Palantir Technologies Inc. Class A Common Stock AIPCon 11

Please welcome Co-founder and Chief Executive Officer of Palantir, Dr. Alex Karp.

Hey. God, I hate watching myself, but I guess I have to get used to that. Thank you people for being here, and we have a lot of long-term friends in the audience. Our retail investor reped here. Many people we have worked with for many years, many Palantirians who have been here forever. Revolutions, basically, typically, we think of sex, drugs, and rock and roll and how that kind of changes the world. Most revolutions actually do start with something like a somewhat flawed idea that progresses into an idea that is less and less flawed, that does change the world. Look at how we ended up with our Constitution. Look how Silicon Valley was built, how America was built, other great civilizations were built.

We assume that everybody involved, like my parents were involved in protesting everything, but also the civil rights movement, and that when you are actually doing it is a lot of just small changes that lead to very big differences. Then a compounding and density of talent around those ideas, which is the way it is still the case that America and Silicon Valley have the greatest density of actual, functional, useful, compounding talent in the world. It really was just American industry and American government working on problems with a university that I went to, that was viewed as universally second-rate, called Stanford. I was like, "Oh, yeah. So second-rate, we can actually get away from just learning Latin and Greek and solve a couple of real problems. Yeah, we are not doing real academics, but we are building companies." Then that spirit.

If you look at the AI revolution, which really, in nascent forms, began a long time ago with NLP, and these things did not really work, and part of the forward-deployed engineers was completely taken from noticing that in France, the food tasted better because essentially, the waiter was forward-deployed, meaning he was an expert in what they did, understood the product, would change the product for the partner client's eaters need, but would not pour corn syrup on the foie gras, no matter what you paid them. That is also important at Palantir. We will not build bullshit. We had this originally in the U.S. government. We ended up having to sue the U.S. government, that is kind of well-known.

But the main reason we had to sue the U.S. government is we had this general, and I am sure he knew a lot about the battlefield, but he did not know much about tech. He was like, "Build me this bullshit alien anti-gravity machine that also tells me I am brilliant." And one of my Forward Deployed Engineers literally told the general, "But you are not smart enough to know how dumb you are." Now, okay, you are not supposed to do that, but that was really important. Then you look at what happened currently with the AI revolution, which started with, oh, it became real. Large language models could do very important things. Of course, they lacked precision. And of course, it really did not work with an application layer.

But there was a willingness to say, "Well, something is moving, and yes, we are paying too much for tokens," and not to pay enough attention about the alpha that was leaving all of our businesses, except for in the classified environment that was never possible. So we knew a lot about how do you make models work where the model becomes precise. Ted is going to talk about this, but essentially, precision as a function of safety and usefulness was already a huge hurdle and required Forward Deployed Engineers rebuilding the Ontology, find post-training models. But also, and there have been many vulgar versions of this in French, actually, especially like we cannot afford to engage in various acts without protection, but you cannot use these models without an application layer, and that became very clear.

But then what became clear of late, and we have NVIDIA and Cisco and others here that are going to talk about post-training, was you do not have to expose yourself to the dangers of random encounters with somebody who is known to be promiscuous and known to take your value and give it to other people. You can capture the whole value of your stack in your enterprise with your own models using frontier models or open-weight models that are fine-tuned. We are using these currently in many environments, especially interestingly in classified environments, where we are getting all the benefit of a model that is outperforming frontier models at a lower cost because of an application layer, with no safety concerns, where you control the alpha. What is that? That is the revolution that actually is changing, primarily, it is not just America, but is dominating the American landscape.

Because what makes America special is the neurodivergent freak show that I very proudly represent. We bring creativity and ingenuity and knowledge to business. And a ruthlessness and an awareness that these things are real. We are not chillaxing, waiting for our vacation to come in this country. Nobody in business survives that way. You will be replaced, out-competed, totally disappeared, and sent home to do something else. We are in an active environment where we have very specialized ways of doing what we do. We need to augment them, protect them, make them more precise, make them safer, and never let our adversary on the battlefield or our competitor in life understand exactly why we are doing the thing they cannot do. And the systems are at scale. NVIDIA has the most complicated supply chain in the world. Their supply chain, we are on battlefields all over the world.

Their supply chain is more complicated than many countries' supply chain. It has to work. They do not ship. A lot of the things we do in this country around the world will not work. That, interestingly, yes, that is a revolution. We are not really doing the sex or the drugs, but we are doing the rock and roll. That is literally what is going on, and that is what you see in our company. The other thing I am very proud of is the sovereign focus does many things. Just like the focus on helping the West, you end up with the best business partners ever because we are aligned with you, and we end up with businesspeople and engineers and IT people who are aligned with their business.

That is an incredible thing because there is also just a lot more fun in getting these things done, in winning and the alignment. You end up working with the best people in the world, and you share ideas, and we proudly partner and share. We are in the business of getting paid after value creation. We are not in the business of convincing you it is valuable, providing steak dinners, taking your alpha. One of the reasons besides the immorality of it, the fact it would not work, it would not work for us, it is less fun, and you end up with the half-idiots. It is no fun. This is like we end up with the very best partners in the world, which are you and many people watching this, and the very best investors in the world. We did our DPO. By the way, we get rid of all the bullshit experts told you not to invest.

All those experts that have no idea. We do not have many of them in our lives. It is great, too. With that, welcome. We are having a great time building our business into something that is much larger and scaling with and through partners. I am delighted you are here. Yeah, let us keep the music rolling.

Take care. Bye. Please welcome Senior Director of Solution Architecture of NVIDIA, Alex Neefus.

Thank you. The world is constrained by a lack of compute. NVIDIA views our supply chain as starting at the wafer and ending at the first token that is produced. There is unprecedented demand for our products right now. They power all the AI workloads probably of everyone in this room. The question we have is: How do we keep up with all of you and your insatiable demand? To do this, NVIDIA needs unprecedented visibility to identify constraints so that we can build the world's most resilient supply chain. We need to maintain a reliable AI infrastructure supply chain. This is a Grace Blackwell NVL72. It has millions of parts that come from thousands of suppliers who are spread across the globe. Whether you know it or not, this machine is likely running your AI workloads today. Take the compute board that you just saw.

It has its own bill of materials, suppliers, and lead times. Dozens of individual OEMs are dependent on getting that same compute board in order to build the final system. However, our manufacturers cannot start until they have all the critical components they need, CPUs, GPUs, memory, and many more. We call this the Constrained Material Allocation problem, or CMA, and it is the hardest problem we face in supply chain. Optimizing the allocation of those components, some are coming directly from us, others are on consignment, but we are stocking anyway. We want to optimize not just production volume, but we want to minimize the amount of time that those critical components are sitting, waiting for other material to show up before we can build those boards. We have a name for this. We call it Time of Ownership, or TOO. It is the most important metric that we have.