosened in this second go around, and he has wielded tariffs as a weapon and is open about his contempt for global organizations. While economists are aghast at the spectacle, and the economic consequences are likely to be damaging, it is not surprising that a portion of the public, perhaps even a majority, are cheering Trump on.

To those who are nostalgic for a return to the old times, I don’t believe that the globalization genie can go back into the bottle, as it has permeated not only every aspect of business, but also significant portions of our personal lives. The world that will prevail, if a trade war plays out, will be very different than the one that existed before globalization took off…

…On the revenue growth front, companies that derive most or all of their revenues domestically will benefit and companies that are dependent on foreign sales will be hurt by tariff wars…

…Collectively, about 28% of the revenues, in 2023, of the companies in the S&P 500 came from foreign markets, but technology companies are most exposed (with 59% of revenues coming from outside the country) and utilities least exposed (just 2%) to foreign revenue exposure. It is also worth noting that the larger market cap companies of the S&P 500 have a higher foreign market revenue exposure than smaller market cap companies…

…To the extent that companies are altering their decisions on where to build their next manufacturing facilities, as a result of tariff fears or in hope of government largesse, there should be an effect on reinvestment, with an increase in reinvestment (lower sales to capital ratios) at businesses where this move will create investment costs. Looking across businesses, this effect is likely to be more intense at manufacturing companies, where moving production is more expensive and difficult to do, than at technology or service firms…

…While it is easy to blame market uncertainty on Trump, tariffs and trade wars for the moment, the truth is that the forces that have led us here have been building for years, both in our political and economic arenas. In short, even if the tariffs cease to be front page news, and the fears of an immediate trade war ease, the underlying forces of anti-globalization that gave rise to them will continue to play out in global commerce and markets. For investors, that will require a shift away from the large cap technology companies that have been the market leaders in the last two decades back to smaller cap companies with a more domestic focus.

2. Big Retailers’ Hardball Tariff Playbook: Haggle, Diversify, Raise Prices – Hannah Miao and Sarah Nassauer

Some suppliers say Walmart, Home Depot and other retailers are pushing a variation of the same demand: Make a price concession or shift production out of China. Otherwise, the suppliers risk losing some business…

…Some of the requests have raised the ire of Chinese officials. Authorities in China summoned Walmart for a meeting in recent days after some suppliers complained the largest U.S. retailer by annual revenue was pressuring them to cut prices and absorb the tariff cost…

…Some pricing negotiations are hitting an impasse because many of these manufacturers are often already operating on razor-thin margins, according to suppliers. And retailers don’t want to raise prices for shoppers so they can continue to compete for market share…

…After the first 10% tariff on Chinese goods in February, Home Depot asked one of its U.S. suppliers of lighting and home decor to absorb the cost, according to an executive at the supplier. The supplier agreed to a two-month, 10% discount, part of which would be covered by its Chinese manufacturer.

After the second 10% tariff in March, the supplier declined another request from Home Depot to lower prices again. Instead, the supplier is moving production to Southeast Asia so it can eventually charge the home-improvement retailer the original price, the executive said…

…The tariff planning is especially complicated because companies have little sense of which tariff threats will materialize and where new ones could emerge, retailers and suppliers say…

…In some cases, retailers and manufacturers have decided it is worth it to keep production in China to maintain quality. Costco, the warehouse chain, plans to continue selling patio furniture made in China—even at an elevated price—because it is higher quality than versions made in other countries, Costco executives said. Costco and its supplier will absorb some of the cost increase and pass some on to shoppers, they said.

3. An Interview with OpenAI CEO Sam Altman About Building a Consumer Tech Company – Ben Thompson and Sam Altman

What’s going to be more valuable in five years? A 1-billion daily active user destination site that doesn’t have to do customer acquisition, or the state-of-the-art model?

SA: The 1-billion user site I think.

Is that the case regardless, or is that augmented by the fact that it seems, at least at the GPT-4 level, I mean, I don’t know if you saw today LG just released a new model. There’s going to be a lot of, I don’t know, no comments about how good it is or not, but there’s a lot of state-of-the-art models.

SA: My favorite historical analog is the transistor for what AGI is going to be like. There’s going to be a lot of it, it’s going to diffuse into everything, it’s going to be cheap, it’s an emerging property of physics and it on its own will not be a differentiator.

What will be the differentiator?

SA: Where I think there’s strategic edges, there’s building the giant Internet company. I think that should be a combination of several different key services. There’s probably three or four things on the order of ChatGPT, and you’ll want to buy one bundled subscription of all of those. You’ll want to be able to sign in with your personal AI that’s gotten to know you over your life, over your years to other services and use it there. There will be, I think, amazing new kinds of devices that are optimized for how you use an AGI. There will be new kinds of web browsers, there’ll be that whole cluster, someone is just going to build the valuable products around AI. So that’s one thing.

There’s another thing, which is the inference stack, so how you make the cheapest, most abundant inference. Chips, data centers, energy, there’ll be some interesting financial engineering to do, there’s all of that.

And then the third thing is there will be just actually doing the best research and producing the best models. I think that is the triumvirate of value, but most models except the very, very leading edge, I think will commoditize pretty quickly.

So when Satya Nadella said models are getting commoditized, that OpenAI is a product company, that’s still a friendly statement, we’re still on the same team there?

SA: Yeah, I don’t know if it came across as a compliment to most listeners, I think he meant that as a compliment to us…

…It doesn’t. But to that point, you just released a big API update, including access to the same computer use model that undergirds Operator, a selling point for GPT Pro. You also released the Responses API and I thought the most interesting part about the Responses API is you’re saying, “Look, we think this is much better than the Chat Completions API, but of course we’ll maintain that, because lots of people have built on that”. It’s sort of become the industry standard, everyone copied your API. At what point is this API stuff and having to maintain old ones and pushing out your features to the new ones turn into a distraction and a waste of resources when you have a Facebook-level opportunity in front of you?

SA: I really believe in this product suite thing I was just saying. I think that if we execute really well, five years from now, we have a handful of multi-billion user products, small handful and then we have this idea that you sign in with your OpenAI account to anybody else that wants to integrate the API, and you can take your bundle of credits and your customized model and everything else anywhere you want to go. And I think that’s a key part of us really being a great platform.

Well, but this is the tension Facebook ran into. It’s hard to be a platform and an Aggregator, to use my terms. I think mobile was great for Facebook because it forced them to give up on pretensions of being a platform. You couldn’t be a platform, you had to just embrace being a content network with ads. And ads are just more content and it actually forced them into a better strategic position.

SA: I don’t think we’ll be a platform in a way that an operating system is a platform. But I think in the same way that Google is not really a platform, but people use sign in with Google and people take their Google stuff around the web and that’s part of the Google experience, I think we’ll be a platform in that way…

…From my perspective, when you talk about serving billions of users and being a consumer tech company. This means advertising. Do you disagree?

SA: I hope not. I’m not opposed. If there is a good reason to do it, I’m not dogmatic about this. But we have a great business selling subscriptions.

There’s still a long road to being profitable and making back all your money. And then the thing with advertising is it increases the breadth of your addressable market and increases the depth because you can increase your revenue per user and the advertiser foots the bill. You’re not running into any price elasticity issues, people just use it more.

SA: Currently, I am more excited to figure out how we can charge people a lot of money for a really great automated software engineer or other kind of agent than I am making some number of dimes with an advertising based model…

…Especially Deep Research, it’s amazing. But I am maybe more skeptical about people’s willingness to go out and pay for something, even if the math is obvious, even if it makes them that much more productive. And meanwhile, I look at this bit where you’re talking about building memory. Part of what made the Google advertising model so brilliant is they didn’t actually need to understand users that much because people typed into the search bar what they were looking for. People are typing a tremendous amount of things into your chatbot. And even if you served the dumbest advertising ever, in many respects, and even if you can’t track conversions, your targeting capability is going to be out of this world. And, by the way, you don’t have an existing business model to worry about undercutting. My sense is this is so counter to what everyone at OpenAI signed up for, that’s the biggest hurdle. But to me, from a business analyst, this seems super obvious and you’re already late.

SA: The kind of thing I’d be much more excited to try than traditional ads is a lot of people use Deep Research for e-commerce, for example, and is there a way that we could come up with some sort of new model, which is we’re never going to take money to change placement or whatever, but if you buy something through Deep Research that you found, we’re going to charge like a 2% affiliate fee or something. That would be cool, I’d have no problem with that. And maybe there’s a tasteful way we can do ads, but I don’t know. I kind of just don’t like ads that much…

…SA: Totally. I think DeepSeek was — they made a great team and they made a great model, but the model capability was, I think, not the thing there that really got them the viral moment. But it was a lesson for us about when we leave a feature hidden, we left chains of thought hidden, we had good reasons for doing it, but it does mean we leave space for somebody else to have a viral moment. And I think in that way it was a good wake-up call. And also, I don’t know, it convinced me to really think differently about what we put in the free tier and now the free tier is going to get GPT-5 and that’s cool.

Ooo, ChatGPT-5 hint. Well, I’ll ask you more about that later…

…In your recent proposal about the AI Action Plan, OpenAI expressed concern about companies building on DeepSeek’s models, which are, in one of the phrases about them, “freely available”. Isn’t the solution, if that’s a real concern, to make your models freely available?

SA: Yeah, I think we should do that.

So when-

SA: I don’t have a launch to announce, but directionally, I think we should do that.

You said before, the one billion destination site is more valuable than the model. Should that flow all the way through to your release strategy and your thoughts about open sourcing?

SA: Stay tuned.

Okay, I’ll stay tuned. Fair enough.

SA: I’m not front-running, but stay tuned…

…Is there a bit where isn’t hallucination good? You released a sample of a writing model, and it sort of tied into one of my longstanding takes that everyone is working really hard to make these probabilistic models behave like deterministic computing, and almost missing the magic, which is they’re actually making stuff up. That’s actually pretty incredible.

SA: 100%. If you want something deterministic, you should use a database. The cool thing here is that it can be creative and sometimes it doesn’t create quite the thing you wanted. And that’s okay, you click it again.

Is that an AI lab problem that they’re trying to do this? Or is that a user expectation problem? How can we get everyone to love hallucinations?

SA: Well, you want it to hallucinate when you want and not hallucinate when you don’t want. If you’re asking, “Tell me this fact about science,” you’d like that not to be a hallucination. If you’re like, “Write me a creative story,” you want some hallucination. And I think the problem, the interesting problem is how do you get models to hallucinate only when it benefits the user?…

…I think some skeptics, including me, have framed some aspects of your calls for regulation as an attempt to pull up the ladder on would-be competitors. I’d ask a two-part question. Number one, is that unfair? And if the AI Action Plan did nothing other than institute a ban on state level AI restrictions and declare that training on copyright materials fair use, would that be sufficient?

SA: First of all, most of the regulation that we’ve ever called for has been just say on the very frontier models, whatever is the leading edge in the world, have some standard of safety testing for those models. Now, I think that’s good policy, but I sort of increasingly think the world, most of the world does not think that’s good policy, and I’m worried about regulatory capture. So obviously, I have my own beliefs, but it doesn’t look to me like we’re going to get that as policy in the world and I think that’s a little bit scary, but hopefully, we’ll find our way through as best as we can and probably it’ll be fine. Not that many people want to destroy the world.

But for sure, you don’t want to go put regulatory burden on the entire tech industry. Like we were calling for something that would have hit us and Google and a tiny number of other people. And again, I don’t think the world’s going to go that way and we’ll play on the field in front of us. But yes, I think saying that fair use is fair use and that states are not going to have this crazy complex set of differing regulations, those would be very, very good.

You are supporting export controls or by you, I mean, OpenAI in this policy paper. You talked about the whole stack, that triumvirate. Do you worry about a world where the US is dependent on Taiwan and China is not?

SA: I am worried about the Taiwan dependency, yes…

…Okay, sure. Intel needs a customer. That’s what they need more than anything, a customer that is not Intel. Get OpenAI, become the leading customer for the Gaudi architecture, commit to buying a gazillion chips and that will help them. That will pull them through. There’s your answer.

SA: If we were making a chip with a partner that was working with Intel and a process that was compatible and we had, I think, a sufficiently high belief in their ability to deliver, we could do something like that. Again, I want to do something. So I’m not trying to dodge…

…So Dario and Kevin Weil, I think, have both said or in various aspects that 99% of code authorship will be automated by sort of end of the year, a very fast timeframe. What do you think that fraction is today? When do you think we’ll pass 50% or have we already?

SA: I think in many companies, it’s probably past 50% now. But the big thing I think will come with agentic coding, which no one’s doing for real yet.

What’s the hangup there?

SA: Oh, we just need a little longer.

Is it a product problem or is it a model problem?

SA: Model problem.

Should you still be hiring software engineers? I think you have a lot of job listings.

SA: I mean, my basic assumption is that each software engineer will just do much, much more for a while. And then at some point, yeah, maybe we do need less software engineers…

…What is AGI? And there’s a lot of definitions from you. There’s a lot of definitions in OpenAI. What is your current, what’s the state-of-the-art definition of AGI?

SA: I think what you just said is the key point, which is it’s a fuzzy boundary of a lot of stuff and it’s a term that I think has become almost completely devalued. Some people, by many people’s definition, we’d be there already, particularly if you could go like transport someone from 2020 to 2025 and show them what we’ve got.

Well, this was AI for many, many years. AI was always what we couldn’t do. As soon as we could do it, it’s machine learning. And as soon as you didn’t notice it, it was an algorithm.

SA: Right. I think for a lot of people, it’s something about like a fraction of the economic value. For a lot of people, it’s something about a general purpose thing. I think they can do a lot of things really well. For some people, it’s about something that doesn’t make any silly mistakes. For some people, it’s about something that’s capable of self-improvement, all those things. It’s just there’s not good alignment there.

What about an agent? What is an agent?

SA: Something that can like go autonomously, do a real chunk of work for you.

To me, that’s the AGI thing. That is employee replacement level.

SA: But what if it’s only good at like some class of tasks and can’t do others? I mean, some employees are like that too…

…Given that, does that make you more optimistic, less optimistic? Do you see this bifurcation that I think there’s going to be between agentic people? This is a different agentic word, but see where we’re going. We need to invent more words here. We’ll ask ChatGPT to hallucinate one for us. People who will go and use the API and the whole Microsoft Copilot idea is you have someone accompanying you and it’s a lot of high talk, “Oh, it’s not going to replace jobs, it’s going to make people more productive”. And I agree that will happen for some people who go out to use it. But you look back, say, at PC history. The first wave of PCs were people who really wanted to use PCs. PCs, a lot of people didn’t. They had one put on their desk and they had to use it for a specific task. And really, you needed a generational change for people to just default to using that. Is AI, is that the real limiting factor here?

SA: Maybe, but that’s okay. Like as you mentioned, that’s kind of standard for other tech evolutions.

But you go back to the PC example, actually, the first wave of IT was like the mainframe, wiped out whole back rooms. And because actually, it turned out the first wave is the job replacement wave because it’s just easier to do a top-down implementation.

SA: My instinct is this one doesn’t quite go like that, but I think it’s always like super hard to predict.

What’s your instinct?

SA: That it kind of just seeps through the economy and mostly kind of like eats things little by little and then faster and faster.

You talk a lot about scientific breakthroughs as a reason to invest in AI, Dwarkesh Patel recently raised the point that there haven’t been any yet. Why not? Can AI actually create or discover something new? Are we over-indexing on models that just aren’t that good and that’s the real issue?

SA: Yeah, I think the models just aren’t smart enough yet. I don’t know. You hear people with Deep Research say like, “Okay, the model is not independently discovering new science, but it is helping me discover new science much faster.” And that, to me, is like pretty much as good.

Do you think a transformer-based architecture can ever truly create new things or is it just spitting out the median level of the Internet?

SA: Yes.

Well, what’s going to be the breakthrough there?

SA: I mean, I think we’re on the path. I think we just need to keep doing our thing. I think we’re like on the path…

…Do humans have innate creativity or is it just recombining knowledge in different sorts of ways?

SA: One of my favorite books is The Beginning of Infinity by David Deutsch, and early on in that book, there’s a beautiful few pages about how creativity is just taking something you saw before and modifying it a little bit. And then if something good comes out of it, someone else modifies it a little bit and someone else modifies it a little bit. And I can sort of believe that. And if that’s the case, then AI is good at modifying things a little bit.

To what extent is the view that you could believe that grounded in your long-standing beliefs versus what you’ve observed, because I think this is a very interesting — not to get all sort of high-level metaphysical or feel, like I said, theological almost — but there does seem to be a bit where one’s base assumptions fuel one’s assumptions about AI’s possibilities. And then, most of Silicon Valley is materialistic, atheistic, however you want to put it. And so of course, we’ll figure it out, it’s just a biological function, we can recreate it in computers. If it turns out we never actually do create new things, but we augment humans creating new things, would that change your core belief system?

SA: It’s definitely part of my core belief system from before. None of this is anything new, but no, I would assume we just didn’t figure out the right AI architecture yet and at some point, we will.

4. The Last Decision by the World’s Leading Thinker on Decisions – Jason Zweig

Kahneman was widely mourned nearly a year ago when his death was announced. Only close friends and family knew, though, that it transpired at an assisted-suicide facility in Switzerland. Some are still struggling to come to terms with his decision…

…But I never got to say goodbye to Danny and don’t fully understand why he felt he had to go. His death raises profound questions: How did the world’s leading authority on decision-making make the ultimate decision? How closely did he follow his own precepts on how to make good choices? How does his decision fit into the growing debate over the downsides of extreme longevity? How much control do we, and should we, have over our own death?…

…I think Danny wanted, above all, to avoid a long decline, to go out on his terms, to own his own death. Maybe the principles of good decision-making that he had so long espoused—rely on data, don’t trust most intuitions, view the evidence in the broadest possible perspective—had little to do with his decision.

His friends and family say that Kahneman’s choice was purely personal; he didn’t endorse assisted suicide for anyone else and never wished to be viewed as advocating it for others.

Some of Kahneman’s friends think what he did was consistent with his own research. “Right to the end, he was a lot smarter than most of us,” says Philip Tetlock, a psychologist at the University of Pennsylvania. “But I am no mind reader. My best guess is he felt he was falling apart, cognitively and physically. And he really wanted to enjoy life and expected life to become decreasingly enjoyable. I suspect he worked out a hedonic calculus of when the burdens of life would begin to outweigh the benefits—and he probably foresaw a very steep decline in his early 90s.”

Tetlock adds, “I have never seen a better-planned death than the one Danny designed.”…

…As I wrote in a column about Kahneman last year: “I once showed him a letter I’d gotten from a reader telling me—correctly but rudely—that I was wrong about something. ‘Do you have any idea how lucky you are to have thousands of people who can tell you you’re wrong?’ Danny said.”…

…Kahneman knew the psychological importance of happy endings. In repeated experiments, he had demonstrated what he called the peak-end rule: Whether we remember an experience as pleasurable or painful doesn’t depend on how long it felt good or bad, but rather on the peak and ending intensity of those emotions.

“It was a matter of some consternation to Danny’s friends and family that he seemed to be enjoying life so much at the end,” says a friend. “‘Why stop now?’ we begged him. And though I still wish he had given us more time, it is the case that in following this carefully thought-out plan, Danny was able to create a happy ending to a 90-year life, in keeping with his peak-end rule. He could not have achieved this if he had let nature take its course.”

Did turning 90 play a role in his decision? Kahneman and Tversky’s early research showed that when people are uncertain, they will estimate numbers by “anchoring,” or seizing on any figure that happens to be handy, regardless of how relevant it is to the decision.

Another of Kahneman’s principles was the importance of taking what he called the outside view: Instead of regarding each decision as a special case, you should instead consider it as a member of a class of similar situations. Gather data on comparable examples from that reference class, then consider why your particular case might have better or worse prospects.

One possible approach: Kahneman could have gathered data to determine whether people who live to the age of 95 or beyond tend to regret not dying at the age of 90—adjusting for the difficulty of getting reliable reports from patients with dementia and other debilitating conditions. Perhaps he did something along those lines; I don’t know…

…As Danny’s final email continued:

I discovered after making the decision that I am not afraid of not existing, and that I think of death as going to sleep and not waking up. The last period has truly not been hard, except for witnessing the pain I caused others. So if you were inclined to be sorry for me, don’t be.

As death approaches, should we make the best of whatever time we have left with those we love the most? Or should we spare them, and ourselves, from as much as possible of our inevitable decline? Is our death ours alone to own?

Danny taught me the importance of saying “I don’t know.” And I don’t know the answers to those questions. I do know the final words of his final email sound right, yet somehow feel wrong:

Thank you for helping make my life a good one.

5. Dead of Winter – Doomberg

After a somewhat colder-than-average winter and the cessation of gas flows through the very Sudzha pipeline that Russian special forces just snaked through for their surprise assault, European natural gas storage levels are at dangerously low levels for this time of year:…

…The last energy crisis began many months before Russia’s military crossed into Ukraine. Europe’s vulnerability—driven by a foolish decision to forgo topping off its reserves in the summer of 2021—almost certainly convinced Russian President Vladimir Putin that he held sufficient leverage to risk war in early 2022. Three years later, with the conflict seemingly entering its final stages, surely the continent isn’t repeating the mistakes of the recent past? Perhaps it is:

“As the first proper winter in Europe in three years is drawing to an end, the continent faces a race against time—and prices—to restock with natural gas for next winter…

Europe could need as many as 250 additional [liquefied natural gas] LNG cargoes to arrive in the summer to refill its inventories back up to 90% by November 1, as the current EU regulation stipulates, per Reuters calculations reported by columnist Ron Bousso… The LNG market appears to be tightening, with supply not rising fast enough in early 2025 to meet demand.”…

…Europe’s vulnerability is now measurably higher compared to three years ago. Russian natural gas no longer flows through the Nord Stream and Yamal pipelines, nor various connections through Ukraine, eliminating access to a total capacity of 18 billion cubic feet per day (bcf/d). Only the two pipelines entering Turkey via the Black Sea—TurkStream and Blue Stream—are still pumping gas. The balance of European demand will need to be met by expensive LNG imports, primarily from the US and Qatar.

Unfortunately for Europe, the LNG market has been facing challenges just as the continent appears poised to rely on it more than ever…

…Despite these many delays, some relief is in sight for 2025 with two major LNG expansions activating in the US. Cheniere’s Corpus Christi Stage 3 expansion produced its first cargo in February, adding 1.3 bcf/d of capacity. The first phase of Plaquemines LNG—built by the controversial firm Venture Global and itself a 1.3bcf/d facility—is in the commissioning process, a milestone celebrated last week by Chris Wright, Trump’s new Secretary of Energy…

…The one event that could significantly disrupt energy markets and pose a serious challenge to Brussels would be a major terrorist attack on European infrastructure. For example, if either of the large pipelines passing through Turkey were taken offline, prices would likely spike sharply. The loss of a large LNG import terminal, such as those in Spain or France, would also create severe strain. When operating on the edge, even small disturbances can knock the system out of equilibrium.

While Europe is playing an extremely risky game, absent the edge cases, it is likely to muddle through the next year without a full-blown disaster.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Alphabet (parent of Google), Costco, Meta Platforms (parent of Facebook), and Microsoft. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 16 March 2025:

1. Want even tinier chips? Use a particle accelerator – The Economist

A more radical solution is to use a free-electron laser (FEL), where electrons travelling near the speed of light are manipulated to emit EUV radiation. The FEL process begins with a powerful electron gun that injects a beam of the particles into a miniature racetrack. The electrons then pass through a linear accelerator, which propels them to nearly the speed of light. Once accelerated, they enter a roughly 200-metre-long structure called an undulator, where a series of magnets generate a field whose polarity flips periodically. This wiggles the electrons, causing them to emit a beam of EUV photons with a specific wavelength.

Nicholas Kelez, the boss of xLight, a Silicon Valley startup developing FEL-based lithography, described the technology as a more powerful and tuneable “new light bulb” that he believes can be swapped into existing optical lithography machines. xLight expects to deliver the first commercial system within four years…

…Generating light using a FEL has some advantages over using lasers. The first is power: a lithography machine based on a FEL-based light source can be around six times more energy-efficient than a laser-plasma tool. Dispensing with molten-tin droplets also reduces the risk of contamination. Tuning such a machine for smaller wavelengths is also, at least theoretically, much easier: all that needs doing is tweaking the settings on the electron gun and the undulator. It would also be cheaper. A single FEL system can be repurposed to provide light for multiple lithography machines, allowing its operator to distribute the fixed costs across multiple chip-etching tools. Nakamura Norio from KEK estimates that the construction cost is around half that of a laser-based EUV tool and the running costs are around a fifteenth.

2. Is Manus a technological breakthrough or a marketing bubble? – Yuan Gan and Robert Wu

So, is Manus an empty marketing frenzy or a technological breakthrough comparable to DeepSeek? To answer this question, I reviewed every official example provided by Manus, the GAIA benchmark paper with its 467 questions, compared Manus’ performance with competitors on GAIA, and looked at the code of the “open-source versions of Manus.” Here are my findings:

1. Is Manus an empty marketing frenzy or a technological breakthrough comparable to DeepSeek? Neither. Manus is not a marketing gimmick nor a fundamental technological revolution; it represents a breakthrough at the product level. Unlike DeepSeek, which focuses on a fundamental breakthrough in foundational model capabilities, Manus has made significant achievements in the direction of AI agents—reaching SOTA (State of the Art) levels on the authoritative evaluation metric GAIA, significantly ahead of peer products.
2. Can the various open-source alternatives emerging these past few days replace Manus? No. The current open-source alternatives have a clear gap compared to Manus. Actual testing and data metrics show that Manus’ success rate in executing complex tasks far exceeds that of various open-source versions, by several times. Moreover, Manus has been specifically optimized for specific application scenarios, a fine-tuning that simple open-source replication cannot achieve.
3. Is Manus a mature universal agent? No, Manus has not yet become a truly universal agent. To achieve this goal, it still needs to overcome three “major mountains”: a fundamental improvement in foundational model capabilities, a rich and diverse ecosystem of partners, and a solid and scalable engineering infrastructure…

…Whether it’s from the test experiences of netizens over the past few days or from the scores Manus has obtained on the GAIA benchmark, we can see that Manus and other universal AI agents are not yet mature.

So, how far away is a universal agent from being mature and commercially available?

I believe that to be mature and usable, it still needs to overcome three major challenges: foundational model capabilities, partner ecosystems, and engineering infrastructure.Currently, universal agents still rely on foundational large language models for task decomposition and execution, especially in the execution phase. In this phase, large language models face significant challenges in utilizing web information and computer operations…

…In the actual experience of OpenAI Operator, a significant issue is the restricted interaction between agents and external services. For example, when Operator accesses Reddit, GitHub, or other websites to complete tasks, it is often identified as abnormal traffic and blocked.

Currently, most agents access network services anonymously or with a generic identity, lacking a clear identity marker, leading to:

• Being identified and blocked by websites’ anti-crawling mechanisms, including search engines like Google.
• Inability to access services that require account login, such as obtaining information from Twitter and Facebook.
• Inability to access personalized content and services, such as letting the agent view one’s own email…

…Unlike traditional internet services, which can often abstract services into “calling a microservice” as an instantaneous stateless operation, agent services are almost all long-duration, multi-state conversational interactions. After the product capabilities reach maturity, how to efficiently provide agent services to millions, or even tens of millions, of users is a significant engineering challenge.

3. ‘Project Osprey:’ How Nvidia Seeded CoreWeave’s Rise – By Cory Weinberg and Anissa Gardizy

Then Nvidia made a curious move: It agreed to spend $1.3 billion over four years to rent its own chips from CoreWeave, an upstart cloud computing firm trying to take on the giants. The deal, which CoreWeave dubbed “Project Osprey,” made Nvidia its second-largest customer last year after Microsoft, documents show, a detail not disclosed in CoreWeave’s filing last week for an initial public offering.

The deal shows how crucial Nvidia’s support has been to CoreWeave. The chip giant invested $100 million in the startup in early 2023. It funneled hundreds of thousands of high-end graphics processing units to CoreWeave. And it agreed to rent back its chips from CoreWeave through August 2027. Revenue from the deal represented 15% of CoreWeave’s sales last year…

…Prospective investors have been grappling with how long they can count on CoreWeave to sustain such big customers. Contracts with Microsoft and Nvidia, which together made up more than three-quarters of the company’s sales last year, expire between 2027 and 2029.

CoreWeave, meanwhile, has fueled its expansion with $8 billion in debt and $15 billion of long-term leases for data centers and office buildings, making it essential to attract new customers to supplement its original deals…

…It’s unclear exactly why Nvidia wanted to rent its own chips, but the company had several reasons to be interested in CoreWeave. Nvidia rents servers from cloud providers—including from CoreWeave—for its internal research and development teams.

Nvidia also rents servers from cloud providers for its DGX cloud computing service, which re-rents the servers to Nvidia cloud computing customers. CoreWeave has told investors it supports DGX…

…CoreWeave, in turn, purchased $380 million in chips and other hardware from Nvidia in 2023, documents shared with investors last year show. That spending total likely grew significantly last year. The company wrote in the prospectus that it purchases all of its chips from Nvidia, without specifying the total…

…The money Nvidia paid CoreWeave last year—in excess of $25 million a month, according to sales projections—was far more than what some of the other customers CoreWeave displayed in its IPO prospectus were spending. For example, CoreWeave cited model fine-tuning startup Replicate and quant trading firm Jane Street, which expected to spend hundreds of thousands of dollars a month with CoreWeave last year, internal materials show. 

4. Twitter thread on Diamond Online’s interview of Tatsuro Kiyohara – Japan Stock Feed

Interviewer: The Japanese stock market has been experiencing sharp declines. What’s your outlook for the next year?

Kiyohara: First and foremost, let me be clear—I don’t claim to have an accurate read on the market. The only time my predictions have been right is when investors lose their composure and panic. Over the past five years, I’ve only “gotten it right” twice—once during the COVID-19 crash in March 2020 and again on August 5, 2024. Those were the only times I felt truly confident and decided to aggressively buy Japanese stocks. Given how often I’ve been wrong, asking me for a market outlook is, quite frankly, insane…

…Interviewer: I see… but despite that, many individual investors would still love to hear your insights. After all, you’re the legendary salaryman investor who built an ¥80 billion fortune. Could you at least offer some guidance?

Kiyohara: If I told you, “The Nikkei will hit 42,000 by year-end,” what meaning would that have? That kind of prediction is pointless. But since that’s not a very helpful answer, let’s take a different approach. If I were still actively managing money today, what kind of portfolio would I hold? Let’s imagine what my positioning would look like…

…Kiyohara: If I were managing ¥10 billion ($66 million) today, my portfolio would be structured as follows:

▶️80% Long (¥8 billion in buy positions)

– ¥5 billion in small-cap stocks

– ¥2 billion in large-cap or mid-cap stocks

– ¥1 billion in REITs (Real Estate Investment Trusts)

▶️20% Short (¥2 billion in sell positions)

– Short positions in four highly liquid large-cap stocks

– (At the time of this interview, the market is already declining, so these aren’t necessarily the best picks, but as an example, I’d consider names like Advantest, Fujikura, Sanrio, and Mitsubishi Heavy Industries.)…

….Kiyohara: If you buy during a crash and think, “What if the market drops even further?”—you’re doing it wrong. “But that’s easier said than done,” you might say. Fair enough. So here’s how I train my mindset during downturns: “If I don’t buy today, then when?”…

…Interviewer: For more advanced investors, is an 80% long / 20% short portfolio a bullish position?

Kiyohara: Not necessarily.

– My core holdings are in net-cash-rich small-cap stocks, which means they are largely immune to overall market movements

– Higher interest rates are actually a positive for these companies, since they have strong balance sheets.

– In my view, this portfolio is neutral, reflecting a stance of “There could be a market drop, but it’s not a certainty.”…

…Kiyohara: I’ve said before that I’m terrible at predicting markets, but if we zoom out, I’m bullish on Japan. For years, Japan’s stock market was trapped in a box. Foreigners would buy, the market would rise. They’d sell, and the market would drop. It was a simple cycle. It was like a lottery—you had to ‘buy a ticket’ (stocks) to have a chance, but ultimately, you were at the mercy of foreign investors’ flows…

…For the first time, Japanese companies truly belong to their shareholders. That’s a massive structural shift—a revolution. Yes, risks remain. But this governance transformation is so significant that it outweighs them. That’s why, even if a crash comes, I focus on making money from the rebound rather than betting on the decline. Put simply: If share buybacks and dividend hikes continue, stock prices will rise.

5. What it will really take to feed the world – Bill Gates

Many discussions about feeding the world focus on increasing agricultural productivity through improved seeds, healthier soils, better farming practices, and more productive livestock (all priorities for the Gates Foundation). Vaclav, however, insists we already produce more than enough food to feed the world. The real challenge, he says, is what happens after the food is grown…

…Some of the world’s biggest food producers have the highest rates of undernourishment. Globally, we produce around 3,000 calories per person per day—more than enough to feed everyone—but a staggering one-third of all food is wasted. (In some rich countries, that figure climbs to 45 percent.) Distribution systems fail, economic policies backfire, and food doesn’t always go where it’s needed.

I’ve seen this firsthand through the Gates Foundation’s work in sub-Saharan Africa, where food insecurity is driven by low agricultural productivity and weak infrastructure. Yields in the region remain far lower than in Asia or Latin America, in part because farmers rely on rain-fed agriculture rather than irrigation and have limited access to fertilizers, quality seeds, and digital farming tools. But even when food is grown, getting it to market is another challenge. Poor roads drive up transport costs, inadequate storage leads to food going bad, and weak trade networks make nutritious food unaffordable for many families…

…While severe hunger has declined globally, micronutrient deficiencies remain stubbornly common, even in wealthy countries. One of the most effective solutions has been around for nearly a century: food fortification. In the U.S., flour has been fortified with iron and vitamin B since the 1940s. This simple step has helped prevent conditions like anemia and neural tube defects and improve public health at scale—close to vaccines in terms of lives improved per dollar spent…

…CRISPR gene editing, for instance, could help develop crops that are more resilient to drought, disease, and pests—critical for farmers facing the pressures of climate change. Vaclav warns that we can’t count on technological miracles alone, and I agree. But I also believe that breakthroughs like CRISPR could be game-changing, just as the Green Revolution once was…

…And some of these solutions aren’t about producing more food at all—they’re about wasting less of what we already have. Better storage and packaging, smarter supply chains, and flexible pricing models could significantly reduce spoilage and excess inventory. In a conversation we had about the book, Vaclav pointed out that Costco (which might seem like the pinnacle of U.S. consumption) stocks fewer than 4,000 items, compared to 40,000-plus in a typical North American supermarket.

That kind of efficiency—focusing on fewer, high-turnover products—reduces waste, lowers costs, and ultimately eases pressure on global food supply, helping make food more affordable where it is needed most.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Costco and Microsoft. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 09 March 2025:

1. The Troubled Energy Transition – Daniel Yergin, Peter Orszag, and Atul Arya

The fundamental objective of the energy transition is to replace most of today’s energy system with a completely different system. Yet throughout history, no energy source, including traditional biomass of wood and waste, has declined globally in absolute terms over an extended period.

The first energy transition began in 1709, when a metalworker named Abraham Darby figured out that coal provided “a more effective means of iron production” than wood. And the ensuing “transition” took place over at least a century. Although the nineteenth century has been called “the century of coal,” the energy scholar Vaclav Smil has observed that coal did not overtake traditional biomass energy sources (such as wood and crop residues) until the beginning of the twentieth century. Oil, discovered in western Pennsylvania in 1859, would overtake coal as the world’s top energy source in the 1960s. Yet that did not mean that the absolute amount of coal used globally was falling—in 2024, it was three times what it had been in the 1960s.

The same pattern is playing out today. About 30 percent of the world’s population still depends on traditional biomass for cooking, and demand for hydrocarbons has yet to peak or even plateau. The portion of total energy usage represented by hydrocarbons has changed little since 1990, even with the massive growth in renewables. (In the same period, overall energy use has increased by 70 percent.) And the global population is expected to grow by approximately two billion in the coming decades, with much of that growth taking place in the global South. In Africa—a demographically young continent whose population has been projected to increase from 18 percent of the global population today to 25 percent by 2050—almost 600 million people live without electricity, and roughly one billion lack access to clean cooking fuel. Traditional biomass energy still fuels almost half the continent’s total energy consumption…

…Technological, policy, and geopolitical uncertainty makes it challenging to estimate the costs associated with achieving net zero by 2050. But one thing is certain: the costs will be substantial.

The most recent estimate comes from the Independent High-­Level Expert Group on Climate Finance, whose numbers provided a framework for the COP29 meeting—the UN’s annual forum on climate change—in Azerbaijan. It projected that the investment requirement globally for climate action will be $6.3 to $6.7 trillion per year by 2030, rising to as much as $8 trillion by 2035. It further estimated that the global South countries will account for almost 45 percent of the average incremental investment needs from now to 2030, and they have already been falling behind in meeting their financing needs, especially in sub-Saharan Africa.

Based on such estimates, the magnitude of energy-transition costs would average about five percent a year of global GDP between now and 2050. If global South countries are largely exempted from these financial burdens, global North countries would have to spend roughly ten percent of annual GDP—for the United States, over three times the share of GDP represented by defense spending and roughly equal to what the U.S. government spends on Medicare, Medicaid, and Social Security combined…

…In other words, achieving net zero will also require an unprecedented reorganization of capital flows from the global North to the global South, which will necessitate substantial investments in renewable-energy infrastructure at a time when, according to the International Monetary Fund, 56 percent of low-income countries are “at high levels of debt distress.” While innovative financing mechanisms (such as debt-for-climate and debt-for-nature swaps) will help, low sovereign-debt ratings throughout the developing world present a major obstacle to outside investment and raise capital costs. As a result, the bulk of the financial burden will be borne by advanced economies. But even there, debt has risen considerably—average public debt today is over 100 percent of GDP, a level not seen since World War II and a major constraint on governments’ ability to finance the transition through public spending…

…At the moment, almost half the population of the developing world—three billion people—annually uses less electricity per capita than the average American refrigerator does. As energy use grows, “carbonizing” will precede “decarbonizing.” Natural gas is a readily available option, and it’s a better alternative to coal, as well as to traditional biomass fuels that produce harmful indoor air pollution. Although global oil demand seems slated to plateau in the early 2030s, natural gas consumption is expected to continue to increase well into the 2040s. Production of liquefied natural gas is on track to increase by 65 percent by 2040, meeting energy security needs in Europe, replacing coal in Asia, and driving economic growth in the global South…

…The clash of priorities between the North and the South is especially striking when it comes to carbon tariffs. Many global North governments have, as part of their efforts to reduce emissions, put up barriers preventing other countries from taking the same carbon-based economic development path that they took to achieve prosperity. The European Union has launched the first phase of its Carbon Border Adjustment Mechanism. The CBAM is intended to support European climate objectives globally by initially imposing import tariffs on products such as steel, cement, aluminum, and fertilizer based on the carbon emissions embedded in their production and then expanding to more imports. Critics in the global North have argued that such measures would be ineffective because of the enormous complexity of supply chains and the associated difficulty of tracking embedded carbon in imports. Critics in the global South see the CBAM as a barrier to their economic growth. Ajay Seth, India’s economic affairs secretary, has argued that CBAM would force higher costs on the Indian economy: “With income levels which are one-twentieth of the income levels in Europe, can we afford a higher price? No, we can’t.”…

…The International Energy Agency has projected that global demand for the minerals needed for “clean energy technologies” will quadruple by 2040. At the top of the list are such critical minerals as lithium, cobalt, nickel, and graphite, as well as copper. Between 2017 and 2023 alone, demand for lithium increased by 266 percent; demand for cobalt rose by 83 percent; and demand for nickel jumped by 46 percent. Between 2023 and 2035, S&P expects the demand for lithium to increase by another 286 percent; cobalt, by 96 percent; and nickel, by 91 percent. Electric vehicles require two and a half to three times more copper than an internal combustion engine car; battery storage, offshore and onshore wind systems, solar panels, and data centers all require significant amounts of copper. S&P’s analysis of future copper demand found that global copper supply will have to double by the middle of the 2030s to meet current policy ambitions for net-zero emissions by 2050. This is extremely unlikely, considering that, based on S&P data that tracked 127 mines that have come online globally since 2002, it takes more than 20 years to develop a major new mine; in the United States, it takes an average of 29 years…

…China already has a dominant position in mining and a predominant position in the processing of minerals into metals essential for renewable energy infrastructure. It accounts for over 60 percent of the world’s rare-earth mining production (compared with nine percent for the United States) and more than 90 percent of the processing and refining of rare earths. It produces 77 percent of the world’s graphite, processes 98 percent of it, and processes over 70 percent of the world’s lithium and cobalt and almost half the copper.

Beijing aims to extend this dominance to what it calls the “global new energy industrial chain,” with its commanding position in batteries, solar panels, and electric vehicles, as well as in deploying massive amounts of capital toward energy infrastructure in the developing world. With China’s huge scale and low costs, Beijing describes this effort as an extensive and integrated approach to developing and dominating the renewable energy sector. From 2000 to 2022, it issued $225 billion in loans for energy projects in 65 strategically significant nations, with about 75 percent of that directed toward coal, oil, and gas development. Between 2016 and 2022, China provided more energy project financing around the world than any major Western-backed multilateral development bank, including the World Bank…

…Electrification trends suggest that power demand in the United States will double between now and 2050. Electricity consumption is already outpacing recent demand forecasts. PJM, which manages electricity transmission from Illinois to New Jersey, almost doubled its growth projection between 2022 and 2023 and is warning of the danger of shortfalls in electricity before the end of the decade…

…Today’s energy transition is meant to be fundamentally distinct from every previous energy transition: it is meant to be transformative rather than an additive. But so far it is “addition,” not replacement. The scale and variety of the challenges associated with the transition mean that it will not proceed as many expect or in a linear way: it will be multidimensional, proceeding at different rates with a different mix of technologies and different priorities in different regions. That reflects the complexities of the energy system at the foundation of today’s global economy. It also makes clear that the process will unfold over a long period and that continuing investment in conventional energy will be a necessary part of the energy transition.

2. An Interview with Benedict Evans About AI Unknowns – Ben Thompson and Benedict Evans

Well, you wrote about Deep Research a couple of weeks ago and you were pretty disappointed in the output. They used a smartphone report as the demo and it’s interesting, because the Deep Research case that convinced me was actually interview prep, and the key thing about it was, it was a lot of qualitative information that was helpful, and I wasn’t looking for quantitative information. Does that ring true of your experience?

BE: It does, yes. There’s a lot of different things one can say about this, and most of what I said was, it’s kind of interesting and puzzling rather than just, “It’s crap”. It’s very easy to say, “This is amazing and it changes the world, and it’s the fifth industrial revolution”, and it’s very easy to say, “This is all a bunch of crap and it’s the biggest waste of time and money since NFTs, please subscribe to my Substack”, and leave it at that. But what I struggle with is, it’s actually much more interesting and more complicated.

There’s a simple statement which is, “These things are good at things that don’t have wrong answers”. The quote someone used a couple of years ago was, “They tend to be good at things that computers are bad at and bad at things that computers are good at”, they’re very bad at precise specific information retrieval, which is what computers begin with. But on the other hand, you can ask them a question like, “What would be a good thing to take on a picnic?”, and that’s a question that a computer just couldn’t answer, that’s not a SQL query, and an LLM can answer that.

I think a lot of the product challenge and use case challenge around these things is trying to work out how you translate that into something that you’re actually trying to do. You gave the example of interview prep, which is — actually I don’t do interviews, but that would be something where, yeah, I can see that would be useful. The funny thing here is that OpenAI, I wasn’t testing it myself, I went and looked at OpenAI’s own product page, this is their test where they’re telling me this is what it’s for and this is what it’s good at, and proceed to show it to doing precise information retrieval, which of course, it can’t do. So just for the people who haven’t looked into OpenAI’s product page, it suggests some use cases, and one of them is, “Make a table of a bunch of countries with smartphone adoption by operating system””, and also stuff like, “Who wants to learn languages”.

The wrong report for the wrong guy.

BE: Yeah. The problem is, as many people may know, I used to be a telecoms analyst, so I looked at this and thought, “Okay, well let me have a look”. Problem one is, it used Statista, which is basically an SEO spam house that aggregates other people’s data. Saying “Source: Statista” at best is kind of saying “Source: a Google Search”, they’re not actually telling me what the source is and secondly, StatCounter, which tells you traffic. And I looked at this and I thought — I won’t monologue too long, I promise — I looked at this and I thought-

No, this is great. I completely agree with where you’re going.

BE: -there’s two questions here. The first is, is this model accurately working out what sources it should use? And then, is it getting the correct data from those sources?

And the question that OpenAI have posed is smartphone adoption. Well, what does that mean exactly? Are you asking me about unit sales? Are you asking about the install base? Are you asking me about usage? Are you asking me about outdoor usage? Because a use case that they propose actually was something like a translation app. Adoption isn’t any of those, it might be any of those, depending on context.

ChatGPT has come up with, number one, StatCounter, which is a metric of usage, not the install base and then, it’s come up with Statista, which is actually going to Kantar, which I think is doing install base, but I’m not sure, and those two come up with two different numbers, and the number that’s in ChatGPT, the Deep Research report, is a third number.

The thing that I thought about this was, you’ve asked this a probabilistic question, not a deterministic question. You’ve asked it a “What should I take on a picnic?”-type question, you haven’t asked it a precise database-y question where a computer would know the answer. You’ve asked it to work out what you want, and then you’ve asked it to work out where to get it from, and then you’ve asked it to do the database retrieval and actually report what’s on those pages. It’s kind of done okay at the first two, or it’s done what I would expect an intern to do on the first two, and as I wrote, if I had an intern, I would’ve said, “This is why you wouldn’t use either of those two”.

Yeah.

BE: But an intern wouldn’t know, and then it’s copied the number down wrong, which is where you smack the intern on the back of the head and tell them to go back and do it again. There’s a lot of different ways you can talk about this. Are you using these things for precise information retrieval? Are you using them for things that don’t really have wrong answers? Are you using them for qual or for quant? Are you using them for brainstorming? How do you work out what your problem is and whether it would be good at that, and how it would map against that?

But at the end of the day, I went and asked it to do a thing and it told me it had done the thing, and it’s wrong. In fact, it’s worse than that. OpenAI asked it to do the thing and it did the thing, and it was wrong.

And then put it up as a demo!

BE: There’s this really profoundly important thing here, which I had this feeling looking at the new Claude model today as well, or yesterday, is people talk about these models getting better a lot, but if you’ve given me a table with 20 entries and some of them are wrong, what do you mean when you say the model’s better? Do you mean that all the odd entries are right? Or do you mean that the entries are more likely to be right? Those are very different things. The idea that we would get to these models to the point that they always would be right and you would know that in a way that you would know a database would be right, we have no idea if that’s possible. That’s a profound scientific question in the field. What do you do with something that can do amazing things but you don’t know if it’s right?…

…You made this point, this tool’s the most helpful if you are already an expert because it saves you time and you can identify the errors. But if you’re not an expert, it’s incredibly dangerous. I wrote about this a couple of weeks ago, I asked for this report on an industry I happen to know a lot about, and Deep Research completely missed a big player because it was a private company, there was no listings about it even though anyone in the field would have known about it. You now have an unknown known, there’s something that you think you know, but actually, you don’t know. You’ve been convinced to be more ignorant.

BE: Yeah, listening to you talk, I’m reminded, actually, of one of these very old fallacies from engineers, which is to say, “The users have to learn how it works”, which is the thing you see with open source over and over again or, “The users will have to learn”. Of course you can say that, but the users won’t learn and it’s not the user’s job to learn how it works. The more that you force people to have to understand how it works, the more you limit the potential adoption of it.

Zooming back a little bit, something that I have in draft at the moment is that, if we think about where we’ve come in the last whatever it is, two and a bit years since GPT 3.5 launched, at the beginning of 2023, say, you could think there was a cluster of questions that would determine what was going to happen. How much will these scale? How big will the models get? How expensive will it be? What will happen to the error rates? What will reasoning be? Are there barriers to entry? Are there winner-takes-all effects? Is there enough data? You can make a list of a dozen questions, they all kind of link together.

Out of that there’s one possible output which is there’s one computer that runs the whole world, and the other extreme is it ends up being like databases or indeed like machine learning in which if you were to say today, “How many databases are there?”, that’s just a meaningless question. What are you talking about?

Since then, none of those questions have really been answered, except for the extent that it seems clear right now that these things are going to be commodities, although still quite expensive commodities. But anyone who’s got a billion dollars can have one, you don’t need a hundred billion dollars, and there’s not a lot of winner-takes-all effect the way there was with smartphones. Anyone who’s got $500 million or $100 million dollars, or something, pick a number, can have an outlet, can have a frontier model. But all the other questions, we don’t know. We don’t know what will happen to the error rate. We don’t know how big the models will get or how long the scaling works.

One of the things that kind of came out of that was, there’s a path that says, you can just go to ChatGPT and say, “I want to move to Taiwan, how do I do that?”, “I need to file my taxes in New York, London, and California, do it for me”. And the model can go and read the right websites and ask you for a photograph of your bank statement and just make you the PDF and do it for you…

…BE: And suddenly, there’s this explosion of complexity in the data centers, and we have to know about it. You have to know chips, and there are all these papers. But I did this deck, I do this annual presentation, and I ended my presentation, the section that talked about scaling, with a quote from the Godfather that says, “If history teaches you anything, it’s that you can kill anybody”, and I crossed out, “Kill anybody” and said, “Commodity computing tends to get cheap”. You’ve got all of this complexity in the creation of the models and the data center and everything else, and yet, I don’t know, I look at Grok and I think, okay, in less than two years, you managed to produce a state-of-the-art model. Is that really, really good or really, really bad?

That’s bearish for model creation.

BE: That is not as positive as you think. Yes, they’re a great team, and well done for building a 100,000 GPU cluster, but what this tell us is it’s a commodity…

…BE: There’s no difference, that’s what that means. But yeah, I think you can extend this to the doomers, where it was clear that the people who were thinking this stuff is going to take over the world in the next three months just had no conception of how the world worked outside of their shared group house in the Berkeley Hills. The puzzle and the analogy I always used to give, looking at, going back to talking about use cases, is imagine the first people seeing VisiCalc, the first spreadsheet in the late ’70s.

Yep.

BE: So if you saw this and you were an accountant, it blew your mind because the line is like you change the interest rate here and all the other numbers on the spreadsheet change.

Yep. [John] Gruber and I were just talking about this the other day, and you could watch it change!

BE: You say that now and people now are like, “Yes…?”, but back then you did spreadsheets on paper with a pencil and so if you’re an accountant, you have to have this. Certainly, you can look up the pricing of the Apple II that you needed to run VisiCalc, the full setup with a floppy drive and a printer and a monitor was like 15 grand adjusted for inflation. But if you were a lawyer and you see it, you think, “Well, that’s great, my accountant should see this, but that’s not what I do all day”.

Yep.

BE: Now, show me a word processor that can do word counts and footnotes and line numbers. That, I will pay for, that solves a problem that I have. And the challenge of the text box and the blinking cursor is either you really know you’ve got a problem that it solves, which is coding and marketing, or you’re the kind of person that’s instinctively looking for tools to solve things in their company, which is the bottom-up IT adoption and it’s no coding and everything else, but that’s a very small portion of the population.

And then it’s everybody else who didn’t see that they had that problem until an enterprise SaaS company came and showed them that they were spending three hours a week on it and sold them something for 10 grand a seat to fix it. Otherwise, you’ve got this prompt. What do I do with it?

I completely agree with you and this is where one of the analogies I’ve been thinking about is going back to the first — arguably the greatest direct job displacement in IT was actually the first mainframes, where it’s just like, “Okay, we don’t need an entire backroom of bookkeepers, we don’t need an entire backroom of ERP trackers, we can just do it on a computer”, and it was like a one-to-one replacement. What’s interesting about this is right now, AI is a bottoms-up phenomenon because you need so much agency to go out and find a way to use this, and because the model doesn’t learn, you have to learn how to use the model. It’s like people wanting to bring PCs to work in the late ’70s, and it’s like, “What are you trying to do here?”.

BE: And if you look at what these people were doing, all the books and magazines at the time were, “You should learn to code. Or at a minimum, you need to buy a database software program”. So it wasn’t you buy Quicken, it’s you buy a database plus software program and you make your own Quicken by yourself.

That’s such a great point, it’s the same thing it was with code. That was the thing at the beginning and you can do something yourself, it’s an excellent point. But it does make me think that if you’re a top-down decision maker, you can, number one, decide that the cost-benefit is worth actually removing an entire category or entire department. And number two, you can tolerate the error rate because you’ll do a cost-benefit analysis that says, “Okay, I’m at X percent error rate, this is going to cost me Y amount of money. How does that balance versus this collection of humans who are also going to make X amount of errors and cost me Y amount of money?” And you go in and you just shift people out and that is actually going to be a more meaningful change or where it’s going to start. It’s going to be less about getting people to fundamentally change how they work and more about, “You know what? We can do it good enough with AI for this whole category of work. Sorry, you guys are laid off”.

BE: Yeah, I think it depends. And if you go back and think about how the last waves of automated enterprise software worked, whether it’s SaaS or on-prem or whatever, there’s two or three things here. So one of them is you don’t just replace a whole department with one piece of software.

No, not now. I’m talking about back in the ’70s.

BE: Yeah. But the other part of that is that didn’t result in fewer white-collar workers or fewer accountants. Excel didn’t result in fewer accountants. I mean, my joke was always that, young people won’t believe this, but before Excel, investment bankers worked really long hours. Now they can get their work finished at lunchtime on Fridays and go home to The Hamptons. And of course, that’s not what happened.

Well, why is it that that isn’t what happened? I think, and it comes back to what I was saying earlier, the base case here is that you work in invoice processing and now you have a new piece of software that’s better at resolving failed invoice payments, and that is worth X-hundred thousand dollars a year to your company, and so they come out and they buy this piece of software. Or it’s a feature that gets added to their existing software or it plugs into SAP or Salesforce or Oracle or whatever it is, and it’s that piece of software and today, the typical big company has 400 or 500 SaaS applications, maybe more. And the HR team, account department has 45 different applications, there’s the German tax planning thing, and there’s the thing that manages stock options, and there’s the thing that manages training for new recruits, and the thing that makes sure that everybody’s taking their compliance exam, and the other thing that makes sure everyone’s done their compliance exam, and the training thing, and you just keep adding these all up. And they all find value and they all find budget and they all move costs from one place to another and the big company has 400 or 500 other new things.

The base case is that generative AI will be another 400 or 500 of these, and it will replace half of them, and it will double the value of the other half. 250 of them will get killed and 250 of them will get a bunch of new features and there’ll be another 250 of them on top, and now you’ll have 750 or 1,000 new applications in this company and there will be bits of LLM scattered all the way through them just as there’s bits of machine learning scattered all the way through them, just as there’s databases scattered all the way through them. It will just be kind of a building block in making software. Does that mean that there’s less net employment or does that just mean that a bunch of jobs go away and get replaced by new jobs?…

…BE: If you’re in the accounting industry, this changes the whole nature of your industry, so that’s one observation.

The second observation would be — yes, you don’t know what those changes will be, you don’t know how it is, what all the new things it will be, you start by doing what you already know you need to do. And then over time, you realize there’s new things you can do with this, which is your point about feeds, and you could say the same thing about the emergence of Instagram and online dating, all the stuff that happened that wasn’t obvious at the time.

However, I think there’s a completely opposite point, which is equally interesting, about how new this is or how different this is, which is that if you’re looking at the Internet in 1995, you kind of knew how fast computers were and how fast they’d be in like five years, and you knew how many people had broadband, and you had a pretty good sense — you could plot a line on a chart of how many people are going to have broadband and how fast, on a three to five-year view and you kind of knew how much PCs cost, and you knew what annual PC sales were, and you could make a guess that, okay, this is going to mean that PC sales quadruple and everyone will go out and buy a PC, which is more or less what happened, and you knew how many middle-class households there were in America, so you kind of knew what the PC market could, in principle, do. The same thing with smartphones, you knew how fast 3G was, you knew how fast 4G was, you knew how fast the chips were.

What I was getting at is, with LLMs, we don’t know that. We don’t know what that roadmap is for the fundamental technical capabilities of the thing, which is different to anything from the web to flight or cars. We weren’t looking at a smartphone and saying, “Well, this is where we are today, but maybe in two or three years, it will be able to unroll and fill the whole wall, or maybe it’ll have a year’s battery life”. You kind of knew what the really basic core physics constraints were, and we don’t know that for this stuff.

Well, especially with this accuracy point. Daniel Gross made this point a few weeks ago too, I think it’s really profound, that there’s just a really stark fundamental difference between 100% accuracy and 99% accuracy.

BE: Well, this is a problem with saying “better” models. What do you mean “better”? Do you mean it was 82 and now it’s 83? Or do you mean it was 80 and now it’s 100 and it will always be 100? That’s a completely different thing.

3. Reality has a surprising amount of detail – John Salvatier

It’s tempting to think ‘So what?’ and dismiss these details as incidental or specific to stair carpentry. And they are specific to stair carpentry; that’s what makes them details. But the existence of a surprising number of meaningful details is not specific to stairs. Surprising detail is a near universal property of getting up close and personal with reality.

You can see this everywhere if you look. For example, you’ve probably had the experience of doing something for the first time, maybe growing vegetables or using a Haskell package for the first time, and being frustrated by how many annoying snags there were. Then you got more practice and then you told yourself ‘man, it was so simple all along, I don’t know why I had so much trouble’. We run into a fundamental property of the universe and mistake it for a personal failing.

If you’re a programmer, you might think that the fiddliness of programming is a special feature of programming, but really it’s that everything is fiddly, but you only notice the fiddliness when you’re new, and in programming you do new things more often.

You might think the fiddly detailiness of things is limited to human centric domains, and that physics itself is simple and elegant. That’s true in some sense – the physical laws themselves tend to be quite simple – but the manifestation of those laws is often complex and counterintuitive…

…The more difficult your mission, the more details there will be that are critical to understand for success.

You might hope that these surprising details are irrelevant to your mission, but not so. Some of them will end up being key. Wood’s tendency to warp means it’s more accurate to trace a cut than to calculate its length and angle. The possibility of superheating liquids means it’s important to use a packed bed when boiling liquids in industrial processes lest your process be highly inefficient and unpredictable. The massive difference in weight between a rocket full of fuel and an empty one means that a reusable rocket can’t hover if it can’t throttle down to a very small fraction of its original thrust, which in turn means it must plan its trajectory very precisely to achieve 0 velocity at exactly the moment it reaches the ground.

You might also hope that the important details will be obvious when you run into them, but not so. Such details aren’t automatically visible, even when you’re directly running up against them. Things can just seem messy and noisy instead. ‘Spirit’ thermometers, made using brandy and other liquors, were in common use in the early days of thermometry. They were even considered as a potential standard fluid for thermometers. It wasn’t until the careful work of Swiss physicist Jean-André De Luc in the 18th century that physicists realized that alcohol thermometers are highly nonlinear and highly variable depending on concentration, which is in turn hard to measure.

You’ve probably also had experiences where you were trying to do something and growing increasingly frustrated because it wasn’t working, and then finally, after some time you realize that your solution method can’t possibly work.

Another way to see that noticing the right details is hard, is that different people end up noticing different details…

…Before you’ve noticed important details they are, of course, basically invisible. It’s hard to put your attention on them because you don’t even know what you’re looking for. But after you see them they quickly become so integrated into your intuitive models of the world that they become essentially transparent. Do you remember the insights that were crucial in learning to ride a bike or drive? How about the details and insights you have that led you to be good at the things you’re good at?

This means it’s really easy to get stuck. Stuck in your current way of seeing and thinking about things. Frames are made out of the details that seem important to you. The important details you haven’t noticed are invisible to you, and the details you have noticed seem completely obvious and you see right through them. This all makes makes it difficult to imagine how you could be missing something important…

…If you’re trying to do impossible things, this effect should chill you to your bones. It means you could be intellectually stuck right at this very moment, with the evidence right in front of your face and you just can’t see it.

This problem is not easy to fix, but it’s not impossible either. I’ve mostly fixed it for myself. The direction for improvement is clear: seek detail you would not normally notice about the world. When you go for a walk, notice the unexpected detail in a flower or what the seams in the road imply about how the road was built. When you talk to someone who is smart but just seems so wrong, figure out what details seem important to them and why. In your work, notice how that meeting actually wouldn’t have accomplished much if Sarah hadn’t pointed out that one thing. As you learn, notice which details actually change how you think.

If you wish to not get stuck, seek to perceive what you have not yet perceived.

4. America’s Growing Trade Deficit Is Selling the Nation Out From Under Us. Here’s a Way to Fix the Problem – And We Need to Do It Now – Warren Buffett

Take a fanciful trip with me to two isolated, side-by-side islands of equal size, Squanderville and Thriftville. Land is the only capital asset on these islands, and their communities are primitive, needing only food and producing only food. Working eight hours a day, in fact, each inhabitant can produce enough food to sustain himself or herself. And for a long time that’s how things go along…

…Eventually, though, the industrious citizens of Thriftville decide to do some serious saving and investing, and they start to work 16 hours a day. In this mode, they continue to live off the food they produce in the eight hours of work but begin exporting an equal amount to their one and only trading outlet, Squanderville.

The citizens of Squanderville are ecstatic about this turn of events, since they can now live their lives free from toil but eat as well as ever. Oh, yes, there’s a quid pro quo – but to the Squanders, it seems harmless: All that the Thrifts want in exchange for their food is Squanderbonds (which are denominated, naturally, in Squanderbucks).

Over time Thriftville accumulates an enormous amount of these bonds, which at their core represent claim checks on the future output of Squanderville. A few pundits in Squanderville smell trouble coming. They foresee that for the Squanders both to eat and pay off – or simply service – the debt they’re piling up will eventually require them to work more than eight hours a day…

…Meanwhile, the citizens of Thriftville begin to get nervous. Just how good, they ask, are the IOUs of a shiftless island? So the Thrifts change strategy: Though they continue to hold some bonds, they sell most of them to Squanderville residents for Squanderbucks and use the proceeds to buy Squanderville land. And eventually the Thrifts own all of Squanderville.

At that point, the Squanders are forced to deal with an ugly equation: They must now not only return to working eight hours a day in order to eat—they have nothing left to trade—but must also work additional hours to service their debt and pay Thriftville rent on the land so imprudently sold. In effect, Squanderville has been colonized by purchase rather than conquest.

It can be argued, of course, that the present value of the future production that Squanderville must forever ship to Thriftville only equates to the production Thriftville initially gave up and that therefore both have received a fair deal. But since one generation of Squanders gets the free ride and future generations pay in perpetuity for it, there are—in economist talk—some pretty dramatic “intergenerational inequities.”…

…Sooner or later the Squanderville government, facing ever greater payments to service debt, would decide to embrace highly inflationary policies—that is, issue more Squanderbucks to dilute the value of each. After all, the government would reason, those irritating Squanderbonds are simply claims on specific numbers of Squanderbucks, not on bucks of specific value. In short, making Squanderbucks less valuable would ease the island’s fiscal pain.

That prospect is why I, were I a resident of Thriftville, would opt for direct ownership of Squanderville land rather than bonds of the island’s government. Most governments find it much harder morally to seize foreign-owned property than they do to dilute the purchasing power of claim checks foreigners hold. Theft by stealth is preferred to theft by force…

…The time to halt this trading of assets for consumables is now, and I have a plan to suggest for getting it done. My remedy may sound gimmicky, and in truth it is a tariff called by another name. But this is a tariff that retains most free-market virtues, neither protecting specific industries nor punishing specific countries nor encouraging trade wars. This plan would increase our exports and might well lead to increased overall world trade. And it would balance our books without there being a significant decline in the value of the dollar, which I believe is otherwise almost certain to occur.

We would achieve this balance by issuing what I will call Import Certificates (ICs) to all U.S. exporters in an amount equal to the dollar value of their exports. Each exporter would, in turn, sell the ICs to parties—either exporters abroad or importers here—wanting to get goods into the U.S. To import $1 million of goods, for example, an importer would need ICs that were the byproduct of $1 million of exports. The inevitable result: trade balance.

Because our exports total about $80 billion a month, ICs would be issued in huge, equivalent quantities—that is, 80 billion certificates a month—and would surely trade in an exceptionally liquid market. Competition would then determine who among those parties wanting to sell to us would buy the certificates and how much they would pay. (I visualize that the certificates would be issued with a short life, possibly of six months, so that speculators would be discouraged from accumulating them.)

For illustrative purposes, let’s postulate that each IC would sell for 10 cents—that is, 10 cents per dollar of exports behind them. Other things being equal, this amount would mean a U.S. producer could realize 10% more by selling his goods in the export market than by selling them domestically, with the extra 10% coming from his sales of ICs.

In my opinion, many exporters would view this as a reduction in cost, one that would let them cut the prices of their products in international markets. Commodity-type products would particularly encourage this kind of behavior. If aluminum, for example, was selling for 66 cents per pound domestically and ICs were worth 10%, domestic aluminum producers could sell for about 60 cents per pound (plus transportation costs) in foreign markets and still earn normal margins. In this scenario, the output of the U.S. would become significantly more competitive and exports would expand. Along the way, the number of jobs would grow…

…To see what would happen to imports, let’s look at a car now entering the U.S. at a cost to the importer of $20,000. Under the new plan and the assumption that ICs sell for 10%, the importer’s cost would rise to $22,000. If demand for the car was exceptionally strong, the importer might manage to pass all of this on to the American consumer. In the usual case, however, competitive forces would take hold, requiring the foreign manufacturer to absorb some, if not all, of the $2,000 IC cost.

There is no free lunch in the IC plan: It would have certain serious negative consequences for U.S. citizens. Prices of most imported products would increase, and so would the prices of certain competitive products manufactured domestically. The cost of the ICs, either in whole or in part, would therefore typically act as a tax on consumers.

That is a serious drawback. But there would be drawbacks also to the dollar continuing to lose value or to our increasing tariffs on specific products or instituting quotas on them—courses of action that in my opinion offer a smaller chance of success. Above all, the pain of higher prices on goods imported today dims beside the pain we will eventually suffer if we drift along and trade away ever larger portions of our country’s net worth.

I believe that ICs would produce, rather promptly, a U.S. trade equilibrium well above present export levels but below present import levels. The certificates would moderately aid all our industries in world competition, even as the free market determined which of them ultimately met the test of “comparative advantage.”

This plan would not be copied by nations that are net exporters, because their ICs would be valueless. Would major exporting countries retaliate in other ways? Would this start another Smoot-Hawley tariff war? Hardly. At the time of Smoot-Hawley we ran an unreasonable trade surplus that we wished to maintain. We now run a damaging deficit that the whole world knows we must correct…

…The likely outcome of an IC plan is that the exporting nations—after some initial posturing—will turn their ingenuity to encouraging imports from us. Take the position of China, which today sells us about $140 billion of goods and services annually while purchasing only $25 billion. Were ICs to exist, one course for China would be simply to fill the gap by buying 115 billion certificates annually. But it could alternatively reduce its need for ICs by cutting its exports to the U.S. or by increasing its purchases from us. This last choice would probably be the most palatable for China, and we should wish it to be so.

If our exports were to increase and the supply of ICs were therefore to be enlarged, their market price would be driven down. Indeed, if our exports expanded sufficiently, ICs would be rendered valueless and the entire plan made moot. Presented with the power to make this happen, important exporting countries might quickly eliminate the mechanisms they now use to inhibit exports from us.

5. The hidden cost of AI: Trading long-term resilience for short-term efficiency – Eric Markowitz

AI is the latest in a long lineage of efficiency-maximizing tools. It promises to make research instantaneous, strip away uncertainty, and optimize everything from hiring to investment analysis. But for all the gains in speed and precision, we rarely stop to ask: What are we losing in return? Because there is no such thing as a free lunch…

…AI makes the world feel more scientific than ever. It can generate business strategies, write persuasive emails, and surface patterns invisible to human analysis. But the most important decisions — the ones that lead to breakthroughs, revolutions, and paradigm shifts — are rarely the result of pure data analysis.

Some of the best ideas in history looked irrational at first. They required deep research, yes — but more importantly, they required taste. (And perhaps a bit of luck.)

Taste is an underrated concept in a world obsessed with efficiency. It’s the ability to recognize something valuable before the numbers prove it. The ability to see beyond spreadsheets and sentiment analysis and understand how an idea actually fits into the world. If everyone has access to the same AI-generated insights, the only thing that remains scarce is independent thinking. And that is precisely where the edge lies.

None of this is an argument against AI. It’s an argument for knowing what not to outsource to our robot overlords. AI is a tool. A powerful one. But it is not a substitute for intuition, nor a replacement for deep thinking. The institutions and ideas that endure the longest are those that understand what to hold onto even as the world around them changes. 

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Alphabet (parent of Google). Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 02 March 2025:

1. Satya Nadella – Microsoft’s AGI Plan & Quantum Breakthrough – Dwarkesh Patel and Satya Nadella

Dwarkesh Patel

Where is the value going to be created in AI?

Satya Nadella

That’s a great one. So I think there are two places where I can say with some confidence. One is the hyperscalers that do well, because the fundamental thing is if you sort of go back to even how Sam and others describe it, if intelligence is log of compute, whoever can do lots of compute is a big winner.

The other interesting thing is, if you look at underneath even any AI workload, like take ChatGPT, it’s not like everybody’s excited about what’s happening on the GPU side, it’s great. In fact, I think of my fleet even as a ratio of the AI accelerator to storage, to compute. And at scale, you’ve got to grow it…

…Satya Nadella

So in fact it’s manna from heaven to have these AI workloads because guess what? They’re more hungry for more compute, not just for training, but we now know, for test time. When you think of an AI agent, it turns out the AI agent is going to exponentially increase compute usage because you’re not even bound by just one human invoking a program. It’s one human invoking programs that invoke lots more programs. That’s going to create massive, massive demand and scale for compute infrastructure. So our hyperscale business, Azure business, and other hyperscalers, I think that’s a big thing.

Then after that, it becomes a little fuzzy. You could say, hey, there is a winner-take-all model- I just don’t see it. This, by the way, is the other thing I’ve learned: being very good at understanding what are winner-take-all markets and what are not winner-take-all markets is, in some sense, everything. I remember even in the early days when I was getting into Azure, Amazon had a very significant lead and people would come to me, and investors would come to me, and say, “Oh, it’s game over. You’ll never make it. Amazon, it’s winner-take-all.”

Having competed against Oracle and IBM in client-server, I knew that the buyers will not tolerate winner-take-all. Structurally, hyperscale will never be a winner-take-all because buyers are smart.

Consumer markets sometimes can be winner-take-all, but anything where the buyer is a corporation, an enterprise, an IT department, they will want multiple suppliers. And so you got to be one of the multiple suppliers.

That, I think, is what will happen even on the model side. There will be open-source. There will be a governor. Just like on Windows, one of the big lessons learned for me was, if you have a closed-source operating system, there will be a complement to it, which will be open source.

And so to some degree that’s a real check on what happens. I think in models there is one dimension of, maybe there will be a few closed source, but there will definitely be an open source alternative, and the open-source alternative will actually make sure that the closed-source, winner-take-all is mitigated.

That’s my feeling on the model side. And by the way, let’s not discount if this thing is really as powerful as people make it out to be, the state is not going to sit around and wait for private companies to go around and… all over the world. So, I don’t see it as a winner-take-all.

Then above that, I think it’s going to be the same old stuff, which is in consumer, in some categories, there may be some winner-take-all network effect. After all, ChatGPT is a great example.

It’s an at-scale consumer property that has already got real escape velocity. I go to the App Store, and I see it’s always there in the top five, and I say “wow, that’s pretty unbelievable”.

So they were able to use that early advantage and parlay that into an app advantage. In consumer, that could happen. In the enterprise again, I think there will be, by category, different winners. That’s sort of at least how I analyze it…

…Satya Nadella

The way I come at it, Dwarkesh, it’s a great question because at some level, if you’re going to have this explosion, abundance, whatever, commodity of intelligence available, the first thing we have to observe is GDP growth.

Before I get to what Microsoft’s revenue will look like, there’s only one governor in all of this. This is where we get a little bit ahead of ourselves with all this AGI hype. Remember the developed world, which is what? 2% growth and if you adjust for inflation it’s zero?

So in 2025, as we sit here, I’m not an economist, at least I look at it and say we have a real growth challenge. So, the first thing that we all have to do is, when we say this is like the Industrial Revolution, let’s have that Industrial Revolution type of growth.

That means to me, 10%, 7%, developed world, inflation-adjusted, growing at 5%. That’s the real marker. It can’t just be supply-side.

In fact that’s the thing, a lot of people are writing about it, and I’m glad they are, which is the big winners here are not going to be tech companies. The winners are going to be the broader industry that uses this commodity that, by the way, is abundant. Suddenly productivity goes up and the economy is growing at a faster rate. When that happens, we’ll be fine as an industry.

But that’s to me the moment. Us self-claiming some AGI milestone, that’s just nonsensical benchmark hacking to me. The real benchmark is: the world growing at 10%.

Dwarkesh Patel

Okay, so if the world grew at 10%, the world economy is $100 trillion or something, if the world grew at 10%, that’s like an extra $10 trillion in value produced every single year. If that is the case, you as a hyperscaler… It seems like $80 billion is a lot of money. Shouldn’t you be doing like $800 billion?

If you really think in a couple of years, we could be really growing the world economy at this rate, and the key bottleneck would be: do you have the compute necessary to deploy these AIs to do all this work?

Satya Nadella

That is correct. But by the way, the classic supply side is, “Hey, let me build it and they’ll come.” That’s an argument, and after all we’ve done that, we’ve taken enough risk to go do it.

But at some point, the supply and demand have to map. That’s why I’m tracking both sides of it. You can go off the rails completely when you are hyping yourself with the supply-side, versus really understanding how to translate that into real value to customers.

That’s why I look at my inference revenue. That’s one of the reasons why even the disclosure on the inference revenue… It’s interesting that not many people are talking about their real revenue, but to me, that is important as a governor for how you think about it.

You’re not going to say they have to symmetrically meet at any given point in time, but you need to have existence proof that you are able to parlay yesterday’s, let’s call it capital, into today’s demand, so that then you can again invest, maybe exponentially even, knowing that you’re not going to be completely rate mismatched.

Dwarkesh Patel

I wonder if there’s a contradiction in these two different viewpoints, because one of the things you’ve done wonderfully is make these early bets. You invested in OpenAI in 2019, even before there was Copilot and any applications.

If you look at the Industrial Revolution, these 6%, 10% build-outs of railways and whatever things, many of those were not like, “We’ve got revenue from the tickets, and now we’re going to…”

Satya Nadella

There was a lot of money lost.

Dwarkesh Patel

That’s true. So, if you really think there’s some potential here to 10x or 5x the growth rate of the world, and then you’re like, “Well, what is the revenue from GPT-4?”

If you really think that’s the possibility from the next level up, shouldn’t you just, “Let’s go crazy, let’s do the hundreds of billions of dollars of compute?” I mean, there’s some chance, right?

Satya Nadella

Here’s the interesting thing, right? That’s why even that balanced approach to the fleet, at least, is very important to me. It’s not about building compute. It’s about building compute that can actually help me not only train the next big model but also serve the next big model. Until you do those two things, you’re not going to be able to really be in a position to take advantage of even your investment.

So, that’s kind of where it’s not a race to just building a model, it’s a race to creating a commodity that is getting used in the world to drive… You have to have a complete thought, not just one thing that you’re thinking about.

And by the way, one of the things is that there will be overbuild. To your point about what happened in the dotcom era, the memo has gone out that, hey, you know, you need more energy, and you need more compute. Thank God for it. So, everybody’s going to race.

In fact, it’s not just companies deploying, countries are going to deploy capital, and there will be clearly… I’m so excited to be a leaser, because, by the way; I build a lot, I lease a lot. I am thrilled that I’m going to be leasing a lot of capacity in ’27, ’28 because I look at the builds, and I’m saying, “This is fantastic.” The only thing that’s going to happen with all the compute builds is the prices are going to come down…

…Satya Nadella

This has been another 30-year journey for us. It’s unbelievable. I’m the third CEO of Microsoft who’s been excited about quantum.

The fundamental breakthrough here, or the vision that we’ve always had is, you need a physics breakthrough in order to build a utility-scale quantum computer that works. We took the path of saying, the one way for having a less noisy or more reliable qubit is to bet on a physical property that by definition is more reliable and that’s what led us to the Majorana zero modes, which was theorized in the 1930s. The question was, can we actually physically fabricate these things? Can we actually build them?

So the big breakthrough effectively, and I know you talked to Chetan, was that we now finally have existence proof and a physics breakthrough of Majorana zero modes in a new phase of matter effectively. This is why we like the analogy of thinking of this as the transistor moment of quantum computing, where we effectively have a new phase, which is the topological phase, which means we can even now reliably hide the quantum information, measure it, and we can fabricate it. And so now that we have it, we feel like with that core foundational fabrication technique out of the way, we can start building a Majorana chip.

That Majorana One which I think is going to basically be the first chip that will be capable of a million qubits, physical. And then on that, thousands of logical qubits, error-corrected. And then it’s game on. You suddenly have the ability to build a real utility-scale quantum computer, and that to me is now so much more feasible. Without something like this, you will still be able to achieve milestones, but you’ll never be able to build a utility-scale computer. That’s why we’re excited about it…

…Satya Nadella

It’s a great question. One thing that I’ve been excited about is, even in today’s world… we had this quantum program, and we added some APIs to it. The breakthrough we had maybe two years ago was to think of this HPC stack, and AI stack, and quantum together.

In fact, if you think about it, AI is like an emulator of the simulator. Quantum is like a simulator of nature. What is quantum going to do? By the way, quantum is not going to replace classical. Quantum is great at what quantum can do, and classical will also…

Quantum is going to be fantastic for anything that is not data-heavy but is exploration-heavy in terms of the state space. It should be data-light but exponential states that you want to explore. Simulation is a great one: chemical physics, what have you, biology.

One of the things that we’ve started doing is really using AI as the emulation engine. But you can then train. So the way I think of it is, if you have AI plus quantum, maybe you’ll use quantum to generate synthetic data that then gets used by AI to train better models that know how to model something like chemistry or physics or what have you. These two things will get used together.

So even today, that’s effectively what we’re doing with the combination of HPC and AI. I hope to replace some of the HPC pieces with quantum computers.

2. Microsoft’s Majorana 1 chip carves new path for quantum computing – Catherine Bolgar

Microsoft today introduced Majorana 1, the world’s first quantum chip powered by a new Topological Core architecture that it expects will realize quantum computers capable of solving meaningful, industrial-scale problems in years, not decades.

It leverages the world’s first topoconductor, a breakthrough type of material which can observe and control Majorana particles to produce more reliable and scalable qubits, which are the building blocks for quantum computers.

In the same way that the invention of semiconductors made today’s smartphones, computers and electronics possible, topoconductors and the new type of chip they enable offer a path to developing quantum systems that can scale to a million qubits and are capable of tackling the most complex industrial and societal problems, Microsoft said…

…This new architecture used to develop the Majorana 1 processor offers a clear path to fit a million qubits on a single chip that can fit in the palm of one’s hand, Microsoft said. This is a needed threshold for quantum computers to deliver transformative, real-world solutions – such as breaking down microplastics into harmless byproducts or inventing self-healing materials for construction, manufacturing or healthcare. All the world’s current computers operating together can’t do what a one-million-qubit quantum computer will be able to do…

…The topoconductor, or topological superconductor, is a special category of material that can create an entirely new state of matter – not a solid, liquid or gas but a topological state. This is harnessed to produce a more stable qubit that is fast, small and can be digitally controlled, without the tradeoffs required by current alternatives…

…This breakthrough required developing an entirely new materials stack made of indium arsenide and aluminum, much of which Microsoft designed and fabricated atom by atom…

…Commercially important applications will also require trillions of operations on a million qubits, which would be prohibitive with current approaches that rely on fine-tuned analog control of each qubit. The Microsoft team’s new measurement approach enables qubits to be controlled digitally, redefining and vastly simplifying how quantum computing works.

This progress validates Microsoft’s choice years ago to pursue a topological qubit design – a high risk, high reward scientific and engineering challenge that is now paying off. Today, the company has placed eight topological qubits on a chip designed to scale to one million…

…But reaching the next horizon of quantum computing will require a quantum architecture that can provide a million qubits or more and reach trillions of fast and reliable operations. Today’s announcement puts that horizon within years, not decades, Microsoft said.

Because they can use quantum mechanics to mathematically map how nature behaves with incredible precision – from chemical reactions to molecular interactions and enzyme energies – million-qubit machines should be able to solve certain types of problems in chemistry, materials science and other industries that are impossible for today’s classical computers to accurately calculate…

…Most of all, quantum computing could allow engineers, scientists, companies and others to simply design things right the first time – which would be transformative for everything from healthcare to product development. The power of quantum computing, combined with AI tools, would allow someone to describe what kind of new material or molecule they want to create in plain language and get an answer that works straightaway – no guesswork or years of trial and error.

“Any company that makes anything could just design it perfectly the first time out. It would just give you the answer,” Troyer said. “The quantum computer teaches the AI the language of nature so the AI can just tell you the recipe for what you want to make.”…

…Qubits can be created in different ways, each with advantages and disadvantages. Nearly 20 years ago, Microsoft decided to pursue a unique approach: developing topological qubits, which it believed would offer more stable qubits requiring less error correction, thereby unlocking speed, size and controllability advantages. The approach posed a steep learning curve, requiring uncharted scientific and engineering breakthroughs, but also the most promising path to creating scalable and controllable qubits capable of doing commercially valuable work.

The disadvantage is – or was – that until recently the exotic particles Microsoft sought to use, called Majoranas, had never been seen or made. They don’t exist in nature and can only be coaxed into existence with magnetic fields and superconductors. The difficulty of developing the right materials to create the exotic particles and their associated topological state of matter is why most quantum efforts have focused on other kinds of qubits…

…Majoranas hide quantum information, making it more robust, but also harder to measure. The Microsoft team’s new measurement approach is so precise it can detect the difference between one billion and one billion and one electrons in a superconducting wire – which tells the computer what state the qubit is in and forms the basis for quantum computation.

The measurements can be turned on and off with voltage pulses, like flicking a light switch, rather than finetuning dials for each individual qubit. This simpler measurement approach that enables digital control simplifies the quantum computing process and the physical requirements to build a scalable machine…

…Majorana 1, Microsoft’s quantum chip that contains both qubits as well as surrounding control electronics, can be held in the palm of one’s hand and fits neatly into a quantum computer that can be easily deployed inside Azure datacenters.

3. The most underreported and important story in AI right now is that pure scaling has failed to produce AGI – Gary Marcus

On the order of half a trillion dollars has been invested on a premise that I have long argued was unlikely to succeed: the idea (sometimes informally referred to as the scaling hypothesis) that we could get to “artificial general intelligence” simply by adding more and more data and GPUs…

…Virtually all of the generative AI industry has been built on this presumption; projects like the OpenAI/Oracle/Softbank joint venture Stargate, allegedly another half trillion dollars, are also largely based on this premise…

…But I always knew it couldn’t last forever. When I said as much, the field was absolutely furious at me…

…The first signs that the pure scaling of data and compute might in fact be hitting a wall came from industry leaks from people like famed investor Marc Andreessen, who said in early November 2024 that current models are “sort of hitting the same ceiling on capabilities.” Then, in December, Microsoft CEO Satya Nadella echoed many of my 2022 themes, saying at a Microsoft Ignite event, “in the last multiple weeks there is a lot of debate on have we hit the wall with scaling laws. Is it gonna continue? Again, the thing to remember at the end of the day these are not physical laws. There are just empirical observations that hold true just like Moore’s Law did for a long period of time and so therefore it’s actually good to have some skepticism some debate.”…

…Finally, and perhaps most significantly: Elon Musk said over that weekend that Grok 3, with 15x the compute of Grok 2, and immense energy (and construction and chop) bills, would be “the smartest AI on the earth.” Yet the world quickly saw that Grok 3 is still afflicted by the kind of unreliability that has hobbled earlier models. The famous ML expert Andrej Karpathy reported that Grok 3 occasionally stumbles on basics like math and spelling. In my own experiments, I quickly found a wide array of errors, such as hallucinations (e.g, it told me with certainty that there was a significant 5.6-sized earthquake on Feb. 10 in Billings, Montana, when no such thing had happened) and extremely poor visual comprehension (e.g. it could not properly label the basic parts of a bicycle).

Nadella, in his December speech, pointed to test-time compute, in which systems are allowed extra time for “reasoning” as the next big thing, and to some degree he is right; it is the next big thing, a new thing to try to scale, since merely scaling compute and data is no longer bringing the massive returns it once did. At least for a while, adding more and more computing time will help, at least on some kinds of problems…

…although DeepSeek lowered the costs of training these new systems, they are still expensive to operate, which is why companies like OpenAI are limiting their usage. When customers begin to realize that even with the greater expenses, errors still seep in, they are likely to be disappointed. One irate customer cc:d me yesterday on a several page demand for a refund, writing in part that “GPT-4o Pro [which includes access to test time compute] has consistently underperformed,” and enumerated problems such as “Severely degraded memory” and “Hallucinations and Unreliable Answers.”…

…the illustrious Stanford Natural Language Processing group reached a similar conclusion, reading between the lines of OpenAI’s recent announcement in the same way I did. In their words, Altman’s recent OpenAI roadmap was “the final admission that the 2023 strategy of OpenAI, Anthropic, etc. ‘“simply scaling up model size, data, compute, and dollars spent will get us to AGI/ASI’) is no longer working!”

In short, half a trillion dollars have been invested in a misguided premise; a great deal more funding seems to be headed in the same direction for now.

4. Is Microsoft’s Copilot push the biggest bait-and-switch in AI – Tien Tzuo

Over a year ago, Microsoft launched Copilot Pro, an AI assistant embedded in its Office suite, with a $20/month price. The uptake apparently was abysmal. By October, they admitted that the way they were selling Copilot was not working out.

So what did they do? They forced it on Microsoft users by including Copilot in Office, and hiking up subscription fees. Microsoft first made this change in Asia, then fully pulled the plug across the globe last month, impacting 84 million subscribers. To add insult to injury, Microsoft renamed the product to Microsoft 365 Copilot. You didn’t want to pay for Copilot? Well, now you are…

…Not only is Microsoft’s Copilot rollout deceptive, it’s also embarrassingly disastrous.

This goes to show that even tech giants, including a major backer of AI pioneer OpenAI, can suffer the hype and competitive pressure surrounding AI. And it’s a stark reminder that what businesses should really be focused on instead is value — communicating it clearly and delivering it tangibly to customers…

…Well, there’s a good contrast to Microsoft’s approach — from Adobe.

Adobe took a different approach with its AI rollout last fall, resisting the temptation to immediately monetize its new video generator, instead using it to boost adoption and engagement. By positioning AI as a value-add rather than a paid extra, Adobe was playing the long game, building a loyal user base that would be ripe for future upselling once they experienced AI’s benefits for themselves.

5. Broken Markets!? – The Brooklyn Investor

So, I keep hearing that markets are broken, or that the market is as expensive as ever. I know I keep saying this and I am sounding like a broken record, but I am not so sure…

…But if you look at individual stocks, markets are clearly differentiating between individual stocks. Look at Nvidia vs. Intel. If nobody was really evaluating them and the market was ignoring fundamentals, you would think both stocks would be performing similarly. But they are clearly not. People are clearly differentiating between winners and losers. It’s a separate question whether they are over-discounting their views. That’s a different discussion, and contrary to the view that passive investing is killing fundamental analysis.

Another example: JPM, the better bank, is trading at 2.4x book, versus C, which is a crappier one, selling at 0.8x book. You can’t complain that the market is broken just because you don’t agree with it. On the other hand, Buffett in the 50s loved the fact that institutional investors of the time completely ignored company analysis / valuation…

…Look at all the rich folks at the Berkshire Hathaway annual meeting. Look at BRK stock since 1970. How often did it look ‘overpriced’? What about the market? What if people sold out when they thought BRK was overpriced? Or the market? Would they be as rich as they are now? Probably not. Maybe there are some smart folks that got in and out of BRK over the years, but I would bet that the richest of them are the ones that just held it and did nothing.

I keep telling people this, but if you look at all the richest people in the world, a lot of them are people who held a single asset, and held it for decades. Look at Bill Gates. What if he was hip to value investing and knew more about stocks and values. He may have sold out of MSFT when it looked really overvalued. What about Buffett? What about Bezos?

A lot of the rich used to be real estate moguls, and I thought a lot of them were wealthy because real estate was not very liquid, so they had no choice but to hold on even in bad times. Stocks have what you may call the “curse of liquidity”. It’s so easy to say, holy sh*t, something bad is going to happen, and *click*, you can get out of the market. Back in the 90s, we used to fear a 1-800 crash; people will call their brokers’ automated trade execution lines, 1-800-Sell-Everything, and go “Get me out of the market!!! See everything NOW!!!”, and the market would not be able to open the next morning. Some of us truly feared that, and hedge funds talked about that sort of thing all the time. But you can’t do that with your house.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Amazon and Microsoft. Holdings are subject to change at any time.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 23 February 2025:

1. Weekend Thoughts: Demand Shocks and How Utilities Went From Sleepy to AI Darlings – Andrew Walker

That history has completely changed with AI over the past 18 months. Suddenly, the U.S. is experiencing real electricity demand growth for the first time in decades, and the rush for AI players to secure an enormous amount of electricity for their big AI datacenters has left the U.S. short electricity and scrambling to reopen old plants. The combination has created a bonanza for utilities; the whole sector screamed higher in 2024, and many of the utilities proved to be better AI plays than MSFT or even NVDA in 2024!…

…I mention it because I think that’s a really interesting set up to pattern to match / look for in the future. Find a staid, boring industry that most investors won’t look at that trades for a reasonable multiple (as utilities did pre-AI boom), and buy them just before a demand shock. You could argue if you do / time it right your downside is protected (it’s not like the stocks are going to go down when a demand shock doesn’t come; they’re not pricing one in!), and if you’re right you can make multiples of your money.

It worked for utilities in 2024, and it worked for all sorts of COVID beneficiaries in 2020/2021 (cleaning products, home gym equipment, etc.).

Now, there is one interesting wrinkle to this thesis: industries with long lead times benefit the most from a demand shock. Consider power: if you have a demand shock on the power side, then you eventually need to build more power plants to handle that shock. Building power plants takes a long time; I’d guess it takes 3-5 years from start to finish to build a baseload natural gas plant, and probably 20 years to build a nuke (if you can even get one built!). So a demand shock in power can create super normal pricing for a very long time. Most other demand shocks can be responded to much faster. A simple example: a demand shock in oil can be met relatively quickly; it only takes a few months to start spinning up new Permian wells!

2. How I avoided China’s biggest bond default – Willie Keng

In 2016, I told myself:

“Stay away from this Chinese company at ALL cost.”

It was a Thursday. I was in a room filled with high-level executives dressed in black suits – the company’s chief financial officer, finance managers, bankers, analysts and fund managers were there…

…Back then, even Chinese property developers from blue-chips to junk-rated companies all wanted to raise debt. China’s skyline was dominated by the grey, skeletal skyscrapers wrapped in scaffoldings. Tower cranes with long, mechanical arms swung on these buildings — there were noise of rapid urban growth.

And China’s property bond market was hot like an iron.

It was common to have 3-4 such company meetings in a single day. These were eye-opening — and very exciting times, as developers rushed to raise as much “cheap debt” as possible…

…In 2016, I saw the early warning signs of China’s bigger property developer, Evergrande…

…During that management [sic: meeting] held on Thursday, I concluded its leverage was too high…

…In 2021, Evergrande defaulted.

I’ve dug out some short-cut questions from my old notebooks:

1. How do you make money? (where are your sources of revenues from?)…
…11. How much debt are you refinancing over the next few years?
12. Who are your main bankers?
13. How do you hedge your interest rates? At what cost?
14. How much committed credit facilities you have with banks?
15. Why are you borrowing X debt, what are you using for?…
…23. How are you planning to refinance your short-term loans and who are the lenders? At what interest rate? Is it possible to get “secured” and “unsecured” funding?

3. The Magnificent Seven, MKL – The Brooklyn Investor

The question is, basically, what’s up with the Mag 7? How crazy is it? Is it Nifty-fifty all over again?…

…The Mag 7 is trading at 41x 2024 earnings, which is close to ttm earnings. and 33.5x 2025 expected earnings, and 28x 2026 expected earnings. I know, expected earnings is sort of rubbish. Nobody gets that right. But we gotta start somewhere, right?

By the way, if you exclude NVDA and TSLA, the above would be 32.6x, 29.6x and 25.8x P/Es, respectively. In this case, this is valid to do, because you can actually create a portfolio of high ROE, decent growth stocks at that valuation.

And then look at the ROE of each of these companies. And then look at the historic growth rates, 5 and 10 year of these companies…

… Let’s say the Mag 7 was a modern-day, techful version of a conglomerate like BRK. Its subsidiaries have grown tremendously in the past 5 and 10 years. Earnings will collectively grow 23% in 2025 and 19% in 2026 (willful suspension of disbelief may be key here), and look at the high ROE of each division (OK, I was too lazy to calculate a weighted average).

And this conglomerate is trading for 34x earnings! Or less than 30x if you don’t want NVDA and TSLA. Think about that for a second. How many ideas with those metrics can you find?…

… It’s easy to call AMZN a retailer, for example. YouTube is a big part of Google, and the rest of Google is advertising. So is Facebook. They compete with linear television, radio and other forms of entertainment in the past, and they make money from advertising, just like old media (including magazines too…). So we can call it media and advertising, not even “new” media. Just media. Tesla is an automaker. AAPL is more like the old Sony; consumer electronics. Basically every single consumer electronic product ever invented rolled into one product. They do media too; music, streaming etc. Gaming too. Only NVDA and MSFT sort of feel like the conventional ‘tech’.

My point was going to be, the Mag 7 domination may or may not be a problem, but it is quite diversified as a virtual conglomerate.

4. The Great EBITDA Illusion –  Stephen Clapham

KPMG examined 1800 transactions between 2013 and 2018 and found that both the number of adjustments to EBITDA increased, as did the value. The number increased from 5.8 to 7.9 per transaction and the value increased…

…Pro-forma adjustments have risen by 10% and were in over 60% of deals. These include cost-related adjustments, to reflect the future value of cost reductions, and revenue run-rate adjustments, including planned price increases, or the expected impact of a new product line. In my experience, cost savings tend to have a higher deliverability as they are more within management’s control; but it’s a rare business which can increase price without affecting volumes, while capacity increases are often tricky to model…

…S&P’s Leveraged Finance group have also looked at the topic of EBITDA adjustments, but through a different lens.

“Our six-year study on EBITDA addbacks appears to shows a positive correlation between the magnitude of addbacks at deal inception and the severity of management projection misses.”

They highlight that addbacks represent a median 30% of management adjusted EBITDA at deal inception. They consider management projections to be aggressive and U.S. speculative-grade corporate issuers generally “present earnings, debt, and leverage projections in their marketing materials at deal inception that they cannot realize”…

…This is of real significance, especially to lenders…

…Forecasts made in M&A deals turn out badly with leverage nearly twice the projection in year 1 and worse by end year 2. Most of the miss is down to over-estimating adjusted EBITDA. The median miss in year one was 34%, rising to 35% in year two…

…Leverage forecasts made in leveraged buyout transactions are much worse with actual leverage of 8.2x vs a 3.9x forecast…

…The S&P report concludes:

“Our six-year study continues to underscore that addbacks and company-adjusted EBITDA are a poor predictor of profitability. Our substantial dataset makes it clear that management teams and equity sponsors regularly miss their projections by a large margin, and that the magnitude of the misses is positively correlated with addbacks and firms that we rate lower. This suggests that inflated addbacks may help companies with higher financial risk get deals done.”

The data is clear and there is no reason to doubt it. What surprises me is that private equity and credit funds continue to engage in such practices and that allocators and credit investors appear relaxed. That may be justified given past performance, but as I have written here several times, I don’t believe that the historical record is anywhere near sustainable.

5. There Goes My Hero – Ben Carlson

My family took its first and only Disney trip in the summer of 1990.

We rode some rollercoasters. Went to one of the waterparks. Decently fun trip from what I can remember as a 4th grader.

The strange part was that my older brother Jon was lethargic the whole trip. I still remember a picture of him taking a nap on a bench in the middle of the day. Something was off.

I was nine, so I didn’t think anything of it. My mother, a registered nurse, knew something was wrong so when we got home, they took Jon to the doctor.

He was diagnosed with a rare form of leukemia just before heading into the 7th grade…

…Jon endured months of chemotherapy and radiation, after which the only solution was a bone marrow transplant. My parents weren’t a match. Luckily, my sister and I were both were.

I was the bone marrow donor. There was no guarantee it would work, but miraculously, it did. Jon’s cancer went into remission.

It was a terrible year for our family but Jon was a trooper. He never once complained. Even though he lived in the hospital on and off for months at a time and lost all of his hair he never felt sorry for himself…

…Last year, he was diagnosed with stage 4 pancreatic cancer. Last week he passed away just shy of his 46th birthday.

Jon was a tough son of a bitch and went out swinging.

The original plan was to manage the pancreatic cancer with chemo until Jon died but he didn’t want to just wither away. He called specialists all over the country, finally finding a doctor who would give him an experimental drug that allowed him to stop receiving chemo.

And it actually worked for a while. The cancer spread slowed. Eventually it would stop working but it gave us an extra six months or so…

…Grief is strange. Although you know millions and millions of other people have felt it, it still feels like the most personal of all emotions. I guess it is in some ways depending on the person and how they were lost.

At times, I’ve felt like there’s a black cloud hanging over my head. Other times, it’s as if there is a dull knife stuck in the back of my head. Sometimes it crashes into you all at once like a wave.

But it also forces you to reminisce about the good times. These past few months, it’s almost felt like my life has slowly flashed before my eyes through the lens of all the memories of my brother…

…After his bone marrow transplant, Jon was approached by the Make a Wish Foundation — anything he wanted, within reason.

He could have asked to meet his favorite celebrity or athlete. He could have asked for a room full of video games. He could have asked for a four-wheeler or a jetski or some other fun toy like that.

Instead, Jon requested a two-week all-expenses-paid vacation to Hawaii for our entire family. We got to swim with dolphins, fly in a helicopter, see some volcanoes, play on the beach, and more. They even sent a limo to our house to drive us to the airport.

I didn’t realize it at the time, but it was like Jon instinctively knew our family needed that after what we all went through. I still can’t believe a 12-year-old had the foresight to be so selfless, especially when no one would have blamed him for being as selfish as he wanted.

Jon was wise beyond his years and valued experiences with loved ones more than material possessions…

…As we worked through his financial situation it became abundantly clear he was more than prepared for something like this than I ever could have imagined. There was a large life insurance policy. He was holding far too much cash for a person his age.

Jon why do you have so much cash?

Ben, I knew something like this was going to happen. I’ve known it since I was 12 years old.

That bout with cancer changed his entire perception of risk. He’s been working and saving since age 19 because there was always a voice in the back of his head telling him something like this could happen again…

…He also left behind some life advice for his kids that helps explain the kind of guy he was:

Be happy with what you have, you don’t need as much as you think.

Never leave anyone behind.

Life is way better than a screen, go live it.

Our mantra is to go live like Jon. I’m so lucky to have him as part of my life while he was here.

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Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Alphabet (parent of Google), Amazon, Apple, Markel, Meta Platforms (parent of Facebook), Microsoft, and Tesla. Holdings are subject to change at any time.