What We’re Reading (Week Ending 25 August 2024) - 25 Aug 2024
Reading helps us learn about the world and it is a really important aspect of investing. The late Charlie Munger even went so far as to say that “I don’t think you can get to be a really good investor over a broad range without doing a massive amount of reading.” We (the co-founders of Compounder Fund) read widely across a range of topics, including investing, business, technology, and the world in general. We want to regularly share the best articles we’ve come across recently. Here they are (for the week ending 25 August 2024):
1. Eric Schmidt talk on AI at Stanford (Transcript here) – Eric Schmidt and Erik Brynjolfsson
Schmidt: One more technical question. Why is NVIDIA worth $2 trillion and the other companies are struggling? Technical answer.
Attendee: I mean, I think it just boils down to like most of the code needs to run with CUDA optimizations that currently only NVIDIA GPU supports. Other companies can make whatever they want to, but unless they have the 10 years of software there, you don’t have the machine learning optimization.
Schmidt: I like to think of CUDA as the C-programming language for GPUs. That’s the way I like to think of it. It was founded in 2008. I always thought it was a terrible language and yet it’s become dominant.
There’s another insight. There’s a set of open source libraries which are highly optimized to CUDA and not anything else and everybody who builds all these stacks- this is completely missed in any of the discussions. It’s technically called VLLM and a whole bunch of libraries like that. Highly optimized CUDA, very hard to replicate that if you’re a competitor. So what does all this mean?
In the next year, you’re going to see very large context windows, agents, and text-to-action. When they are delivered at scale, it’s going to have an impact on the world at a scale that no one understands yet. Much bigger than the horrific impact we’ve had by social media in my view. So here’s why.
In a context window, you can basically use that as short-term memory and I was shocked that context windows get this long. The technical reasons have to do with the fact that it’s hard to serve, hard to calculate, and so forth. The interesting thing about short-term memory is when you feed, you’re asking a question – read 20 books, you give it the text of the books as the query and you say, “Tell me what they say.” It forgets the middle, which is exactly how human brains work too. That’s where we are.
With respect to agents, there are people who are now building essentially LLM agents and the way they do it is they read something like chemistry, they discover the principles of chemistry, and then they test it, and then they add that back into their understanding. That’s extremely powerful.
And then the third thing, as I mentioned is text to action. So I’ll give you an example. The government is in the process of trying to ban TikTok. We’ll see if that actually happens. If TikTok is banned, here’s what I propose each and every one of you do. Say to your LLM the following: “Make me a copy of TikTok, steal all the users, steal all the music, put my preferences in it, produce this program in the next 30 seconds, release it and in one hour, if it’s not viral, do something different along the same lines.” That’s the command. Boom, boom, boom, boom. You understand how powerful that is?
If you can go from arbitrary language to arbitrary digital command, which is essentially what Python in this scenario is, imagine that each and every human on the planet has their own programmer that actually does what they want, as opposed to the programmers that work for me who don’t do what I ask, right? The programmers here know what I’m talking about. So imagine a non-arrogant programmer that actually does what you want, and you don’t have to pay all that money to, and there’s infinite supply of these programs.
Interviewer : And this is all within the next year or two?
Schmidt: Very soon. Those three things – and I’m quite convinced it’s the union of those three things – that will happen in the next wave. So you asked about what else is going to happen. Every six months I oscillate. It’s an even-odd oscillation.
So at the moment, the gap between the frontier models, which they’re now only three, I’ll reveal who they are, and everybody else, appears to me to be getting larger. Six months ago, I was convinced that the gap was getting smaller. So I invested lots of money in the little companies. Now I’m not so sure. And I’m talking to the big companies and the big companies are telling me that they need $10 billion, $20 billion, $50 billion, $100 billion.
Interviewer: Stargate is $100 billion, right?
Schmidt: That’s very, very hard. I talked to Sam Altman – he’s a close friend. He believes that it’s going to take about $300 billion, maybe more. I pointed out to him that I’d done the calculation on the amount of energy required. And I then, in the spirit of full disclosure, went to the White House on Friday and told them that we need to become best friends with Canada, because Canada has really nice people, helped invent AI, and lots of hydropower. Because we as a country do not have enough power to do this. The alternative is to have the Arabs fund it. And I like the Arabs personally. I spent lots of time there, right? But they’re not going to adhere to our national security rules. Whereas Canada and the U.S. are part of a triumvirate where we all agree…
…Attendee: In terms of national security or geopolitical interests, how do you think AI is going to play a role in competition with China as well?
Schmidt: So I was the chairman of an AI commission that sort of looked at this very carefully and you can read it. It’s about 752 pages and I’ll just summarize it by saying we’re ahead, we need to stay ahead, and we need lots of money to do so. Our customers were the Senate and the House. And out of that came the Chips Act and a lot of other stuff like that. A rough scenario is that if you assume the frontier models drive forward and a few of the open source models, it’s likely that a very small number of companies can play this game – countries, excuse me.
What are those countries or who are they? Countries with a lot of money and a lot of talent, strong educational systems, and a willingness to win. The US is one of them. China is another one. How many others are there?
Interviewer: Are there any others?
Schmidt: I don’t know. Maybe. But certainly in your lifetimes, the battle between the US and China for knowledge supremacy is going to be the big fight. So the US government banned essentially the NVIDIA chips, although they weren’t allowed to say, that was what they were doing, but they actually did that to China. We have a roughly 10-year chip advantage in terms of sub-DUV, that is sub-five nanometer chips.
So an example would be today we’re a couple of years ahead of China. My guess is we’ll get a few more years ahead of China, and the Chinese are whopping mad about this. It’s like hugely upset about it. So that’s a big deal. That was a decision made by the Trump administration and driven by the Biden administration…
…Interviewer: I want to switch to a little bit of a philosophical question. So there was an article that you and Henry Kissinger and Dan Huttenlocher wrote last year about the nature of knowledge and how it’s evolving. I had a discussion the other night about this as well. So for most of history, humans sort of had a mystical understanding of the universe and then there’s the scientific revolution and the enlightenment. And in your article, you argue that now these models are becoming so complicated and difficult to understand that we don’t really know what’s going on in them.
I’ll take a quote from Richard Feynman. He says, “What I cannot create, I do not understand.” I saw this quote the other day. But now people are creating things that they can create, but they don’t really understand what’s inside of them. Is the nature of knowledge changing in a way? Are we going to have to start just taking the word for these models without them being able to explain it to us?
Schmidt: The analogy I would offer is to teenagers. If you have a teenager, you know they’re human, but you can’t quite figure out what they’re thinking. But somehow we’ve managed in society to adapt to the presence of teenagers and they eventually grow out of it.
I’m serious. So it’s probably the case that we’re going to have knowledge systems that we cannot fully characterize, but we understand their boundaries. We understand the limits of what they can do. And that’s probably the best outcome we can get.
Interviewer: Do you think we’ll understand the limits?
Schmidt: We’ll get pretty good at it. The consensus of my group that meets every week is that eventually the way you’ll do this so-called adversarial AI is that there will actually be companies that you will hire and pay money to to break your AI system.
Interviewer: Like Red Team.
Schmidt: So instead of Human Red Teams, which is what they do today, you’ll have whole companies and a whole industry of AI systems whose jobs are to break the existing AI systems and find their vulnerabilities, especially the knowledge that they have that we can’t figure out. That makes sense to me…
…Attendee: In general, you seem super positive about the potential for AI’s problems. I’m curious, what do you think is going to drive that? Is it just more compute? Is it more data? Is it fundamental architectural shifts? Do you agree?
Schmidt: The amounts of money being thrown around are mind-boggling. And I’ve chosen – I essentially invest in everything because I can’t figure out who’s going to win. And the amounts of money that are following me are so large, I think some of it is because the early money has been made and the big money people who don’t know what they’re doing have to have an AI component. And everything is now an AI investment, so they can’t tell the difference. I define AI as learning systems, systems that actually learn. So I think that’s one of them.
The second is that there are very sophisticated new algorithms that are sort of post-transformers. My friend, my collaborator, for a long time has invented a new non-transformer architecture. There’s a group that I’m funding in Paris that has claims to have done the same thing. There’s enormous invention there, a lot of things at Stanford.
And the final thing is that there is a belief in the market that the invention of intelligence has infinite return. So let’s say you put $50 billion of capital into a company, you have to make an awful lot of money from intelligence to pay that back. So it’s probably the case that we’ll go through some huge investment bubble, and then it’ll sort itself out. That’s always been true in the past, and it’s likely to be true here…
…Attendee: You mentioned in your paper on natural security that you have China and the U.S [indecipherable].. The next cluster down are all other U.S. allies or teed up nicely through the U.S. allies. I’m curious what your take is on those 10 and the middle that aren’t formally allies. How likely are they to get on board with securing our security guideline and what would hold them back from wanting to get on board?
Schmidt: The most interesting country is India because the top AI people come from India to the U.S. and we should let India keep some of its top talent. Not all of them, but some of them. And they don’t have the kind of training facilities and programs that we so richly have here. To me, India is the big swing state in that regard. China’s lost. It’s not going to come back. They’re not going to change the regime as much as people wish them to do. Japan and Korea are clearly in our camp. Taiwan is a fantastic country whose software is terrible, so that’s not going to work – amazing hardware. And in the rest of the world, there are not a lot of other good choices that are big. Europe is screwed up because of Brussels. It’s not a new fact. I spent 10 years fighting them. And I worked really hard to get them to fix the EU Act and they still have all the restrictions that make it very difficult to do our kind of research in Europe. My French friends have spent all their time battling Brussels and Macron, who’s a personal friend, is fighting hard for this. And so France, I think, has a chance. I don’t see Germany coming and the rest is not big enough.
2. Activism at Scale in Japan – Daniel Rasmussen, Lionel Smoler Schatz, and Yuto Kida
Last year, the Tokyo Stock Exchange issued a directive asking all companies with price-to-book ratios below 1x to issue a plan to get to 1x book. The reforms aimed to help Japan shake off its reputation as a “value trap.” At the time of the announcement (March 2023), around 50% of companies in the Prime Section and 60% of firms in the Standard Section had a PBR <1x, reflecting a shocking degree of pessimism and inattention by investors. Over the past year, companies issued plans and posted them to the TSE’s website.
We did a systematic review (methodology described below) of every plan issued by companies on the TSE’s Prime and Standard Section (3,247 firms) to assess the impact of these reforms. And the answer, we believe, is that dramatic change is afoot, with widespread dividend and buyback increases…
…As of the end of June, based on the TSE’s monthly list of disclosed companies, 50.9% of firms have disclosed plans and 9.8% are considering…
…The majority of companies issuing plans are increasing dividends, almost a quarter are repurchasing shares, and over 10% are selling cross-share and strategic holdings…
…Firms that have made an effort to lay out a specific and tangible action plan to reach 1x book have experienced a significant rise in their stock prices since the TSE announcement, more than double compared to companies that haven’t disclosed or are still considering doing so. We can see that the market has generally reacted positively to the companies’ disclosed plans and that the TSE’s “name and shame” tactic is working so far. It seems like whether the Japanese stock market continues to build on its momentum depends on the willingness of companies to be transparent about and responsive to the TSE’s request to reach 1x book.
3. The CEO Who Made a Fortune While His Hospital Chain Collapsed – Jonathan Weil
Steward Health Care System was in such dire straits before its bankruptcy that its hospital administrators scrounged each week to find cash and supplies to keep their facilities running.
While it was losing hundreds of millions of dollars a year, Steward paid at least $250 million to its chief executive officer, Dr. Ralph de la Torre, and to his other companies during the four years he was the hospital chain’s majority owner.
Steward filed for bankruptcy in May, becoming one of the biggest hospital failures in decades. Conditions at some of its hospitals have grown dire. In one Florida hospital, a pest-control company last year found 3,000 bats.
This month in Phoenix, where temperatures topped 100 degrees, the air conditioning failed at a Steward hospital, forcing patients to be transferred elsewhere, according to a court filing. Also, the kitchen was closed because of health-code violations. The state last week ordered the hospital to cease operations…
…The former cardiac surgeon owns a 190-foot, $40 million yacht called Amaral and a 90-foot, $15 million sportfishing boat called Jaruco, according to the Senate committee. He owns an 11,108-square-foot Dallas mansion, valued at $7.2 million by the county. Other residents of his exclusive Preston Hollow neighborhood include George W. Bush and Mark Cuban.
He paid at least $7.2 million in 2022 for a 500-acre ranch 45 miles south in Waxahachie, according to the property deed. Two private jets that the same Senate committee valued at $95 million were owned by a Steward affiliate that is majority-owned by de la Torre…
…Once a renowned surgeon, de la Torre became CEO of Steward’s predecessor in 2008 and took over majority ownership of Steward from its private-equity owner in 2020…
…The $250 million in payments from Steward to de la Torre and to his businesses are based on public disclosures from Steward or companies it dealt with. The total likely understates the full tally because Steward’s bankruptcy-court disclosures in most cases have covered only the 12 months before it filed for chapter 11. Some of the $250 million was paid to de la Torre directly. Other payments were to companies that did business with Steward where he had big ownership stakes.
De la Torre got his majority stake in Steward in 2020 when the company’s private-equity owner, Cerberus Capital Management, transferred its 90% stake to a physician group he led in exchange for a $350 million promissory note…
…Steward also made payments to two of de la Torre’s other companies. It was paying a management-consulting firm majority-owned by him at a rate of $30 million a year, a bankruptcy-court filing shows.
Steward said the firm, Management Health Services, employed 16 people, including Steward executives. Steward said they “provide executive oversight and overall strategic directive.” Steward effectively paid its CEO’s firm, which employed Steward executives, for executive-management services for Steward.
De la Torre’s spokeswoman said the only payments he received from MHS were for salary. She called MHS a payroll vendor. But it also owned hard assets including the two private jets, according to RZJets, which tracks aircraft history. One, a Bombardier Global 6000, was valued at $62 million, according to the Senate panel, while the other, a Dassault Falcon 2000LX, was worth $33 million. The pilots were on MHS’s payroll, according to people familiar with the matter. Both jets were sold this year.
Steward also paid $37 million to a company called CREF from May 2023 to May 2024, according to a bankruptcy-court filing. CREF is 40%-owned by de la Torre, according to people familiar with the matter, and provides real-estate and facility-management services. The other 60% is owned by CREF’s founder and CEO, Robert Gendron, who was a Steward executive vice president from 2018 to 2022 in charge of real estate and facilities.
4. The Lessons of a Lousy Business – Kingswell
The very thing that honed Buffett’s ability to spot wonderful companies and identify undervalued investment opportunities was his hard-won experience dealing with the dregs of the business world.
At the Berkshire Hathaway AGM in 2017, he admitted that it was his firsthand experiences with “lousy” businesses that made him the investor he is today.
“If you want to be a good evaluator of businesses,” said Buffett, “you really ought to figure out a way — without too much personal damage — to run a lousy business for a while. You’ll learn a whole lot more about business by actually struggling with a terrible business for a couple of years than you learn by getting into a very good one where the business itself is so good that you can’t mess it up.”…
…It’s not just one of the most interesting chapters of Buffett’s long career, but his time at Dempster Mill Manufacturing Co. imprinted several lessons on the young investor that he would apply to Berkshire Hathaway a few years later…
…What appeared to be an outrageously low price is exactly what led Buffett to Dempster Mill Manufacturing Co., a windmill and farm implement maker based in Beatrice, Nebraska.
Buffett started buying shares for his partnership at $18 a piece — which was just 25% of the company’s book value. Eventually, he snapped up enough of them — at an overall cost basis of $28 per share — to take majority control of Dempster.
His prize? A front row seat to the dysfunction that caused Dempster to trade at such a low valuation in the first place. The quantitative metrics might have screamed BUY!, but the sharks were circling right beneath the surface. Sales had flatlined, unsold inventory piled up, and cash was in dangerously short supply.
Buffett tried to enact positive change without upsetting the apple cart — helpfully making suggestions as a member of the board — but that went nowhere. Dempster management paid lip service to the new owner’s ideas, but basically ignored them…
…Staring disaster in the face, Buffett turned to Charlie Munger for help. And, thankfully, Charlie knew just the man for the job. “A good friend, whose inclination is not toward enthusiastic descriptions, highly recommended Harry Bottle for our type of program,” Buffett wrote to his partners in 1962…
…Buffett and Bottle connected in Los Angeles in April of 1962 and, less than a week later, Bottle was in place in Beatrice. With a $50,000 signing bonus and Dempster stock options for his trouble. From Buffett’s perspective, no money has ever been better spent…
…Harry Bottle played hard ball. His was not a Kumbaya-style of management. Some people don’t like that. But drastic times call for drastic measures.
(In a Christmas letter to employees, Bottle admitted that some of the things done to right the ship “were distasteful to all of us”.)…
…In only one year, Bottle completely transformed Dempster into a profitable operation.
- 1961: $166,000 cash vs. $2.3 million liabilities
- 1962: $1 million cash and stock vs. $250,000 liabilities
In 1963, Buffett decided to cash in and sell Dempster at a hefty profit. But, as Alice Schroeder details in The Snowball, it was not exactly a smooth process. When Buffett posted notice that the company would be sold, “Beatrice went berserk at the thought of another new owner that might impose layoffs or a plant closing on its biggest and virtually only employer.”
“The people of Beatrice pulled out the pitchforks,” wrote Schroeder. “Buffett was shocked. He had saved a dying company. Didn’t they understand that? Without him, Dempster would have gone under. He had not expected the ferocity, the personal vitriol. He had no idea that they would hate him.”
It all ended happily enough — with the town raising enough money to purchase Dempster and Buffett’s partnership nearly tripling its money on an investment that had one foot in the grave just a year earlier.
On paper, it looked like a walk-off home run for Buffett. But pulling Dempster out of the fire left scars on the young investor that, while painful, nevertheless prepared him to paint his masterpiece with Berkshire Hathaway.
5. A Number From Today and A Story About Tomorrow – Morgan Housel
Every forecast takes a number from today and multiplies it by a story about tomorrow.
Investment valuations, economic outlooks, political forecasts – they all follow that formula. Something we know multiplied by a story we like.
The trick when forecasting is realizing that’s what you’re doing…
… A fact multiplied by a story always equals something less than a fact. So almost all predictions have less than a 100% chance of coming true. That’s not a bold statement, but if you embrace it it always pushes you towards room for error and the ability to endure surprise…
…If you’re trying to figure out where something is going next, you have to understand more than its technical possibilities. You have to understand the stories everyone tells themselves about those possibilities, because it’s such a big part of the forecasting equation.
When interest rates are low, the story side of the equation becomes more powerful. When short-term results aren’t competing for attention with interest rates, most of a company’s valuation comes from what it might be able to achieve in the future. That, of course, is just a story. And people can come up with some wild stories.
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have no vested interest in any companies mentioned. Holdings are subject to change at any time.
