State of the Markets

These are the early days of the artificial intelligence (AI) revolution, the infancy stage of what we believe is likely to be a transformational change moment in the course of human history. Like any era of change, we stand on a blade’s edge — on one side: the promise of prosperity that has historically accompanied eras of innovation; on the other: the inevitable fears that we are going too fast and markets may be due for a reckoning.

This much I know to be true — no one knows the path this fast-flowing river will carve, but if we are honest with ourselves about what is knowable and not, we can apply lessons from history to stay disciplined in our investment approach.

I have been asked in many venues whether I see parallels between the rise of AI and the rise of the dot-coms in the late 1990s, but my most recent thinking takes me even further back in time. I think about another era of rapid change and disorientation — the height of the Italian Renaissance in the early 1500s, when Machiavelli wrote The Prince. In short, it was another time when the river moved fast, another time when the prevailing thinkers believed humans possessed the power to alter the course of the world.

The pace of change in today’s world can feel overwhelming, and as in previous eras, we should expect it to bring human advancement and creative destruction. In Machiavelli’s day, wealthy city-states in Florence, Milan, and Venice waged battles for economic dominance, shipping routes expanded globally and diverted goods to the wealthiest European powers, and banking innovations like credit and payment systems fueled a surge of international trade. The world has never been the same.

In times of transformational change, the protagonists have been the founders and disruptors, those unique souls bold enough to reject the old order and brazen enough to believe they can, as Steve Jobs said, “make a dent in the universe.” The common threads that connect the Renaissance to the industrial revolution to the dot-com boom to the AI revolution are founders and disruptors who imagine, build, and monetize innovation at scale.

• The Medici Family made the bulk of its wealth devising a system for international trade, but the major innovation that it brought to the world was the scalable financial system it established to enable the transfer of funds across borders without the physical exchange of gold and silver.
• The Gilded Age beneficiaries of the Industrial Revolution dominated their industries with new machines that made mass production possible — the Rockefellers in oil, the Carnegies in steel, and the Vanderbilts in railroads and shipping.
• History often recounts the epic failures of the dot-com bubble, but there were plenty of founders and disruptors who thrived. Larry Page and Sergey Brin founded Google in 1998 to make it easier for Internet users to find information quickly, and few could have predicted that their innovation would disrupt the advertising and media industries. Jeff Bezos founded an online bookstore in 1994, and as Wall Street badgered him for decades over growth without profitability, he disrupted the bricks-and-mortar retail industry, forever changing how we shop.

So it will be with the AI revolution, in our view. New ideas come to market. Some succeed, some fail, and some disrupt in ways no one can predict. Obsolete industries die off, corporate investment is redirected, the job landscape shifts, and vast fortunes are made and lost seemingly overnight. That begs the question: How shall we invest in these murky early innings of transformational change?

I find Machiavelli’s pragmatic realism instructive in this moment. In The Prince, he uses the metaphor of a river, writing that fortune is like “one of those violent rivers which, when they are enraged, flood the plains, tear down trees and buildings, wash soil from one place to deposit it in another.”

Is there a better expression of creative destruction? When the flood subsides, we find the river has carved a new path; it’s up to us then to consider where the river’s new path may lead us.

As I reflect on this past year, I see in the headlines the markings of great change:

• Nvidia Corp. became the first company to exceed $5 trillion in market capitalization, a size equivalent to the gross domestic product of Germany. The chipmaker reported $57 billion in third-quarter revenue — nearly 10 times its revenue in the same quarter of 2021. Apple Inc., one of the largest U.S. technology hardware companies, and Microsoft Corp., the largest U.S. software company, each exceeded $4 trillion in market capitalization recently.
• Mark Zuckerberg, chief executive officer (CEO) of Meta Platforms Inc., declared recently that the great risk in the AI era is underinvesting, not overinvesting. In its pursuit to be a leader in “superintelligence,” a form of AI intelligence that aims to surpass the human mind in problem solving and decision making, the company is investing $27 billion in its Hyperion data center in northern Louisiana; it will be over 4 million square feet, stretching end-to-end to a length equivalent to the size of the island of Manhattan.
• SpaceX launched its 139th mission this year — that’s more than NASA’s space shuttle flew in its 30-year history — and it now uses reusable booster rockets, previously unheard of at NASA. It also launched its 10,000th Starlink satellite into orbit; 0.1% of the world’s population uses Starlink satellites today, and almost no one has yet grasped its potential.
• Something to think about as you wait for your robotaxi to arrive: Anduril Industries, a private defense contractor working to build AI-powered unmanned aerial systems for the U.S. military, flew America’s first semiautonomous fighter jet in late October. That means it isn’t controlled remotely; it operates by itself and adjusts its flight without human input. Amazingly, it went from clean-sheet design to wheels up in just 556 days, a production pace that is five times faster than it took to create prior human-controlled fighter jets.

These are the sorts of endeavors that, in my opinion, can only happen in an economic system that aligns investment with innovation. We are quick to focus on the noise of political fractiousness and slow to recognize that our economic system still enables Moore’s Law, the compounding effect that doubles the speed of technology change in a geometric way. Time compresses, advances accelerate, and non-linear innovation multiplies the set of potential change scenarios.

When new realities are created, even the founders and disruptors can’t predict how their ideas will evolve in a free market. But we are the fortunate few who get to see it and live it and watch it all unfold with wonder.

So, where might the AI revolution go from here?

When the river rages early in a transformational change cycle, the range of outcomes is broad, risks are intensified, volatility can be disorienting, and there can be harsh consequences for incorrect choices. Let’s frame three broad scenarios:

1. A muted outcome: The first possibility is that the large language model (LLM) path the innovation leaders are taking fails to materialize anywhere close to the level expected. This is doubtful but must be considered as a probability of higher than zero. And if this is the case, then we’ll discover that instead of more compute leading to continued gains in the intelligence of these systems, we hit a point where the incremental returns decline while the costs continue to rise and scale, and we’ll conclude that this approach won’t lead us to some kind of wildly profitable future state after all. I think this scenario is unlikely, but prudence suggests the probability needs to be considered within the range of outcomes.
2. Success with economic consequences: The second possibility is that we’re on the right path, and the massive and accelerating investments we’re seeing now will eventually generate stunning profits — but that it takes a few years to get there. And in this interim period, the race to build the infrastructure to support AI sparks inflation — the kind we’re already seeing in electricity prices — but inflation strikes before the economy experiences a material gain in productivity. This scenario needs deeper contemplation, but I suspect it would prove challenging for markets, central banks, and companies to get to the other side of this formidable air pocket.
3. AI proves spectacularly accretive to economic growth: The third possibility is that AI investments are already having a meaningful positive impact on the economy — in all the ways we can see and in other ways that may be less obvious. If this scenario is already true, then we would expect the impact of AI to accelerate beyond what markets and investors currently expect.

The question is how do we anticipate which of these three simplistic scenarios is most likely? Or more important, which scenario will be seen by markets as most likely?

Simply put, we don’t know yet, but let’s expound.

If the first possibility, the muted outcome scenario, is right, it will probably take at least a few years to know. It may be that if you connect enough compute using a LLM model, a new superintelligence miraculously appears. With so much capital committed to this race, it seems unlikely that the major players will give up anytime soon.

How about the second scenario? If the inflationary costs of the AI buildout arrive now, but the benefits don’t materialize for a few years, what would that look like today? We would likely see AI’s gluttonous appetite for investment capital starve other industries of capital, and the resulting loss of productivity would bring repercussions for the economy.

And what if the third possibility is right? If AI is already lifting productivity, we should see the economy perform quite well. Perhaps surprisingly so. Because our economic PhDs tend to be more comfortable assessing the future through a rearview mirror, their forecasts are unlikely to call for anomalies this would create. And it is therefore worth noting that despite the tariff hikes, trade disruptions, immigration shutdown, the exodus of migrant workers, and vast AI investment spending, inflation has remained remarkably low. That’s probably how we will know.

Change is the one constant with investing. As Machiavelli wrote long ago, “One must be adaptable to changing circumstances, at any cost whatsoever.” There is no off switch for the compounding change being thrust upon us. The costs this time will be great, for governments and businesses alike, but we think they’ll conclude that these are costs that must be paid. Given what’s at stake economically and militarily, we think they’ll conclude there is no second place in the race for global AI superiority.

As investors, we must understand it, embrace it, and bend it to our advantage while managing for the uncertainty and risk that naturally comes with change.

The greatest opportunities in markets often reveal themselves first as mysterious phenomena, at times when markets move in opposition to general principles. It is not at all uncommon to see irrational exuberance over the wrong innovations — the fact that I have seven AI chatbot apps on my phone may be an indicator that the AI revolution isn’t likely to be won or lost based on who has the best chatbot — nor is it uncommon to hear voices warning that the sky is falling, even on sunny days.

Remember that the core principles of disciplined investing have not changed. The best investments are and have always been a reflection of risks taken at scale by founders and disruptors who see with conviction a future that others can’t see. Even if they go fast, as they must, investors can take their time and make decisions based on good data, durable trends, and their own appetite for risk.

History teaches us that periods of transformational change often follow repeatable paths even if the pieces of the puzzle are different. Our job as investors is to keep working the puzzle until the pieces fit together. Each piece holds clues — sometimes, the patterns are difficult to see; other times, the patterns are readily apparent. This puzzle is extraordinarily complex. Paradoxically, the really complex puzzles that matter, and ultimately alter the course of human history, when revealed can have rare and profound implications.

Forecasts are not guaranteed and based on certain assumptions and on views of market and economic conditions which are subject to change.

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