What We’re Reading (Week Ending 04 December 2022) - 04 Dec 2022
Reading helps us learn about the world and it is a really important aspect of investing. The legendary Charlie Munger even goes 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 04 December 2022):
1. TIP499: Investing Through A Bear Market w/ David Gardner – Trey Lockerbie and David Gardner
[00:02:46] Trey Lockerbie: For one, we experienced the worst six months start in the stock market since 1970. There’s a new high interest rate environment and a lot of debate around inflation or deflation. So, I had to bring you back on because I’ve been speaking with so many people about this major macro-environment, we’re in and all the concerns around that.
[00:03:05] Trey Lockerbie: I’m hoping you can bring us back down to earth a little bit and provide potentially some reality setting or even just some hope that this market will turn around just like all previous markets.
[00:03:17] David Gardner: Well, thank you Trey. And I don’t feel any specific compulsion to need to be an optimist or to need to be the long-term guy, but the fact is I am a long-term guy, so I don’t have to affect it, and I am by nature optimistic, and It was true for my earliest youth. So, I’m glad to know that studies show that it’s a healthier approach to life and wonderful books like The Rational Optimist by Matt Ridley, which I totally recommend for anybody who’s not read that book, remind us that consistently throughout history, human history, we tend to think everything’s going down in our generation.
[00:03:49] David Gardner: We have apocalyptic thoughts that recur over and over again. We say things like, yeah, our kids won’t have it as good as we’ve had it, and we have been consistently wrong as a race. And I’m not just talking about the last five years or [00:04:00] 30 years. I’m talking about the last 2000 years recorded history and so it’s just worth remembering that.
[00:04:05] David Gardner: And I feel as if you and I, because I hope you generally agree with me, I sense a fellow entrepreneur and an optimist. It’s hard to be an entrepreneur and not be an optimist, I’ve found. But I do think that it still feels unusual for most people. We all come from different places in different angles.
[00:04:21] David Gardner: So, I’m not here to assert anything other than what I do and what I believe. And if anybody listens to this podcast, and a lot of people listen to your podcast, Trey, so I hope some people do. Maybe we’ll open some eyes or maybe we’ll start to remind some of the older hands of how things have been and will be, and that is good.
[00:04:39] David Gardner: That’s a good thing. The market goes lower left, upper right over any meaningful period of time…
…[00:09:14] Trey Lockerbie: Speaking of Netflix, you’ve owned that for almost, I think 18 years now. I mean, you work very early on it.
[00:09:20] David Gardner: Yes. Before, yeap.
[00:09:21] Trey Lockerbie: And the commentary as of late is that the thesis is busted, right? There are too many competitors, not enough content, cracking down on subscribers and raising prices, et cetera. Do you believe the thesis is busted?
[00:09:34] Trey Lockerbie: I imagine you would’ve sold it if that were the case, but is this just another quickster moment for Netflix, or what are you seeing and keeps you believing?
[00:09:42] David Gardner: Well, first of all, Netflix is down from a high of 700, closer to 300 today. So, this stock has been, well, more than halved in just a year. So, a lot of the bearishness and some of the broken thesis that you’re speaking to has in fact play.
[00:09:56] David Gardner: So, people like me who believe in Netflix and have owned Netflix for a long time [00:10:00] have a lot less allocation toward Netflix, assuming it’s underperforming. The rest of its our portfolio, which for me it has been. But of course, I remain a staunch believer in Netflix. It continues to have the largest market share.
[00:10:12] David Gardner: It’s really head and shoulders above any other streaming service. There are now so many streaming services that people are like, could I please get a cable, some new form of cable subscription that would bundle everything, so I don’t have to be subscribed to 17 different through my Roku services or whatever.
[00:10:27] David Gardner: So, in a world of ever proliferating streaming services where I think we arguably have more content than we’ll ever need in one lifetime, and we’re not even including YouTube and all that’s there right now, it’s amazing the battle for eyeballs. I mean, how many players are in there? But Netflix is head and shoulders.
[00:10:43] David Gardner: Above all, it’s the only pure play at scale globally. I don’t see anybody else there. I mean, you certainly see Disney with global possibilities, but they’re doing so many other things. And you see Amazon not as global, but they’re doing so many other things. I really like, first of all, I like all of them.
[00:11:01] David Gardner: Those are all great companies and great stocks, and I own all of them. So, I don’t think it’s a zero-sum game. It’s not a winner take all industry at all. And so, I, I would say that Netflix is certainly in a different place than it has been before. This is not an emergent company that people are doubting, which is how it was when I first bought it.
[00:11:20] David Gardner: And Blockbuster was on top of the world and the CEO, blockbuster was saying, well, Netflix looks interesting to us, but that’s a very small niche market. And from that point in time, the late 1990s, Netflix would come public year or two later, and all of a sudden, of course, the world changed. That was back in the DVD, subscription rental days, streaming later came along.
[00:11:40] David Gardner: Of course, Netflix was first there. Netflix is now, as moving to an ad supported model as well for those who want to pay a cheaper fair. And I think that’s smart. I also think it’s smart to, yeah, disentangle adult kids who may be surfing on moms and dads Netflix and have them pay to, I think it’s a great company and again, at a [00:12:00] market cap.
[00:12:00] David Gardner: Let’s see. I love Googling while we talk. It makes me sound so smart at a market cap of 122 billion today, Netflix, it’s about a hundred times where I first had it when it was more like a billion-dollar company. So, it’s not about to go up a hundred times in value ever again. Is this a stock that I believe will continue to be brilliantly managed, the leader in the space, and it’s a valuable space and probably in time if it starts to mature, they could start playing paying dividends, which is what some companies do in time.
[00:12:28] David Gardner: I’m happy to be invested and I will point out in closing on this one, Trey, that the stock is already well down. It’s not like often when stocks are way down, I find the sentiment starts saying That’s nothing. Watch what’s about to happen. And that thing doesn’t happen. Actually, the stocks flip back, and I was seeing Netflix being counted dead about a month ago, and then they came out with earnings.
[00:12:49] David Gardner: The stock went up from basically two 30 to 300. It’s on a roll, it’s up about 30% in the last month. So, it’s actually kind of like the market overall…
…[00:15:09] Trey Lockerbie: Now on that point right there. I mean, you’ve lived through a few different bear markets at this point. So has this one compared in any way to the previous ones, have those just sort of conditioned you a little bit better to withstand the volatility we’ve been seeing? Or is there anything different about this bear market in particular that you’ve noticed from previous ones?
[00:15:27] David Gardner: This feels very similar to me, just in the sense that the market is very far. And typically, my kinds of companies are farther down than that. And I had the pleasure of, we had our first Motley Fool member gathering face to face in a few years, for obvious reasons.
[00:15:43] David Gardner: That was about a month ago, and I had the pleasure or mispleasure, if you will, of standing in front of the whole room and saying, Whoever’s down, however much you’re down, I’m down more and it’s, I hope that’s refreshing for everybody to hear because it’s generally true. Percentage wise, I’m, I mean [00:16:00] I gave that I’m down 20% from a year ago, but really 2021 was a year of underperformance.
[00:16:05] David Gardner: A lot of the, especially some of the superstar stocks of the Covid rage gave away a lot of value in 2021. So, I am very well down. I’ve been about cut in half from where I was a couple of years ago, which sounds really bad since I’ve done this for a living and I’m a professional I guess, but it doesn’t sound that bad to me because it’s happened a few times before.
[00:16:24] David Gardner: And I think if I keep persisting as long as I hope to on planet Earth, it’s going to happen a few more times. And so, I don’t want to ever make it sound like it’s easy because it’s not. And our business gets hurt. Certainly, people don’t want to, they don’t want to open up their brokerage statements. They probably don’t want to open up a new subscription to a Motley Fool service.
[00:16:42] David Gardner: But again, once every 10 years or so, we’ve been around for 30 years now, and we’ve had three really bad markets and each one was for a different reason. You asked earlier, does this feel the same or different? It’s always going to be a different reason and a different environment. But ultimately when you’re seeing companies that you really like getting cut in half or more, that feels like the other times that’s happened and that’s happened before and it’s going to happen again.
[00:17:05] David Gardner: So, I think the reason I can say that with a smile my face is because I know what happens after that. I know that two years out of every three, the market rises, and the nine to 10% annualized returns include every horrific having of my portfolio and implosion of our markets and recessions are all baked into that number.
[00:17:25] David Gardner: And especially if you stay focused, not just on the. The market. I rarely invest in the market. I don’t really invest in funds or especially index funds, even though I, we promote them at the Motley Fool, and we greatly admire Vanguard and what Jack Bogle has done for this world. But we really think that you should just buy the great companies and not buy all rans and the mediocre and the bad companies.
[00:17:45] David Gardner: When you buy an index fund, you’re often buying everything. And I think we’ve made a career about pacing the market returns. It hasn’t felt that hard to do really. It’s just you are looking for. And I think part of it is we’re just playing the game differently because most people think of it as stocks that [00:18:00] they should trade.
[00:18:01] David Gardner: And we think of it as businesses that we want to own. And if you just ask yourself, what are the world shapers and world beaters, I don’t think it took any huge genius on the part of any of us to recognize Amazon, whether it was 30 years ago, 25 years ago, 20 years ago, 15 years ago, whenever you hopped on the Amazon train 10 years ago, five years ago.
[00:18:20] David Gardner: It has just been a wonderful stock. It’s not been great for the last year or so. But again, that’s one example among many. They’re in every industry. I’m always looking for the innovators and these companies outpace the averages and I try to let them flock in my portfolios or the scorecards that I picked at the fool over the years.
[00:18:37] David Gardner: So again, never wanting to sound blasé about this because I’m down more than most people are listening to me right now. But I also can tell you that I’ve seen this before and I’m not making it sound easy, but I’m telling you that things end well. They don’t end like this.
2. The Thing That’s Hard About Markets – Ben Carlson
When Russia invaded Ukraine in late-February, the price of oil was a little more than $90 a barrel. It basically went straight up from there to well over $120 a barrel in about a week and a half…
…I specifically recall listening to an Odd Lots podcast in March that laid out the case for $200/barrel oil in March when tensions were high:
Tracy: I mean, how high do you think it could go? And what level would be worrying to you in terms of demand destruction?
Pierre: Well, I think, like close to $200 a barrel — so much higher than today. I feel like there’s no demand destruction at $110 a barrel and we’ll have to go significantly higher before demand can go down by enough. But that’s also assuming there’s no government mandate and some kind of confinement, where let’s say two days a month, we are not doing anything. And we are in confinement for two days a month. I mean, there could be some solutions like that to bring demand down, but if there’s no government mandate, then I think that around $200 oil will be enough to bring demand to balance the market.
Joe: Could we see $200 oil this year?
Pierre: Yes, I think so. Yes.
It sure felt like it was only a matter of time. However, the opposite happened. Oil prices have crashed from those March highs…
…The thing that’s hard about markets is you could be completely right about the geopolitics and still be wrong about the price action. Or you could be completely right about the macro and still be wrong about the price action. For instance, let’s say I would have told you before the start of the year that oil prices would be flat through the end of November. How would you think energy stocks would do in that situation?
I guess energy stocks2 don’t need higher oil prices to outperform:..
…Energy is far and away the best-performing sector in the S&P 500 this year and there isn’t a close second place.
3. Barnett Helzberg Jr.: What I Learned Before I Sold to Warren Buffett – David Senra
Therefore, this confession. I have always solicited other people’s opinions and try to listen intently when they were espousing things.” This is such an important part, too. “Even when I was in pretty violent disagreement. Therefore, I claim only one original idea in my entire life, and with this book wish only to reveal myself as a plagiarist of wonderful ideas from a lot of great people through the years. Think of the world” — I love this part.
“Think of the world as your garden of marvelous people and ideas with unlimited picking rights for you. Enjoy the flowers.” And so it’s obviously an idea I very much agree with. Obviously, I’m dedicating my life’s work to uncovering the ideas from people in the past and hopefully push those ideas — and help push those ideas rather down the generations, but this idea of like we all use other people’s ideas it’s something almost every single person you and I study on this podcast also did.
I was telling a friend of mine one of my favorite quotes which comes from Poor Charlie’s Almanack, which is that he, obviously, Charlie Munger is an advocate for this idea. He calls himself a biography nut. He said he’s read hundreds and hundreds of biographies.
He says if he ever had a chance to teach, I think he said teach finance, maybe teach business. But I’m pretty sure he said, if I ever had the chance to teach finance, my entire curriculum would just be studying 100 different companies that did something right and did something incorrectly. But one of my favorite quotes from Munger is that, “Cicero is famous for saying that a man who doesn’t know what happened before he’s born goes through life like a child.”…
…Okay. So now we jump into all the different lessons that he learned before he sold to Warren Buffett. He starts out with one that he learned from his father. It says, “You should only concern yourself with things that you can control. When growing up, I was intrigued that my father only concerned himself with those business elements that were controllable.
He refused to acknowledge the Depression and did quite well during that period. He was unwilling to talk about recessions or 20-inch snowfalls. He only thought about and talked about those conditions within his control. Dad was a great believer in not sweating the small stuff.
He taught us to concern ourselves only with those things over which we have control. I thought he was unique in this until I realized this is one of the key common traits of highly successful people. Those folks are never victims. They take what comes and handle the situation. The rest is a waste of time.” Then we jump ahead to another lesson. Remember he started out the book saying, hey, I don’t even have any unique ideas.
I just listen when other smart people say things. And if it makes sense, I’m going to use that for my business. We see this idea. So the note I left myself is upgrade the herd annually, or what is the highest and best use of your time. I guess I’m going to read you this Charlie Munger quote that popped in my mind when I got to this section. Charlie says, “Intelligent people make decisions based on opportunity costs. So in other words, it’s your alternatives that matter. That’s how we make all of our decisions.” He’s saying that’s how him and Warren make all their decisions.
[00:30:04] Let’s jump into this lesson that Barnett learned from another founder. “When you’re operating a group of retail stores, there’s always the usual bell curve of weak to great performing stores. At one point, we were struggling with the store doing $800,000 in volume and through gargantuan efforts trying to get to $850,000 in annual sales.” So one store — they’re trying to increase it — it’s struggling, they’re trying to bump it up by another $50,000 a year.
“Much conventional practice dictates committing great effort to the weakest segment. When I discussed this with my friend, Steve Lieberman, he’s a hot dog magnate who ran hundreds of Carousel Snack Bars in shopping centers for many years. He said, ‘You make more money closing bad stores than by opening new ones.’ His philosophy made sense.
We decided we would rather spend time and effort on a $4.5 million store that could ultimately achieve $6 million in revenue than on lower volume store with less potential.” So instead of trying to bump up $50,000 and dedicating all these resources, let’s focus on something that’s already doing well and getting an extra $1.5 million is what he’s saying here.
“Did this mean we gave up immediately when things did not work? Absolutely not. If the store lacked great people, proper merchandising or other controllable variables,” there’s that word control again, “by all means, we fixed it. However, our attitude became to upgrade the herd annually, closing the weakest stores each year.” And then he goes into his reasoning behind this.
“Each activity you undertake exacts the price of not being able to pursue alternative activities. This is sometimes called opportunity cost. What is the actual cost of sending a highly talented person to create an average performance out of a dry well rather than sending him or her to a gusher that can be turned into a super-gusher?” Then he extends this idea by talking about something he learned from Warren Buffett.
“Perhaps one of the key reasons Warren Buffett has been the world’s most successful investor, he does not buy turnaround opportunities,” something that Buffett spends a lot of time discussing over many years in his shareholder letters. He doesn’t believe turnarounds turn around.
“He does not buy turnaround opportunities, only successful companies. Focus is your lever to success. Do not underestimate the incredible amount of mental discipline it takes to focus yourself and your teammates. Wonderful alternatives and seductive opportunities abound and temptations to go in multiple directions are unlimited.”
[00:32:13] That’s — he’s writing these words in 2003. Now imagine how much temptation and distraction we’re exposed to on a daily basis almost 20 years later, way more than the world in 2003. This is the last thing I’m going to read you from this section, but this sings to my soul. “Commit yourself to be the best, define what that means and focus on the head of that pin like no one in your industry.” I got to read that again.
“Commit yourself to be the best, define what that means and focus on the head of that pin like no one in your industry.” And he’s got another great idea. I’ll probably reference Estée Lauder several times, Episode 217. If you haven’t listened to it yet, I highly recommend you do. So she was maybe the best practitioner of Paul Graham’s idea that you should do things that don’t scale.
What Barnett says here is that just providing super service is actually a friend to the entrepreneur. It’s something that you can do that giant companies can’t. And so he talks about going to a locally owned grocery store.
And he says, “I went to the grocery store to get a few items. Unloading the groceries, I found that the home phone numbers of the owners, Mike and Libby, were listed right on the sack with the invitation to call if I was not happy with the store. It was clear that the owners took responsibility for good service.” What I also liked about the book is at the end of every chapter, he’s got all these quotes that he loved, usually from other founders or other interesting people throughout history. You know I’m a sucker for maxims.
This one actually read biography on Thomas Watson. It’s called The Maverick and His Machine, Thomas Watson, Sr., and the making of IBM. I did that a long time ago. I think it’s Episode 87. But he put this at the end of one of the chapters that I really loved, a quote from Thomas Watson, who said, “To be successful, have your heart in your business, and your business in your heart.”…
…His father had this idea of — he calls it the two-supplier principle. And then this is the first time he mentions this or the first time I mentioned it to you, but it’s mentioned a lot in the book that his father and everybody in the company is like, don’t burn a bridge. This is repeated — do not burn a bridge is repeated over and over again in his book. And so this is the first introduction I heard about the two-supplier principle. “One bitterly cold January in the mid-1960s, I went to our bank,” one of the banks, actually, “to the First National Bank of Kansas City to make our routine loan.
We needed to cover the checks that we sent out the day before to our suppliers for the immense amount of merchandise we had bought for the Christmas season the month prior. We had a long-standing relationship with First National Bank going back 30 years. We had gotten the usual letter reassuring us that a $500,000 line of credit was available to us when we needed it.
We hardly noticed the last paragraph of the letter, which would rescind the bank’s obligation if our creditworthiness changed. To our shock and surprise, the bank refused to loan us the money. One particular director of the bank felt that we were not creditworthy.” So they just sent on a bunch of checks, there’s not enough money in their bank account to cover those checks. They’re in dire need. And so the bank is not budging even though they’ve been — had a relationship with them for 30 years. We’ll come back to them in one second. So what do they do?
[00:36:01] “We immediately drove over to Security National Bank, where the family that owned the bank had served my dad for untold years.” Now that guy who had work with his dad, now his son is in the bank. So this guy named Morris Briedenthal Jr. “had only one question for us. How much do you want?” So back to Barnett. “We came to the precipice and we were saved by the two-supplier principle. When at death’s door, you may be saved by a relationship. We were. Did we continue to” — now this is what he means about maybe other people would be mad. Hey, we were a customer of yours for 30 years. How dare you change our relationship overnight? You could have put us out of business. We’re done here.
Barnett did not do that. He says, “Did we continue to do business with both banks? Yes, absolutely. Never burn a bridge was our mantra, and we still wanted two suppliers.” And then he has parting advice in this chapter, get your second sources now when you do not need them. And then he quotes this great African proverb on this chapter that’s about the need to test your new ideas. And it says, “Only a fool tests the depth of the water with both feet.”
And so in the 1970s and before, it was a long-established idea in their industry that you should handle the financing and the extending of the credit to your customers yourself. And then one of Barnett’s executive is like, no, I’m pretty sure we could outsource this and then just focus on the one thing that we’re actually really good at, which is selling diamonds.
So he says, “The stakes were high in terms of the loss of interest income and fees from the outside providers of credit. So Marty chose one of our best store managers to test his idea that jewelry stores could make more money if they focused on selling diamonds.” So this is his hypothesis, right?
“We’re actually going to make more money if we focus on selling diamonds and left the credit business and interest income to banks and other lenders who were experts in such things.” And so one principle at play here is like, listen, if you’re going to test something you think is important — it’s going to be really important to the future of your business, put one of your best people on it.
[00:38:04] That’s what they did. They picked a great store. They didn’t do a test in a c***** store, and then couldn’t figure out. Did it work because it’s a c**** store? Did it work because it was a c**** idea? It’s like well, no, this guy is really good. He’s really smart. He’s one of our best. Let him test it and it wind up being a success and then this is what they did next.
“After our test of outsourcing customer credit, we can now say to the other stores it had proved to be successful. As each of our stores began to implement the new system, our total focus on buying and selling diamonds.” So remember, he talked about the importance of focus. He said in a previous chapter that focus is your lever to success, and the implementation of that is obviously a competitive advantage because I’m not sure humans in general can focus on many things and certainly not in today’s day and age. So that is also going to be a main theme over and over again. That focus is a lever to success. We just see this here.
It says, “As each of our stores began to implement the new system, our total focus on buying and selling diamonds, and not being in the banking business brought incalculable dividends.” And so reducing that lesson down back to that proverb, which is fantastic, only a fool tests the depth of the water with both feet. And so then Barnett talks about this maxim that he learned from his dad, that business is people.
And actually, if you just treat people better and don’t create inhospitable environments, you wouldn’t imagine that companies do this to their customers, but you probably see it every day in your day-to-day lives. That’s actually an advantage and an edge that you can have…
…You’ve probably seen this sign everywhere if you go into a shop or a store rather. It says, hey, don’t bring your food and drink. No food and drink. He’s like, well, I’m just going to do the opposite. Bring it all in, let’s go.
“One of the best things we did was to invite shoppers to bring their food into the store with them. Ice cream cones? Hotdogs with mustard? No problem. The standard store sign in a mall says, ‘no food or drink.’ Ours said, ‘Your food and drink are welcome here.’ We were trying to say we are here on your terms and we are different.”
4. The AI War and How to Win It – Alexandr Wang
The AI War is at the core of the future of our world. Will authoritarianism prevail over democracy? Do we want to find out?
The Ukraine war is already demonstrating that the tech stack for war has changed. Technologies including drones, AI-based targeting and imagery intelligence, and Javelin missiles have allowed for a shocking defense of Ukraine against Russia, despite their nearly $300B in defense spending over the past 5 years.
The future is clear—AI-powered targeting and autonomous drones will define warfare. AI applied to satellite imagery and other sensor data has already enabled targeting and tracking of Russian troops and generals. Our legacy military platforms, while still important, will be disrupted by cheaper autonomous drone fleets. Aircraft carriers are giant targets in the sea compared to autonomous, adaptive drone swarms.
We are in the midst of a renaissance of AI in the commercial sector. In the past few years, breakthroughs have enabled AI systems to generate imagery, text, code, and even reason. The pace of AI research is following its own Moore’s law—every 2 years, the number of AI papers published per month doubles. As venture capitalists ogle over the potential of Generative AI to change knowledge work, we are not addressing the obvious application of AI towards military power, and the very clear risks that America will be outpaced…
…All that will matter in a future conflict is our technology—AI will devise, execute, and update our combat strategy. Our technology is our strategy.
There is precedent for technological disruption of warfare. I grew up in Los Alamos, New Mexico, the birthplace of the atomic bomb. The development of nuclear weapons in 1942 ushered in a new era of the nature of war and deterrence, and is one of the largest contributors to the Pax Americana, the unprecedented relative peace in the world since the end of World War II.
The continuation of Pax Americana rests upon our ability to navigate and maintain the lead in the AI race, which in turn will ensure the military and economic leadership of America. The facts today on our relative standing against China are not good, and need to be confronted head-on. We will not win by standing still…
…China’s military arm, the People’s Liberation Army (PLA), spent between $1.6B and $2.7B on AI against an overall defense budget of $178B in 20202, whereas the US Department of Defense (DoD) spent only between $800M and $1.3B on AI against an overall DoD budget of $693B over the same period.
China is spending between 1% and 1.5% of their military budget on AI while the United States is spending between 0.1% and 0.2%. Adjusted for the total military budget, China is spending 10x more than the United States…
…China is showing that in tactical AI capabilities, such as computer vision for greater sensing and awareness, they are handily ahead. And while America currently leads on more strategic AI systems, such as LLMs which will underpin future command-and-control systems, China is at most 1 year behind.
The current top 5 algorithms on the global leaderboard for image recognition on COCO (the established benchmark) all come from Chinese companies and universities…
…We need to match China’s ability to plan on long, 10-year time horizons. It’s imperative that we begin charting a long-term path towards dominance in defense AI.
Given any existing military capability, it will be more lethal, effective, and efficient if enabled with AI and autonomy. As the technology improves, it is not an exaggeration to say that AI will enable 10x gains. Some simple examples:
- A fully autonomous drone swarm will be nearly impossible to subdue or disarm, and doggedly pursue any objective it is given. As we’ve seen in Ukraine, an effective drone can neutralize nearly any adversary—and a dominant AI agent will be able to outmaneuver even an AI-enabled foe.
- AI-enabled intelligence and automated target recognition will limit the fog of war. We will be able to immediately identify targets and neutralize them faster than any adversarial human could react. As Sun Tzu once said, “Know your enemy, know yourself, and in one hundred battles, you will never be in peril.”
By the end of the decade, any military capability that is not AI-enabled will be rendered nearly useless against an AI-enabled adversary, just as Russia’s tanks have shown to be inept. It would be silly to continue investing in non-AI capabilities when they will clearly be outdone. We can be sure China is thinking along the same lines, as their public statements match a 10-year time horizon for AI-enabled warfare.
5. RWH017: Fidelity Legend Joel Tillinghast – William Green and Joel Tillinghast
[00:19:29] William Green: And [00:19:30] in your book, which is excellent, which I have behind me, which is Big Money, Think Small. Sorry, I keep getting the name wrong, but it’s a really interesting book. I was rereading it yesterday. a very helpful book. So, thank you for writing it. In your book, you described this really formative experience of trying to figure out whether you could predict economic statistics and then making an early bet using futures on margin, on interest rates back, and I think about 1983.
[00:19:59] William Green: Can you talk about what happened and what you learned from that? Because it sounds like that negative experience also had a pretty big impact on the type of investor you’d become.
[00:20:09] Joel Tillinghast: For part of it, I was still, that time I was still in business school and had lots of student loans and a tight budget, even though I was working and so didn’t have that money to trade and brought my job at Drexel was as a research economist.
[00:20:30] Joel Tillinghast: Part of that is putting together hedging packages for customers that wanted to hedge their interest rate. But a lot of the volume of a brokerage business was within active traders. A lot of them traded around the economic statistics. So, if employment was looking robust as it may have recently, then they’ll say bearish for bonds.
[00:20:57] Joel Tillinghast: And my job was to [00:21:00] forecast, will producer prices be up 0.2% for 0.4%? And there are some tricks because some of the statistics use bits and pieces of other statistics that have already been released. So, if you have the industrial production number, you know something about the GDP. If you leading indicators were then got much more focus, but some of the components had already been released, like S&P prices.
[00:21:32] Joel Tillinghast: Well, you knew that. Jobless claims and other things so you could come up with a better estimate and it wasn’t then completely in the market. The problem, lots of people around me who were making much more money than I was and thought, wow can’t I was moderately good at it, forecasting PPI and the other statistics and, well, can I trade this to make money?
[00:22:01] Joel Tillinghast: And I did this, it started with one contract I. And a futures contract on TBIs, I think was a million dollars, but you could buy one by putting up margin of a thousand dollars or $1,500. The problem was you had to put up the variance margin, so if the price went down by $3,000, you had to cough up [00:22:30] the loss or lose your deposit and get sold out of the position and probably get your account closed if you were not a Drexel employee, maybe even if you are a Drexel employee.
[00:22:43] Joel Tillinghast: It went really well for about four months. I’d say it started in January as I was heading to my last year of business school and it, I managed to make about $40,000, which given my income and lack of net worth at the time was truly fantastic. Was thinking I could pay off my student loans, which were, I guess, less burdensome than it seems like some students today are stuck with.
[00:23:17] Joel Tillinghast: But then in early May, as I was heading towards graduation, the market also changed. And my lucky streak, I guess there’s a temptation to pyramid and keep adding to the positions. If you’re winning, you want to press your bets and say, that’s not a bad thing to do. But it comes with a lot of caveats. If you’re doing it with borrowed money, it’s a terrible idea.
[00:23:45] Joel Tillinghast: But if it’s all mad money, you’d say push a winning bet. As far as you. And you then found,
[00:23:54] William Green: if I remember rightly that interest rates suddenly started to tumble when you were betting that they were with Surge.
[00:23:59] Joel Tillinghast: [00:24:00] Yes. And so, where I’m going is with 40,000 in equity, you had something like 25 million worth of notional exposure, which was really disproportionate to anything else for me as a counter party.
[00:24:21] William Green: You were like the long-term capital of yeah. You were the long-term capital of college students.
[00:24:26] Joel Tillinghast: Yeah. If it was all equity and rates were going in that direction, in your direction, then say that’s great. But it was all borrowed. And so, over a couple of weeks I basically lost back all of the 40 grand and in an agreed thing, I don’t know if they shut down my account or just said, you know, I think it would be a good idea to take a holiday from this for a while.
[00:24:53] Joel Tillinghast: And it was hurting so much from losing back the $40,000 because it felt so smart. Like, wow, this is great. Like, let’s annualize that. That’s 10,000 a month that it was making.
[00:25:07] William Green: What do you think it did viscerally, like, Joel, like that experience of actually going through that pain and fear of loss, how did that searing emotional experience actually shape your view of investing and whether you, how in some ways, conservative and defensive you realized you needed to be in order to survive as a successful.[00:25:30] [00:25:30] Joel Tillinghast: Don’t do anything with borrowed money unless the thing you’re borrowing against is giving you an income stream that can cover it. You never ever want to be a seller. Why would stocks sell for less than they’re worth? There’s a whole bunch of behavioral reasons. One of them is people get forced out of their holdings and it happens every financial crisis that something gets sold at an absurd price because they had to.
[00:26:02] Joel Tillinghast: And so, no margin for me, I think it’s not so much conservatism, but a recognition, the interest rates. Lots of people know about this GDP. Lots of people know about. Do I have a really good edge? Probably not as much as I might with the smallish public listed company where management and know what they’re thinking.
[00:26:31] William Green: So is part of the moral, just the, for almost all of us, unless we happen to be George Soros or Stanley Druckenmiller or someone like that, we should just avoid trying to make money off these macro predictions. Like it’s just too difficult that even for someone like you who was spending your whole life at the time trying to make macro predictions, it just was too difficult in a sense.
[00:26:55] Joel Tillinghast: I think if you spend all your time trying to do it like George Soros, that [00:27:00] you can do that, but it’s beyond my skillset and I think it’s very difficult. Generally, right now we have an impending profit recess. And analysts come to me saying, are you interested in buying the home builders? Are you interested in buying me the old Facebook?
[00:27:21] Joel Tillinghast: And figuring out what’s discounted, even in a fairly specific case, is really difficult. Figuring out what the moving pieces are for a whole economy and for aggregated statistics it’s a really tough game and you’ve got to be amazing, like George Soros is to be able to do that well.
[00:27:43] William Green: So in a way, when you are looking at companies, when you have a team of something like 130 stock analysts at Fidelity, right, who come to you and they pitch stuff like this, the housing stocks and energy stocks, and are you really not thinking that much about macro stuff at all? You’re just, you are. You are just looking to see whether they’re fundamental things, like whether they have a good moat, whether they have enduring competitive advanced tiers, whether it’s cheap, whether the cash flow is predictable, what are you focused on?
[00:28:11] Joel Tillinghast: If the house is burning down, you can’t focus on the architectural qualities, but I do not ignore current events, but usually it isn’t conclusive about what I’m. I do have macro-opinions, but mostly I want analysts to help [00:28:30] me imagine different scenarios. What if British interest rates go up another hundred basis points and mortgage rates follow?
[00:28:40] Joel Tillinghast: What will that do to affordability of homes in the UK? What will that do for consumer spending and how catastrophic is that for the companies that we’re talking about? And it might be not at all, or it could be a very big impact. And sometimes companies can have more competitive position and be better placed to withstand those kinds of shocks and sometimes they can have worse positions since that.
[00:29:12] Joel Tillinghast: That’s what I want from analysts. Since the fund has a bunch of British stocks and has. To home builders. It’s a relevant question to, to are they cheap because they’re selling for less than their stated net asset value? Or will this be too devastating for housing to, for them to make a decent profit in the next year or two?
[00:29:36] William Green: So, you can’t really ignore the macro environment, but it seems like given your very low turnover in the fund, you’re also trying to find companies that are going to be okay over the long run, sort of in, they’re going to muddle through difficult macro environments. Is that a fair description?
[00:29:53] Joel Tillinghast: Yeah, and I’m looking for what I think Will is looking for, which is adaptive [00:30:00] companies that have a strong hand to start with.
[00:30:04] Joel Tillinghast: Nobody knows the future, but some companies are more adaptive than others. Next, a UK retailer. The fund holds used to be mostly high street stores with a catalog business, and they could have completely lost their position during the internet age, but in fact to repurposed catalog into internet selling, and now it’s the majority of profits and is growing well.
[00:30:35] Joel Tillinghast: So, there’s a good adaptation. I think you always want an adaptive management team, and I think that’s part of the secret sauce of why we’ll spend so much time on meeting management and understanding their thinking.
6. Liberty RPF — On Creation and Curation (EP.134) – Jim O’Shaughnessy and Liberty RPF
Liberty RPF:
Oh, thank you. I’m just happy that the ideas are there because as you say, I feel like for so much of humanities history, execution and having the idea were so tied together. The person needed to have both. And now with many of our so powerful tools, it’s kind of becoming a bit disconnected and you can have the ideas and then have them executed by software, by a machine, or somewhere else, or OSV may be the execution machine for these people that have the ideas but don’t have the capital or the tools or access or whatever to execute them. So bringing those things together is amazing. About the ideas I had, I think I remember two out of the three, so you may have to jog my memory for the last one.
But the first one I was thinking about is there’s been a big scandal basically about fraudulent research about Alzheimer’s recently. And it made me think about how there’s so much, thousands and thousands and probably hundreds of thousands of studies in every field that will never have enough people to go back and go through them and go with a fine tooth comb trying to figure out if there’s maybe some somewhere if there’s some good faith errors or some outright fraud.
But with machine learning, I think we could data mine these things and try to find all kinds of stuff that we could never have found before. And we may figure out that some branches of sciences have been going in the wrong direction for a long time because they’re basing their current research on some bad foundation somewhere, that the house is built in a foundation on sand or something and they’re wasting so much time and money and effort and that has real consequences. If the Alzheimer’s research spend years and billions of dollars going after emulate plagues, plagues or something because of some fraud, that’s terrible. People suffering from this disease should have research going in the right direction for them to find a cure.
So yeah, I feel I, that’s one of the top uses I can think of for this kind of AI. Not that it’s an easy things and maybe it’s just probabilistic. You flag some stuff as potentially to need human regulate, let’s say. The other one I wish I could see, and that’s probably a bit farther down the line, when you can model things in silico better, I’ve computational models and in biology, we’re already starting to do that. Google has kind of cracked a lot of computational protein folding stuff and eventually we can have more complex models where you can take past experiments and rerun them in silico to try to see if they replicate.
If you had to do it kind of in the real world, it would take forever and cost billions of dollars and you could maybe share, pick a few studies that you could try to replicate and a few needles in the haystacks. If you can do it at scale in AI models basically, that’s another area where you could figure out if there’s a replication crisis in that part of it. But also you can rerun the same studies with slight variations to try to maybe optimize them if you had a good result on some study.
But the people doing the study have only this much funding and they can only try, I don’t know, 500 variations on that compound or on those animals or whatever. Well, maybe if you rerun it much more cheaply and quickly, you can run 500,000 variations and find a much better, one more optimized where you can improve procedure for drugs or whatever. And I don’t know if that’s the third one I mentioned to you, but another one that I’d love to see is there’s, science is, it’s very about prestige and you want citations, you want advanced career. So everybody wants to work on the most prestigious and the sexiest stuff. There’s a line I love by a scientist who said, it seems tragic to me that all of the top scientists and engineers want to work in the fields where they make the least difference. Where if they were hit by a truck five minutes later, someone else would come up with the same thing.
I wish we’d have more effort going into less prestigious areas, areas where there’s less competition from the top minds where you can make more discoveries, but also where you can find a bunch of new hypothesis, right? Where you can find a bunch of stuff that doesn’t work, and having this information about what doesn’t work is still useful. Well, the next person working the field, if they have huge database of a million failed experiments, they can much better target what they want to do in the future or maybe just avoid doing something expensive and it takes a long time to solve resources, avoid wasting resources is just as good as having more resources. So I wish AI could help us with those kind of less sexy parts of science.
That’s another one where in some fields it’s going to be easier ’cause they’re more based on information and data and can be done in software. Some other fields going to be harder. But I feel like over time, because of our good friend Claude Shannon, basically anything in the world can be represented by information and you can act on it in that information realm. It may not be easy, but at the rate at which things are improving, it’s definitely going to be possible at some point…
…Liberty RPF:
Yeah, that’s the thing. I think it’s probably easy to hear that I’m very optimistic and I’m generally pretty optimistic about that stuff. So because of that, I have to remind myself of the dangers and the bad side. And I try to take that very seriously. I’ve been interested in AI for maybe, I don’t know, 17 years or something like that. And a lot of people, it’s funny because a bunch of what I used to read about back then is kind of happening now. Oh, we can do this and that in 25 years, 50 years. And now it’s all more quickly than we expected.
The things I’m worried about are not the small problems that always come with new powerful technology. The way I try to separate it in my mind is there’s a bunch of recoverable problems where you make a mistake and you figure it out and you fix it. And that’s always been like that with every technology. And people complain about this problem. It’s like, okay, but the problem we used to have that was fixed by this was bigger. There’s no good old days for humanity. It used to be pretty terrible in many ways. We take it for granted now. But that’s on one side.
What I try to keep in mind, and I try to keep it in the conversation as much as I can, is there’s also the potential for nonrecoverable problems with AI. Because if you think about it, all of humanity’s most powerful tools and technologies and weapons, they’re all basically IP. A nuclear bomb, that’s an idea and then we made it. But that’s the idea that created it. AI, as it becomes better and better and you get AGI at some point probably, or even without AGI, you can make all kinds of very, very scary stuff with it too.
Bio weapons that are synthetic biology that our immune system cannot recognize and you leave it dormant in someone for years before activating it. And so everybody has it by the time, I can imagine terrifying scenarios with that. So I want to make sure that the people making the AI make humanity better with all kinds of cool tools. And then we fix the recoverable problems that as we get them. And that’s fine. But we always keep our eye on the big nonrecoverable things because as Buffet would say, you can have this lines of great [inaudible] and then you multiply once by zero and even if you’re cured cancer and 99 great things, if you have one big nonrecoverable thing that it all didn’t matter. So that’s the thing, I always want to make sure that the people working on this, and I’m sure they do because they’re much smarter than I am, but that’s a little part that every time I’m super optimistic, I’m like, yeah, but I hope we really don’t screw it up too much.
7. David Deutsch’s multiverse carries us beyond the realms of imagination – Tim Radford
On page 44 of the Penguin edition, David Deutsch describes the interference pattern from a single photon passing through a single slit and infers from this experiment “the existence of a seething, prodigiously complicated, hidden world of shadow photons” and goes on from that to further infer “a huge number of parallel universes, each similar in composition to the tangible one, and each obeying the same laws of physics, but differing in that the particles are in different positions in each universe.”
Welcome to the multiverse. This isn’t the same multiverse as the other one you’ve been told about. In that one, brand-new universes spontaneously bud off from each other, so many bubbles in the champagne fountain of eternity. Some of these bubble universes are snuffed out swiftly and some last ever such a long time, and some might even be hospitable to intelligent life. But we could never know anything about any of the others, only this one.
Deutsch’s multiverse is different. It is co-incident with, somehow contiguous with, and weakly interacting with, this one. It is a composite, a layer cake, a palimpsest of universes very similar but not quite identical to each other.
The number of these shadow universes is enormous (on page 44 Deutsch reasons from the one-photon experiment that there must be a trillion of them, and later in the book airily invites a quantum computational calculation involving 10500 universes, which is another number I cannot imagine.
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have a vested interest in Alphabet (parent of Google), Amazon, Meta Platforns, and Netflix. Holdings are subject to change at any time.
