Paul Kedrosky: AI is the First Bubble With Every Ingredient at Once | #648

**Paul Kedrosky** (0:00)
This moment is the first one that sits at the intersection of all of the forces that created the largest bubbles in US history. I joke all the time that from the standpoint of most of the lenders that I talk to, it could be hide and go seek competitions going on inside the data centers, and they wouldn't give a f***. Tokens are the first hyper deflationary commodity in the history of modern economies. Good God, I hope I don't go crashing down, because I need to grow at this speed just to stand still.

**Meb Faber** (0:31)
Welcome to The Meb Faber Show, where the focus is on helping you grow and preserve your wealth. Join us as we discuss the craft of investing and uncover new and profitable ideas all to help you grow wealthier and wiser. Better Investing starts here.

**SPEAKER_3** (0:44)
Meb Faber is the co-founder and Chief Investment Officer at Cambria Investment Management. Due to industry regulations, he will not discuss any of Cambria's funds on this podcast. All opinions expressed by podcast participants are solely their own opinions and do not reflect the opinion of Cambria Investment Management or its affiliates. For more information, visit cambriainvestments.com.

**Meb Faber** (1:00)
Summertime is over, everybody. So we got an awesome guest today, Paul Kedrosky, a fellow MIT Institute for Digital Economy, partner, SK Ventures, weather, ski nerd. I mean, I remember him from back in the real money street.com days, former sell side analyst, a little bit of everything. Paul, welcome to the show.

**Paul Kedrosky** (1:18)
Hey, thanks, man. Glad to be here.

**Meb Faber** (1:19)
I want to kick it off with a quote. He says, it's going to take a lot of AI to solve the problems of AI.
What do you mean by that?

**Paul Kedrosky** (1:28)
One of the things that interests me in general, whether it's this particular episode or the global financial crisis, or the.com meltdown, pick your favorite implosion historically, all the way back to like canals and railroads is scale, like big things that move in ways that are both unexpected and more consequential than people realize. And there's a tremendous line from the physicist Albert Bartlett, goes something like, the greatest failing of the human species is an inability to understand the exponential function, which is another way of saying that things that get scale quickly really confuse humans. The old idea that three periods before some algae covers an entire pond, right? So then in the last period, it was only half covered, and before that it was a quarter covered. And so that doubling notion of algae in a pond is another example of this scale. So AI is kind of the canonical current example of prodigious scale and exponentials that are completely misunderstood by people, and both by bulls and by bears. And I spend like a ridiculous amount of time talking to people about this in all the different ways that the underlying exponentials, for example, are misunderstood that there's an exponential adoption curve, but there's also an exponential deflation curve. It's the fastest deflating commodity in the history of quasi-industrial commodities, following something like 70 or 80% a year.
And all of these sorts of intersections are really interesting to me. And the one that specifically triggered that comment was because the scale is growing so quickly and the interconnection into the grid can't keep up, people are increasingly being applauded for bringing their own, bring your own beer, bring your own power, adding natural gas turbines behind the behind the meter. And that, of course, has consequences in terms of specifically energy and emissions. And so the joke always is Dario Amadei, Sam, and lots of others love to talk about how AI is going to solve all these problems, whether it's drugs, longevity, or carbon emissions and climate. And it's kind of hilarious because one of the greatest contributors at the margin right now is this prodigious addition of behind the meter power, usually in the guise of natural gas powering all of these new data centers. So long answer to a short question, it's going to take a lot of AI to solve the problems created by AI in climate alone. If you go back to the history of the largest financial and economic bubbles, paroxysm moments, whatever you want to call them over the last 200 years, they tend to have a bunch of things in common, which is really interesting, right? They tend to be related to maybe loose credit. They tend to have a great technology story behind them. They sometimes have a real estate component behind them. And they sometimes have a policy angle. You take that back to the South Sea bubble and there's a policy angle. This, to my way of thinking, this moment is the first one that sits at the intersection of all of the forces that created the largest bubbles in US history. And that's what makes it distinct, unusual, and makes the scale really difficult for people to understand because they approach it through the lens of credit, or they approach it through the lens of real estate, or the geeks on X approach it through the lens of five prompts that will change your life, or whatever the case may be. And the reality is this moment sits at the intersection of all of these, so you can go backwards and think about the railroads. You can think about the canals. You can think about rural electrification in the 1920s. You can think about all these scale moments where massive amounts of capital were allocated towards something hugely consequential and then created a lot of breakage along the way.