Infra Play #151: AI sovereignty

Doctor Karp is on the case

Back in February, in #130, I revisited Palantir and how well it has scaled in the AI era. In my view at the time:

International revenue is stagnating while 73% concentration sits in the US, creating single point of failure exposure to political cycles and defense budget sequestration. The technology moat is the ontology layer and process mining capabilities, but it's eroding as LLMs become increasingly capable of analyzing operational data and generating automation code without a proprietary platform. At current multiples you're paying for a decade of compounding at rates that assume perfection across government retention, international expansion, and continued technological superiority. The harsh reality is that software line items within defense budgets are among the first to face scrutiny during consolidation phases because they lack the constituency protection that hardware programs enjoy. We've reached peak Palantir.

Half a year later, we are starting to see the cracks show more prominently, with what Dr. Karp described as a "meltdown" during an interview. I don't think that description is appropriate, but it is interesting to take a look at their thesis around AI sovereignty, which appears to have a few more holes than expected from what has been historically a very prudent and insightful leadership team.

Sorkin: Palantir is expanding its partnership with Nvidia to build custom AI systems for the US government. That stock is shooting up, up again this morning, up almost 6% this week. Joining us right now exclusively at the table, Alex Karp, Palantir’s co-founder and CEO, and CNBC’s Seema Mody, who covers Palantir. Tell us about the deal with Nvidia. There are so many things we all want to talk about, but let’s get to the Nvidia deal first, because I have so much respect for Nvidia and Jensen Huang.

Karp: I’m going to try to keep this more adult than I usually do. But the truth is, if you want to know how this came together from my perspective, there are a lot of technical issues: who controls the models, who controls the weights, who controls the value of your business. We’re sitting on critical infrastructure across America, Ukraine, Israel. Everyone who uses LLMs on the battlefield runs on top of our ontology. And to say our clients are unhappy with the frontier labs is like saying I’m welcome at the Berkeley faculty. There’s just a level of discomfort and loss of trust that also made this really attractive.

Sorkin: Okay, unpack that. What do you mean by that?

Karp: When you’re using large language models, at this point everyone who’s technical realizes they’re a critical resource. To make them valuable in an enterprise context, like a battlefield context or a regulated context or manufacturing, you have to have what’s called an application layer. We have this thing called ontology that now everyone’s copying. De facto, it takes a large language model and makes it safe and useful and precise. Safe because it doesn’t touch your underlying data. Safe because it prevents the large language model from caching your data and replicating your business. Safe because it doesn’t transfer your IP, how you fight, secret data, top secret data, or in a clinical context. So the general way these things were sold... and again, Sam and Dario, there’s nothing more fun than debating Dario in private, so I’m not throwing shade at them... but something has gone completely wrong. The basic view among enterprises in this country is: I’m going to chillax and waste my time with tokens, I’m going to get no value, and they’re going to get my IP.

There are some directionally correct parts here and some strange choices in how to frame the challenge.

Yes, clearly governments are feeling uneasy with the very rapid rise in the importance and influence of the AI labs, who do not currently operate a mature supply chain framework for interacting with the defense ministries they’ve been eager to monetize. The conflict with Iran demonstrated a step up in capability and field intelligence utilization from the US army that can clearly be connected to the use of LLMs across a variety of use cases.

The framing around Palantir “protecting your data” is rather weird, particularly at a time when EU government customers are churning at a rapid rate. I’ve personally had discussions around their mistrust of the Palantir teams, including refusal to provide usage logs and making it difficult to migrate away.

Then we go into a logical fallacy, where Palantir is helping provide this massive value from LLMs, but enterprises who are not customers are actually “wasting time with tokens and getting no value.”

Quick: That sounds like shade, though.

Karp: And not just shade. No, no, no, no, this is reporting. This is reporting that I’ve literally, against my own interest, called out. I’m profiting from this, right? So the reality is, you may not like us at my former school Haverford, or at Berkeley, but enterprises in this country trust and love us, especially ones involved in critical infrastructure, both public and private. We’re coming up to July 4th. I want us and our friends across the globe to have the very best tech resources. In fact, the whole secret of Palantir here is the forward deployed model, the products that have been five years ahead. You’ve been with me for a long time. Everyone said FDEs (forward deployed engineers) were services. They said we don’t even know what an ontology is. That’s the only thing people talk about now. The secret was we delivered the best things for the war fighters. Those war fighters have serious trust issues. But it’s not just vis-à-vis the frontier labs. Then you have my enterprises in the private sector who have the same issues. They’re like, why would they get access to my data if they’re going to build my alpha? Why wouldn’t I control the weights?

Sorkin: And that’s where you get this partnership.

Karp: What aligns me with Nvidia, and I think what the technical customers want, is control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, that it’s not being transferred to someone else. They’re not interested in some fake deployed code that somehow is deploying tokens that transfer the alpha to a third party, and then the jig is up. So we have to figure out a way... both our products are agnostic. We now sell a product to customers that lets you switch from model to model, we’re completely agnostic, but we need to rebuild trust. And that trust is going to happen where everyone gets to ask and answer basic questions. Who owns the data? Where is it cached? Are the prompts secure? Is this being transferred to you? Are you being compensated?

For a statement meant to address the needs of technical customers, this is disingenuous at best.

“What the technical customers want is control over their compute, their models, their data stack, and their alpha.” Sure, except that the vast majority of companies do not want to own compute in that way and have migrated the majority of their workloads to the hyperscalers.

“They’re not interested in some fake deployed code that somehow is deploying tokens that transfer the alpha to a third party, and then the jig is up.” Since the majority of tokens at enterprises are consumed via API with the hyperscalers, their usage has been private for a while, notwithstanding the contracts prohibiting model training on that data with the frontier labs themselves. So either Karp is stating here that the rules are being breached, which if true would bury the labs under lawsuits, or that the hyperscalers are not providing a proper service, which would go against a decade of carefully built relationships sitting on top of contracts worth billions.

“We now sell a product to customers that lets you switch from model to model, we’re completely agnostic, but we need to rebuild trust.” Which is something that’s been available from many providers for a while. Very few companies offer single-model products if they’re building on top of the frontier labs.

Kernen: Okay, if it was so valuable, let’s say I can make you a billion dollars tomorrow. Wouldn’t I say, I’ll make you a billion dollars and I want 30%? Why are they charging for tokens if it’s so valuable?

Mody: So then, Alex, if the key, from what I’m hearing you say, is a secure American-born open-source model, how quickly can your model compete with frontier AI and agentic AI?

Karp: What I am claiming, obviously slightly true but slightly self-centered, is that it’s the model plus an application layer plus compute. It’s really all three. In our jargon, that’s the value. The reason... just look at our financials. The reason everyone is chillaxing with bad financials and growth while losing money is that the client refuses to pay the true cost. The two places that actually make money, like profit and free cash flow, are our application layer called ontology, and compute. What I am claiming is that we can take an open model, in the classified or non-classified context, and get it to the point of a frontier model, but you control the weights.

Not to point out the obvious, but Databricks is about to have the same run rate as Palantir, and the frontier labs have long surpassed it by 5x to 10x in terms of multiples. Choosing to focus on the profit angle is a fair dig (as Palantir is the only public software vendor that actually makes the Rule of 40 after stock-based compensation) but not some magical forever moat. If anything, a lot of it is connected to the pointed choice of running a very small GTM org and then cheating employees out of their earnings.

Sorkin: So what is the true cost? Not just what you’re paying?

Karp: The true cost is not just what you make minus what you lose, meaning the value of your business. We can get the frontier application to be exactly the same as a frontier model without the risk of transferring the alpha of your business to another. By the way, you could do this with a frontier closed model too. But then the clients have to be able to ask and answer very basic questions. Are you keeping the data? Are you going to enter our business? And in the classified context, when the Department of War goes to you and says I need this application, do they get to control the weights to do it, or do you get to control the weights? Are we really going to outsource the battlefield of this country to the consensus view in Silicon Valley? That is effing insane. And by the way, every single enterprise in this country, in private... a lot of them don’t want to speak in public, because it gets outsourced to the neurodivergent crazy person who apparently is on drugs. The one thing I don’t do... okay, so that’s my role. But I’m telling you, in this country, at every single enterprise I deal with, these people are livid. They’re like, I am paying for tokens that create no value. These people are stealing the weights and alpha of my business, and they’re creating a wealth tax that does not help the poor. It just punishes... it starts with the billionaires. Every single person at this table is going to be paying a wealth tax only to punish us. And the reason for it is because these models have been completely, irresponsibly oversold. The sale is: it’s dangerous for everyone, which is why I can give it to all your adversaries, but I can’t give it to the Department of War, or I can’t safely give it to an enterprise in this country, without being certain that the alpha of that business could transfer to this model tomorrow. I.e. I have no business, no job.

Again, it can't be that the models are "oversold" and generate no value, but somehow they are also "stealing all of the alpha" and Palantir is the only org somehow delivering "frontier applications." There is also a very big difference between the approach taken by OpenAI and SpaceX versus Anthropic, with the latter being the only organization that can be accused of branching out into the business of their customers (or more specifically, software vendors).

Sorkin: You sound pretty angry.

Karp: No, this is the voice of American business being channeled through me. And I’m telling you, it is absolutely a problem for this country, because we are on the cutting edge of every single AI technology. But if you’re going to triply oversell something... and by the way, the enterprises are just tired of it. I want everybody watching this to test what I’m saying, especially investors who think somehow this is working. Pick up the phone and call a CEO in private, not in public. Every single person here can do this. Call two or three and say, “Madman Karp is on TV saying we’re livid.” I’m not going to quote you, you won’t be quoted.

Quick: You have a history.

Karp: And you’ll see, they’re twice as livid as me.

Sorkin: So if you’re right, does that mean we’re living in some kind of terrible AI bubble, and that a quarter or two or three quarters from now we’re going to hear that big enterprises are canceling their subscriptions to these products, or that the buildout is going to slow?

Karp: This is the tragedy of it. The reality of compute plus ontology plus model is changing the course of history. Ask the Ukrainians, ask the Israelis, ask our Department of War, ask the enterprises that are working with us. We do not have to oversell what we have. And it’s all being built in this country, basically, except for the open models, which is a real thing coming from China, and except for Nvidia’s open models, which are world class. It’s all being built here. We do not have to overhype it to the point where we have a wealth tax punishing everyone. If they’re charging the enterprise three times as much as they should be, and then they have to pull back on that, that changes the math of all of this.

The voice of big corpo management (who are allegedly the most talented and smart people in the world) is channeled through the body of Dr. Karp.