A Few Things: The Future Of War, How To Do Great Work, Big Shorts & Big Longs, Great Idea Funnel, Special Sits in Privates, Dating an AI, Epic EM Bull Market, The AI Dilemma and Reid Hoffman on AI...

July 13 2023

I am sharing this weekly email with you because I count you in the group of people I learn from and enjoy being around.

You can check out last week’s edition here: What's Next For The Economy & Markets, What To Expect in Russia, CIA Director on The Future, Ken Griffin on Hedge Funds, News & Charts You Might Have Missed...

Lots of walking and commutes into work, so this one is packed with podcasts.

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Quotes I Am Thinking About:

“The key is not to predict the future but to prepare for it.”

- Pericles

"A writer’s brain is like a magician’s hat. If you’re going to get anything out of it, you have to put something in first."

- Louis L'Amour

"Opportunity is missed by most people because it is dressed in overalls and looks like work.”

- Thomas Edison

"Education is a progressive discovery of our own ignorance.”

- Will Durant

"Millions long for immortality who don't know what to do with themselves on a rainy Sunday afternoon.”

- Susan Ertz

"Curiosity is the beginning of knowledge. Action is the beginning of change."

"Highly focused people do not leave their options open. They select their priorities and are comfortable ignoring the rest. If you commit to nothing, you’ll be distracted by everything."

- James Clear

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A. A Few Things Worth Checking Out:

1. Last week’s Economist had a great report on The Future of War, discussing how a new era of high-tech war has begun.

Key bits (emphasis mine):

Ukraine’s killing fields hold three big lessons. The first is that the battlefield is becoming transparent. Forget binoculars or maps; think of all-seeing sensors on satellites and fleets of drones. Cheap and ubiquitous, they yield data for processing by ever-improving algorithms that can pick out needles from haystacks: the mobile signal of a Russian general, say, or the outline of a camouflaged tank. This information can then be relayed by satellites to the lowliest soldier at the front, or used to aim artillery and rockets with unprecedented precision and range.

Even in the age of artificial intelligence, the second lesson is that war may still involve an immense physical mass of hundreds of thousands of humans, and millions of machines and munitions. Casualties in Ukraine have been severe: the ability to see targets and hit them precisely sends the body-count soaring. To adapt, troops have shifted mountains of mud to dig trenches worthy of Verdun or Passchendaele. The consumption of munitions and equipment is staggering: Russia has fired 10m shells in a year. Ukraine loses 10,000 drones per month. It is asking its allies for old-school cluster munitions to help its counter-offensive.

The third lesson—one that also applied for much of the 20th century—is that the boundary of a big war is wide and indistinct. The West’s conflicts in Afghanistan and Iraq were fought by small professional armies and imposed a light burden on civilians at home (but often lots of misery on local people). In Ukraine civilians have been sucked into the war as victims—over 9,000 have died—but also participants: a provincial grandmother can help guide artillery fire through a smartphone app. And beyond the old defence-industrial complex, a new cohort of private firms has proved crucial. Ukraine’s battlefield software is hosted on big tech’s cloud servers abroad; Finnish firms provide targeting data and American ones satellite comms. A network of allies, with different levels of commitment, has helped supply Ukraine and enforce sanctions and an embargo on Russian trade.

2. A few friends shared Paul Graham’s latest: How To Do Great Work. He’s an amazing thinker and writer, and if you are looking to improve your craft, this is a good read.

It’s a very long piece, and these are some of the key bits:

The first step is to decide what to work on. The work you choose needs to have three qualities: it has to be something you have a natural aptitude for, that you have a deep interest in, and that offers scope to do great work.

Once you've found something you're excessively interested in, the next step is to learn enough about it to get you to one of the frontiers of knowledge. Knowledge expands fractally, and from a distance its edges look smooth, but once you learn enough to get close to one, they turn out to be full of gaps. The next step is to notice them. This takes some skill, because your brain wants to ignore such gaps in order to make a simpler model of the world. Many discoveries have come from asking questions about things that everyone else took for granted. 

Four steps: choose a field, learn enough to get to the frontier, notice gaps, explore promising ones. This is how practically everyone who's done great work has done it, from painters to physicists.

The three most powerful motives are curiosity, delight, and the desire to do something impressive. Sometimes they converge, and that combination is the most powerful of all.

What should you do if you're young and ambitious but don't know what to work on? What you should not do is drift along passively, assuming the problem will solve itself. You need to take action.But there is no systematic procedure you can follow. When you read biographies of people who've done great work, it's remarkable how much luck is involved. They discover what to work on as a result of a chance meeting, or by reading a book they happen to pick up. So you need to make yourself a big target for luck, and the way to do that is to be curious. Try lots of things, meet lots of people, read lots of books, ask lots of questions. 

When in doubt, optimize for interestingness. Fields change as you learn more about them. What mathematicians do, for example, is very different from what you do in high school math classes. So you need to give different types of work a chance to show you what they're like. But a field should become increasingly interesting as you learn more about it. If it doesn't, it's probably not for you.

Great work usually entails spending what would seem to most people an unreasonable amount of time on a problem. You can't think of this time as a cost, or it will seem too high. You have to find the work sufficiently engaging as it's happening. There may be some jobs where you have to work diligently for years at things you hate before you get to the good part, but this is not how great work happens. Great work happens by focusing consistently on something you're genuinely interested in. When you pause to take stock, you're surprised how far you've come.

If you do work that compounds, you'll get exponential growth. Most people who do this do it unconsciously, but it's worths topping to think about. Learning, for example, is an instance of this phenomenon: the more you learn about something, the easier it is to learn more. Growing an audience is another: the more fans you have, the more new fans they'll bring you.

One of the most valuable kinds of knowledge you get from experience is to know what you don't have to worry about. The young know all the things that could matter, but not their relative importance. So they worry equally about everything, when they should worry much more about a few things and hardly at all about the rest. But what you don't know is only half the problem within experience. The other half is what you do know that ain't so.

You arrive at adulthood with your head full of nonsense — bad habits you've acquired and false things you've been taught — and you won't be able to do great work till you clear away at least the nonsense in the way of whatever type of work you want to do.

Much of the nonsense left in your head is left there by schools. We're so used to schools that we unconsciously treat going to school as identical with learning, but in fact schools have all sorts of strange qualities that warp our ideas about learning and thinking. For example, schools induce passivity. Since you were a small child, there was an authority at the front of the class telling all of you what you had to learn and then measuring whether you did.

The best teachers don't want to be your bosses. They'd prefer it if you pushed ahead, using them as a source of advice, rather than being pulled by them through the material. Schools also give you a misleading impression of what work is like. In school they tell you what the problems are, and they're almost always soluble using no more than you've been taught so far.

In real life you have to figure out what the problems are, and you often don't know if they're soluble at all. But perhaps the worst thing schools do to you is train you to win by hacking the test. You can't do great work by doing that. You can't trick God. So stop looking for that kind of shortcut. The way to beat the system is to focus on problems and solutions that others have overlooked, not to skimp on the work itself.

3. Ted Seides at Capital Allocators spoke to Porter Collins and Vincent Daniel, the founders of Seawolf Capital (a family office managed as an old school hedge fund).

Previously, they were two of the three members of Steve Eisman’s team at Frontpoint Capital and found themselves in print and on the silver screen as protagonists in Michael Lewis’ The Big Short. The podcast had some great stories about their time at Frontpoint and what happened after.

Key bits from the conversation:

• In the three full years since they started managing their own capital, the pair is up an extraordinary 9x, coming off a 169% return in 2022.

• They spent some at Citadel, so had the inside scoop of life on the inside: 99% of the time they are long short term momentum and gross up when vol is low. By definition they cannot be contrarian

• Big themes on the upside: brazil, uranium; downside: banks and sov risk.

4. Filtering The Idea Funnel by Neckar is a great read.

Optimizing your funnel sounds simple but requires intellectual honesty. “People naturally allocate more and more effort to the part of the funnel that is most comfortable to them,” he explained. “The brain hides the rest from our consciousness.”

Another useful practice would be to make your filters explicit.

Write them down and track how you apply them. Filters need to be revisited, refined, and revised over time. Remember that Buffett’s early filters were heavily tilted towards valuation rather than quality of the company or management. It’s the perfect exercise for a hot and slow summer. If you get it right, the future payoff can be immense.

5. Invest Like the Best Podcast: Jeremy Giffon - Special Situations in Private Markets.

Jeremy was the first employee and general partner at private equity firm/holding company Tiny, which buys and holds Internet and technology-focused businesses. Prior to that, he was on the founding team of MediaCore, which was acquired by Workday.

The focus of the discussion is about esoteric opportunities that exist in private markets, how misaligned incentives and coordination problems create special situations for people like Jeremy to invest in.

Key bits: (00:05:21) - Key characteristics he’d look for in a perfect investment, (00:16:17) - Examples of a special situations transaction in private markets, (00:18:55) - Building up a sourcing mechanism, (00:25:42) - Refining the underwriting process, (00:33:32) - Why people do things they don’t like, (00:47:05) - Tactics for negotiating with and sourcing CEOs, (00:55:58) - Being hard to kill, (01:20:21) - The one call that everyone needs to make, (01:35:35) - Views he holds that would make people scratch their heads

Lots of wisdom here.

6. The Future of Relationships - Are people going to start dating AI?

Online dating is so mainstream that you’re an outlier if you haven’t met your partner on an app — so why not AI? There was once a stigma attached to online dating: Less than a decade ago, many couples who had met online would make up stories for how they met rather than admit that they had done so via an app.

With rapid advances in AI technology over the past few years, these norms may well evolve to include sex, love and friendships with AI-equipped machines.

7. Best macro thing I heard this week was James Aitken (Founder of Aitken Advisors) with Ted Seides at Capital Allocators, in a discussion titled: Opportunities and Risks from Monetary Policy.

James works with one hundred of the most influential pools of capital in the world.

This conversation covers the precarious set-up from fiscal and monetary policy, then turns to attractive opportunities arising from it in the U.S. industrial complex, Japan, and the UK, and risks on the horizon from volatility targeting, unprofitable businesses, illiquid exposures, and the absence of governments willing to embrace pain.

Worth listening to twice.

8. Structural Underpinning of an EM Bull Market. Louis Gave of Gavekal wrote a piece discussing his thesis and was on Top Traders Unplugged to discussed why EM will see an EPIC bull market.

He outlines his case for why the consensus is wrong to expect a US recession and why he sees accommodative US fiscal policy as a key driver of the economy in the next 1-2 years.

They discuss the upside and downside risks to inflation and how weather patterns may be an underappreciated risk to inflation in the next 1-2 years. One of Louis’ key calls is an upbeat outlook on emerging markets, particularly in the middle East and Asia based on:

• De-dollarization:

• De-sinification

• The upcoming commodity bull market

They wrap up with an assessment of AI and the economic implications in the medium term.

9. The Rise of Saudi Arabia & the Persian Gulf Is Reshaping the World. Thanks Ivan G.

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B. The Technology Section:

1. The A.I. Dilemma. Tristan Harris and Aza Raskin are deeply concerned about the deployment of tools like ChatGPT.

They did a great presentation at the Aspen Institute’s annual event.

As co-founders of the Center for Human Technology, they are on a mission to close the gap between what the world hears publicly about A.I. and what the people closest to the risks and harms inside A.I. labs are telling them.

2. Reid Hoffman discussed the Possibilities of AI in Conversation with Tyler Cowen.

Broad ranging conversation which asks every AI question you could think of from: the optimal liability regime for LLMs, whether there’ll be autonomous money-making bots, which agency should regulate AI, how AI will affect the media ecosystem and the communication of ideas, what percentage of the American population will eschew it, how gaming will evolve, whether AI’s future will be open-source or proprietary, the binding constraint preventing the next big step in AI, which philosopher has risen in importance thanks to AI, what he’d ask a dolphin, what LLMs have taught him about friendship, how higher education will change, and more.

They also discuss Sam Altman’s overlooked skill, the biggest cultural problem in America, the most underrated tech scene, and what he’ll do next.

3. All You Need To Know About Semiconductors. Great overview of the industry.

4. Chip wars: How ‘chiplets’ are emerging as a core part of China’s tech strategy.

5. A lot more to do than NVIDIA…..

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