A Few Things: Ferguson on The USD, What's Happening in PE, Druck on Markets, Where are Middle Eastern $'s Going?, Power and Prediction, What's Next in Gen AI, Charts and News You Might Have Missed....
April 27 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: Attia on Outlive, Built to Move, 5 Trends, Summers on US, Make Something Wonderful, News You Might Have Missed, Post GPT World, Risks of AI....
Quotes I am Thinking About:
“I would rather have a mind opened by wonder than one closed by belief.”
- Gerry Spence
“Wise men speak because they have something to say, fools because they have to say something.”
"Change is never painful, only the resistance to change is painful."
“The secret of getting ahead is getting started.”
- Mark Twain
“The main thing is to keep the main thing the main thing.”
- Steven Covey
“A good plan violently executed now is better than a perfect plan executed at some indefinite time in the future.”
- George S. Patton Jr.
“Our lives are fashioned by our choices. First we make our choices. Then our choices make us.”
- Anne Frank
A. A Few Things Worth Checking Out:
1. Niall Ferguson had a piece on Bloomberg about the almighty US dollar and this narrative I hear a lot around de-dollarisation. He also summarised it in a twitter thread.
2. What’s going in Private Equity?
Mario Giannini and John Toomey lead two of the largest private equity fund investors in the world. Mario is the CEO of Hamilton Lane, which manages over $100 billion and supervises another $700 billion in non-discretionary assets, and John is half of the Executive Management Committee of HarbourVest, which also manages in excess of $100 billion in the space.
They did an overview of private equity markets with Ted on Capital Allocators. They discussed the health and valuation of underlying portfolio companies, new deals, secondary markets, dry powder, fund raising, portfolio construction, winners and losers, new sources of capital, private credit, co-investments, ESG, China, and geopolitical risks.
3. Stanley Druckenmiller spoke at the Norges Bank (Norwegian SWF) conference this week about his market views. He comes in 2hr5mins in.
4. Everyone is headed to the Middle East to raise money. This Economist piece looks into the details. Welcome to a new era of petrodollar power: What are the hundreds of billions of oil riches being spent on?
We estimate that in 2022-23 the current-account surplus of the Gulf’s petrostates may hit two-thirds of a trillion dollars. Our investigation suggests that less of the money is returning to the West. Instead, a growing share is being used to advance political aims at home and gain influence abroad, making global finance a murkier system.
Most of the bounty is instead being accrued by the four biggest members of the Gulf Co-operation Council (GCC): Kuwait, Qatar, the uae and Saudi Arabia. Our research finds they have been used in three novel ways by a variety of actors that include national governments, central banks and sovereign-wealth funds. These are to pay back external debt, lend to friends and acquire foreign assets.
Start with debt. Between 2014 and 2016 a petroleum glut fuelled by America’s shale boom caused the oil price to fall from $120 a barrel to $30, the steepest decline in modern history. In 2020, as covid-19 lockdowns depressed demand, prices cratered again, to $18 in April. To withstand the earnings shock, Gulf states liquidated some foreign assets and their central banks sold part of their foreign-currency stash. But this was not enough, so they also borrowed a lot of hard currency on Western capital markets.
Gulf states are also lending a hand to friends in need—the second use of the new oil money. In early 2022 the central bank of Egypt, a big food importer squeezed by high grain prices, received $13bn in deposits from Qatar, Saudi Arabia and the uae. In recent years, Saudi Arabia has also allowed Pakistan to defer payment for billions of dollars in oil purchases. This money is more conditional than in the past. Eager to see at least some of its cash return, Saudi Arabia recently demanded Egypt and Pakistan implement economic reforms before giving them more help. Some of the Gulf support also comes in exchange for stakes in state-owned assets these embattled countries are putting up for sale.
Yet for all their geopolitical significance, such loans account for only a fraction of the oil jackpot. That leaves the main escape channel: foreign investments.
In past booms the central banks of the world’s two largest petrostates—Russia and Saudi Arabia—did much of the recycling, meaning that the assets they purchased were labelled as reserves. All these countries wanted was stable yields and few surprises. Most often they parked the cash at Western banks or bought super-safe government bonds—so many that Gulf appetite, along with China’s, is credited for helping to create the loose monetary conditions that fed the 2000s sub-prime bubble.
All of which points to an important plank in the sovereign-wealth funds’ new approach: advancing Gulf states’ strategic goals. One such objective has been to project soft power. PIF may have lost a big chunk of the $45bn it invested in 2016 in the Vision Fund, a gigantic vehicle for tech investments that has been rocked by bad bets and market shocks. But the mammoth cheque did a great deal to raise Saudi Arabia’s profile among global investors, says one who recently opened an office in Riyadh. Funds are also setting aside capital to shower on neighbours, boosting their regional sway. PIF has set up subsidiaries in Bahrain, Egypt, Iraq, Jordan, Oman and Sudan to deploy $24bn in the Arab countries.
These shifts are blurring the line between ruling families’ personal wealth and that of the sovereign. The fastest-growing funds tend to be run by royals, or members of their clan. In March Sheikh Tahnoon bin Zayed, the UAE’s national-security adviser, was made chairman of adia (he already chairs adq; his brother will soon run Mubadala). More money is going on pet projects, often through special-purpose vehicles. New “family offices”, which manage the private wealth of the mega-minted, have joined the deal-fest. Armed with war chests “in the ten digits”, they routinely buy $500m-1bn stakes in single firms, says a local banker. It is becoming ever harder to see where oil money goes.
All this is bad news for the West. That it gets less of the bounty is the smaller problem. A murkier financial system makes it easier for funds to move around unnoticed. Financial sleuths reckon that a share of Russia’s oil earnings is deposited into banks in the Gulf, where it is mixed with dollars owned by others so as to become untraceable. More geopolitically astute Petrostates also create the chance for wavering countries, like Turkey, to get financing outside of Western-led institutions, giving them an extra degree of freedom. Two decades ago, when sovereign-wealth funds became fashionable, many in the West worried they might be used to pursue political agendas. At the time, such fears were overblown. They now seem more reasonable—but few are paying attention.
5. I might not agree with Pippa Malmgren, but she always opens my mind to new ways of looking at things. She was on the Macrovoices podcast discussing the escalating geopolitical situation, including her views that the Pentagon played a role in orchestrating the Silicon Valley Bank bailout to protect defence technology interests, and that China rather than Russia has been the principal aggressor from the beginning of the Ukraine conflict.
Always eye opening and thoughtful.
6. You and your kids will like this Space Elevator and lots of other great content here.
7. Thoughtful discussion by Jonathan Haidt - Why does Modern America create fragile children? Thank you Manoj.
B. Power and Prediction:
Artificial intelligence (AI) is changing the world as we know it. How can we understand the economic impact of AI and prepare for its future implications?
That’s the question that three professors, Ajay Agrawal, Joshua Gans, and Avi Goldfarb at the Rotman School of Management in Toronto, try to answer in their new book, Power and Prediction: The Disruptive Economics of Artificial Intelligence.
The book is a sequel to their bestselling Prediction Machines: The Simple Economics of Artificial Intelligence, which explained the basic economics of AI as a prediction technology.
The author’s believe that AI presents an extraordinary opportunity and an extraordinary threat. But not in the way that might be expected.
Core idea of the book: AI is prediction technology. We can use it to make better predictions about more things, when then drive improved decisions.
Prediction technology can transform industries. It does this by decoupling prediction from the other aspects of decision-making, thereby enabling new ways of delivering value. Unleashing this potential requires the invention of new ways of operating, many of which remain undiscovered.
Decisions = Prediction + Judgement
Today, we sit in the Between Times after witnessing AI’s potential, but before its widespread impact.
On the other side of The Between Times, when this process of invention is complete, the changes in decisions will mean changes in power. In industry, power confers profits; in society, power confers control.
Note: AI in this book is a far more holistic term than just LLMs and ChatGPT which have been getting all the attention lately.
This recent presentation by Prof. Goldfarb in Erik Brynjolfsson’s class at Stanford is a good summary of the key ideas.
You could also listen to him on this Invest Like The Best episode: The Economic Impact of AI.
The book is divided into 3 parts:
Part I: The Decision Economy. This introduces the concept of the decision economy, which is the set of interdependent decisions that determine the outcomes of any system. They explain how AI shifts prediction from humans to machines, which enables faster, cheaper, and more accurate decisions.
The critical concept in Part I: The Between Times – We have entered a unique moment in history - some industries have been quick to embrace AI, while others are slower. The reason for this uneven approach is because we have not fully considered the effect of the larger systems in which we operate. The Between times are when we will use point solutions rather than system wide solutions, they equate it to when electricity became wide spread, many factory owners just removed steam engines with electric motors in their factory without re-thinking the entire system and structure of what was now possible.
Part II: Power and Profits. This part explores the implications of AI for power and profits in different contexts. The authors examine how AI affects market structure, competition, pricing, strategy, and regulation. They also discuss how AI can create or destroy value for customers, suppliers, workers, and society at large.
The important concept in Part II: When rules should become unglued – Rules are good to help reduce error and ensure reliability. However, some rules have been created to mask decisions in an organisation that have a degree of uncertainty. We all remember them system wide COVID rules which in hindsight were too broad and created far too much damage versus potential smarter solutions based on better information.
“Ungluing” a decision from the related policies and procedures enables AI to make predictions. We can have the AI system make a prediction, and then the decision is taken separately.
Part III: Preparing for Disruption. This part provides guidance for business leaders and policymakers on how to prepare for the coming AI disruptions.
The key concept in Part III: Power and disruption – As old systems are displaced, there is a shift in economic power. Someone might have power today because they have data allowing them to make better predictions. But if AI can provide better predictions to everyone, we can decouple prediction and judgement.
A machine will make prediction, and the appropriate person will make a judgement on that data. Who is the right person, right skills to make judgement based on the predictions. For example: in the MasterCard network, the AI now makes the judgement in microseconds on fraudulent charges versus in the early days each store had to use their judgement. The decisions moved.
Key questions when implementing AI:
How do we learn both individually and society wide to think probabilistically? With AI, things are probabilistic. It is no longer binary or deterministic.
How do we build AI into the systems level - rather than a point or application level change?
What are the core decisions being made inside your firm or organisation and how can AI / data help you automate them or make better ones?
P.S. As a fun experiment, I had BingGPT compose 60% of the structure of the above and then adjusted and added to it. It was a useful shell to start with and showed me a quick example of where AI can help.
C. The Technology Section:
1. Generative AI: What’s New and What’s Next. Amidst all the fear about AI triggering a species wipeout, perhaps the more pertinent worry should be that of malicious human actors, powered by a competence with AI relative to everyone else, wielding a weapon that in an online world will eventually be able to pass off as human, evoking human emotions and pushing our buttons better than any real human can.
This concept was well discussed in this Ars Technica piece by Rob Reid: “Don’t worry about AI breaking out of its box—worry about us breaking in”.
Lots to think about.
2. Prompting is how we use Generative AI. For most of us mastering AI is going to be about learning how to prompt well. I learnt a lot using this great online resource.
3. After decades of blue-collar jobs being snatched up by machines, advanced chatbots are now breathing down white collar-jobs.
Generative AI tools like ChatGPT have made significant progress in crafting human-like responses to many queries. So much so that chatbots have now leapfrogged humans in certain tasks. This could impact as many as 300m jobs globally, according to Goldman Sachs.
Source: The Economist
However, AI automation should not be feared by default- at least according to The Economist. It could unshackle workers from mundane tasks and unleash greater labour productivity, which would be a boost for tight labour markets in advanced economies.
A study by Goldman Sachs, published on April 5th, suggests that generative AI could grow global GDP by 7% in the next decade. The GS study was well summarised in this twitter thread.
D. Charts and News You Might Have Missed
1. The voicemail might be in decline, but voice notes are not. Users are dropping self-recorded files, often quippy or gossipy, on apps for work and dating. Many senders and recipients feel they work better than text.
A recent poll found ~30% of respondents communicate via voice note "weekly, daily or multiple times a day." 43% of respondents between 18 and 29 years old said they do so at least weekly. On Hinge, which became the first major dating app to add an audio feature in 2021, the number of voice notes increased by 37% between January and February this year compared to that same period in 2022. They're most popular among millennials.
2. US mortality rate is much higher, at almost every age, than that of most of Europe, Japan and Australia. That is, compared with the citizens of these nations, American infants are less likely to turn 5, American teenagers are less likely to turn 30, and American 30-somethings are less likely to survive to retirement.
In fact, a new analysis shows that the typical American is 100% more likely to die than the typical Western European at almost every age from birth until retirement. Access to health care seems to be the biggest factor.
3. A friend ran the London Marathon last weekend. This chart helped me visualise just how good he is to have run it at 3:20!
4. Huge demographic difference between India and China. What difference will it make?
5. I hadn’t realised the level of concentration in the consumer staples market.
Thank you for spending your precious time reading this.
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