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Karp has been saying it for years: The Large Language Model is a commodity

Jack Prescott

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38,838 次观看 • 2 个月前 •via X (Twitter)

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The market is about to learn what Palantir CEO Alex Karp has been saying for years: “The large language model is essentially a commodity”. Swap Claude out with whatever model. It doesn’t matter. The value will come from the infrastructure (Palantir) that allows users to orchestrate the model. The effectiveness of Palantir’s Maven Smart System will remain unchanged; reinforcing the $PLTR thesis. Model agnostic.

The market is about to learn what Palantir CEO Alex Karp has been saying for years: “The large language model is essentially a commodity”. Swap Claude out with whatever model. It doesn’t matter. The value will come from the infrastructure (Palantir) that allows users to orchestrate the model. The effectiveness of Palantir’s Maven Smart System will remain unchanged; reinforcing the $PLTR thesis. Model agnostic.

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Palantir CEO Alex Karp on why the model is not the moat. The application layer is: "To make them valuable in an enterprise, like a battlefield, regulated, or manufacturing context, you have to have what's called an application layer." "We have this thing called ontology that now everyone's copying. 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." The tell for any enterprise AI pitch: ask what sits between the model and your data. If the answer is nothing, you are not buying leverage. You are renting a fast way to hand your business to whoever owns the weights. Alex Karp, CEO of Palantir, on CNBC.

Palantir CEO Alex Karp on why the model is not the moat. The application layer is: "To make them valuable in an enterprise, like a battlefield, regulated, or manufacturing context, you have to have what's called an application layer." "We have this thing called ontology that now everyone's copying. 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." The tell for any enterprise AI pitch: ask what sits between the model and your data. If the answer is nothing, you are not buying leverage. You are renting a fast way to hand your business to whoever owns the weights. Alex Karp, CEO of Palantir, on CNBC.

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Every Fortune 500 executive is buying AI subscriptions and calling it a strategy. Palantir CEO Alex Karp has a word for that. Karp: “The general approach of just buying models is going to be essentially self-pleasuring for an enterprise at the cost of the enterprise.” Karp: “You buy some large language model, you party with it basically, and the next day you have a hangover.” The entire corporate world is mispricing the AI transition. They are renting intelligence with no foundation to run it on. A raw model floating in a vacuum hallucinates over your unstructured data, generates the illusion of work, and executes nothing. The party ends. The hangover begins. Nothing changed. Karp identified exactly where the value actually goes. Karp: “All the value in the market is going to go to chips and what we call ontology.” Not the models. Not the subscriptions. Not the chatbot interfaces layered on top of them. The ontology. The precise digital architecture of how an organization actually operates. Its security permissions. Its supply chain physics. It’s operational logic. Karp: “The ontology will allow you to take a large language model and use it, refine it, and then impose it on your enterprise in the logic of your enterprise, in the security model of your enterprise.” When you bind a frontier model to the strict underlying logic of a specific enterprise, something fundamental shifts. It stops generating text. It starts generating action. Karp: “We’re using it on the battlefield, we’re using it to compress margins. We’re making engineers better engineers. We’re making people who are not engineers into engineers using our ontology and a large language model.” The traditional engineering bottleneck does not slow down. It disappears. Karp: “We are sitting on the only thing that actually creates quantifiable, transformational value.” The companies renting models are paying for the feeling of transformation. The companies building ontologies are executing the actual thing. One of them will define the next decade. The other will wake up in 2030 wondering where their market share went. Exactly like a hangover.

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