This is one of the most remarkable businesses in the history of capitalism?
Model commoditization is a risk. You know what else is a commodity? Crude tankers. Construction. Cloud computing. Energy. Lots of multibaggers.
$ANT is asking for your bid, not your hand in marriage.
Maybe it's worth < $1.5T. Maybe it ends up > $30T 🤷♂️ The appropriate reaction here is amazement, but all I see on fintwit are critics.
I now think the biggest barrier to people's (and Dario's!) understanding of the world (and therefore macro themes like AI) is negativity bias.
I kinda agree with this, except viruses are way more predictable than cyberattacks.
A truly bad attack would come from a hostile state. The timing of this affects the severity a lot (later is better), which depends on unpredictable geopolitics.
openai.com/index/patch-the-p…
There’s only one other time I’ve seen the market this complacent in the face of an imminent, systemic risk. And I’m having déjà vu, because the risk around AI related cybersecurity has the same shape and setup as the pandemic risk in early 2020. Though it’s arguably worse.
Bearish market calls are a dime a dozen. But my threshold for making a public bearish call is extremely high. I’ve only done it once before…Feb 2020, weeks before the market fell 35% in a month.
By early Feb 2020 it was already clear to anyone paying attention that COVID was going to be a global pandemic. We had access to a lot of experts, and they were unanimous in their belief that a global pandemic was inevitable. And yet the public and the market treated it like another Ebola or SARS headline. When I warned people to prepare, I was told that we couldn’t have a global pandemic in this day and age. Today, people have the same difficulty imagining that the internet could become unusable. It’s so fundamental to how we live that its continued functioning is treated as a given.
In 2020, the market didn’t discount this risk until the evidence hit them right in the face. So the adjustment was violent and nearly instant.
In modern markets big tops are typically a process. They don’t tend to crash from all time highs. Economic data slows, breadth narrows, credit widens, etc. The market takes the signal piece by piece and distributes over months. But this one fell out of a clear sky, because an exogenous shock doesn't have to generate those kinds of signals in advance.
Quantitative models are good at extrapolating signals that have paid off in the past. That has increasingly become the backbone of financial markets, as well as betting and prediction markets. You can model a football game, or the weather based on data. But if a novel risk hasn’t shown up in the signals a model tracks, it doesn’t just estimate the odds poorly, it may not represent the risk at all. That’s why the market could sit at an ATH high in Feb 2020, with a catastrophe weeks away.
And its why the market currently sitting near an ATH doesn’t give me much reassurance. For a legible, datable risk it can discount ahead of time. It bids up vol into an election or a Fed meeting. But it struggles to price a novel exogenous tail because it has no reference class and no event date. It stays silent, right up until the repricing.
Today the cyber experts agree on the direction the way the epidemiologists did in February 2020. AI cyber capabilities now pose a risk to our entire digital system. And every day we get more evidence that we are nearing a tipping point. Our economy and livelihoods run on that system. The tail risk is a collapse, and its fatter than the market is pricing. I believe serious disruption is now a foregone conclusion, and only the magnitude and timing are still in question.
The market may wake up to this risk because of a single event that impacts the public in a visceral way, but that won’t be the underlying problem. That’ll just make it clear that the rules have changed. This is a paradigm shift in what attackers can do and how many systems they can target.
And like in 2020, the market can recognize the most obvious exposures without grasping how far the damage could spread. In the weeks before the 2020 crash the market did lightly discount the most direct, first order pandemic trades. The cruise lines, the airlines, a handful of others. But the fallout was never going to be contained to those names.
You can argue that the market is already discounting some risk, as the AI related trade has come under strain, credit markets are tightening, and there are other red flags under the hood. It’s hard to differentiate how much of that is due to cyber risks (and its second order implications), rather than fears over capex sustainability, large capital needs, valuations, etc. but the important point is that the market as a whole is still not pricing the scale of the risk.
Since the market tends not to slowly discount this type of risk, it means you can’t wait for confirmation. The opportunity is to position before the market recognizes what’s already qualitatively visible to experts. Which is what worked in February 2020.
But this isn’t an argument for fatalism, because the setup gives us an opportunity. Protection against an unpriced tail costs very little, because no one is bidding it. If the event never comes, you’re out a small premium. If it comes, you get paid from an undiscounted base, which is where the largest repricings in history come from.
That asymmetry means you only have to notice that the price of the insurance is cheap relative to the payoff.
I should say that the risk to this strategy is timing. A cheap convex bet is cheap per unit time but if that event takes longer then you can get eaten up by the carry. I think the timing of the market realization has now approached the point where my own qualitative analysis suggests that it is appropriate to take steps to protect your portfolio. But explaining the reasoning behind that assessment would take pages.
This isn’t financial advice. You should decide for yourself. I’m just making my own thoughts and logic public for anyone who cares how I am thinking at the moment.
I've never hoped more that I'm wrong.
AI reflexivity risk is important, but I think "spend intensity" is per employee, as defined in past presentations.
If so, this chart is unsurprising, mostly useless for supporting this conclusion, but good for getting Ara on some pods?
Finance bro data quality ever disapoints.
This chart shows the key risk to the AI trade, and it's missing from the latest revenue announcements.
The AI boom is fundamentally driven by a top 1% of companies that drive 80% of spend. Within that top 1%, 80% are venture-backed.
That's all fine if the AI trade works out, and if, as some prominent investors say, everyone wins.
But if it doesn't work out, then we have a cascading effect of large customers simultaneously pulling back their AI spend.
My view is the market is a chimpanzee with rabies and a shotgun: it's to be respected and feared, but not looked at as a source of truth.
It's remarkable how Mark's view (the consensus among professional traders?) and mine coexist because they often produce the same behaviors.
Professional trading is not about being right or wrong. It’s about seeing the caution signs—the red lights, the green lights, and the yellow flags—and adjusting accordingly.
The market is constantly giving you information. Your job isn’t to prove you’re right. Your job is to recognize when conditions change and yield when necessary.
Those who adapt the fastest, adjust the best, and know when to yield are the ones who stay in the game long enough to win.
But what tells us if datacenters are overbuilt are the full supply chain economics, not recent datacenter deals.
I can't find GB300 pricing, but $MSTF asks $69 / hour for a 1-year contract on an instance with 4 GB200s. That's $17.25 / GPU * hour.
devzero.io/instances/azure/S…
As models improve, the productive work a GPU can do increases. This increases its value!
If the quantity of work expands and the scope does not, existing scopes eventually saturate.
But we're a long way from saturation of current scopes, which keep expanding.
Elon's prime genius: find awesome, unique, not-really-impossible goals, which attracts top talent.
He's the coordinator & fundraiser for nerds smarter than him.
It's why he's not especially likely to have big success in AI or robotics: everyone is already working on those.
1. Tokens aren't a commodity. Astra output tokens are worth a lot more than Luna's.
2. There's no clear limit on the demand for intelligence.
3. AI produces massive consumer surplus. Problems within its supply chain are real, but can't collapse the entire industry.
I get it, there are nuances for tech-bros who are deep in the weeds. Everyone has an anecdote about why I’m wrong.
Take a step back and be a commodity-bro who’s seen enough supply/demand cycles. Tokens are a commodity. Currently, the token factories are out-stripping token demand. Pricing is the adjustment factor. Except token factories are mostly fixed-price businesses. They have take-or-pay. They have commitments. They will produce tokens at a loss rather than turn off.
I’m not saying that token demand is slowing. It’s still growing at astronomical rates. I’m saying that token production is now out-pacing demand. The cycle will turn when demand accelerates or token production slows. There’s like half a trillion $ of GPUs waiting to be installed. I don’t think token production slows anytime soon.
Yeah, I get it. Jevon’s and all. It’s great for AI consumers and innovators. But the guys owning token factories are gonna all go bust in the process, and that’s like $2T of capex to date. You cannot even restructure these things and crush the debt. They’re just stranded by new, and more efficient chips. They’re always going to be stranded by new chips. More efficient Models will strand the more expensive ones. It’s a race to the bottom against fixed costs. It’s the most godawful business misallocation I’ve seen in a while. Makes the Chinese look like prudent capital allocators🤣🤣
It’s like having iron rails when the new railroads run on steel. This bankruptcy cycle will be epic…
The marginal, price-sensitive barrel is out of Hormuz and is very expensive. The price of oil cannot drop until the cost of getting oil out of the Gulf drops, because a significant drop would cut a lot of supply.
This is way more supply elasticity than oil has ever had?
Replying to @LSREnergy
3. The physical barrel economics are far from normal
The oil flow volume may have recovered, but the economics of moving that volume are anything but normal. Before the war, a route that priced ~$3.00/BBL in freight at recent peak hit $33/BBL And freight is only part of it. There is war-risk insurance, STS costs, delays, longer voyages and less efficient use of the tanker fleet. A vessel spending more time completing the same transit is effectively removing transportation capacity from the system, even if the number of ships hasn't changed. Please don't take this as $30/BBL of additional freight means Brent should be $30/BBL higher. The cost gets distributed through the physical chain. Some appear in delivered crude prices, some in regional differentials and OSPs, and some is absorbed through lower producer netbacks. But from the buyer's perspective, the distinction is very real. A refiner buys a particular grade of crude, delivered to a particular place, at a particular time. That delivered barrel is considerably more expensive today even if the same number of barrels are leaving the Middle East. So when we say Middle East oil flows have normalized, we are really talking about volume. We are not saying the physical market has returned to its pre-war economics. It hasn't.
I've looked at every strike from multiple sources (UKMTO, JMIC, @WashInstitute), and it looks like each hit does enough damage to stop the ship from operating ~55% of the time. However only 14% of those look like total losses, so most damage is likely being repaired.






















