“Palantir is a great company,” says Europe’s defence Commissioner. We refused to work in Russia and China, even though that cost us money. We went into Kyiv in May 2022 and stayed. We did both because of what we believe, not what we could sell. The engineers that do this work are European. They are building for their own countries. I am grateful to the Commissioner for his praise, and sorry as always to everyone whose afternoon this has ruined.

Palantir CEO Alex Karp on what model companies are really asking for when they call for regulation and why they will be nationalized. “It's a weird twist. They're asking for societal regulation to get out of the first line of defense, which is if you build a technology that can destroy 10% of the of the world, that has civil and criminal liability attached to it.” “The only way to deal with this kind of liability is to go to the government and say nationalize us, please.” "Another problem we have is seemingly everyone who understands this is on some payroll."

Apache Iceberg is now generally available in Palantir AIP. Sovereignty at all levels of the stack. Customers can now use an open, interoperable table format alongside the capabilities required to operate critical data: pipeline building, governance, security, lineage, and Ontology. The full open standard, not some Palantir variant of it...... THE FULL OPEN STANDARD. Managed Iceberg tables and Palantir’s Iceberg REST catalog are GA on standard Foundry enterprise environments. Tables can be stored in Palantir managed storage or a customer-provided bucket. This means one bucket (yours, ours or theirs), one iceberg file, Palantir and your other Iceberg enabled systems working on the same physical file. Zero Data Copy. Teams can build pipelines, perform row-level updates and changelog processing, create Ontology object types backed by Iceberg, analyze tables in with SQL, python or connect external tools directly to the catalog. Completely open. Adopting and supporting an open standard means more than consuming it. Our FDEs have also contributed back to the Iceberg standard to enable features we had built in Foundry but now is available as part of the standard for all, just a few examples: - Table encryption in iceberg-rust github.com/apache/iceberg-ru… - Incremental append scans, schema evolution, and other Iceberg features in Polars github.com/pola-rs/polars/pu… - Incremental append scans and other contributions to PyIceberg github.com/apache/iceberg-py… More about some of the new value add: palantir.com/docs/foundry/an… and palantir.com/docs/foundry/ic…

I’ve worked on a number of risk and compliance implementations across financial services, food safety, automotive, aviation, oil and gas, heavy construction, and healthcare amongst others. I think it’s important to understand how they work, or not, a level down as they are referenced to justify current theatrical efforts. Risk is an excruciatingly difficult thing to manage. It cannot be done with theatre and hypotheticals. Insurance is a ~$10 trillion industry for a reason. The advocates for this theatre in AI are failing any objective evaluation in their business practices and culture today, perhaps because they are monetizing the actual levered methods they could edit to control risk with their current business practices, so they have to concoct new methods that ignore the low hanging fruit. You don’t get to choose convenient areas of risk if you have a rigorous safety culture. As an outsider it seems the advocates of risk reduction are choosing very convenient definitions of risk (and benefits), pushing them to be undefined and in the future. In the present, they are struggling to deliver two 9’s of uptime. They have paid billions of dollars in fines for the compromised integrity of their data supply chains already. They have been permissive in their enablement of distillation attacks through ineffective KYC controls. They have instituted paper thin controls in their offensive cyber testing environments. They have regularly been at odds with one time partners when they launch competitive products. That is clearly not a culture that takes the stairs one step at a time with a hand on the railing. The necessary but insufficient reason to rely on Sovereign AI is generalized controls will not protect individual use. Of course the better a system is controlled, the more valuable it is as well. Patterns that are consistent across all of the above industries: - Safety is cultural. Oil and gas and mining companies who have visceral understanding of the risk of the environments they operate in will open every meeting with a safety moment where a participant will share an anecdote like talking about their child falling on their bike. They will enforce norms like you must take the stairs one at a time and hold the railing with one hand at all times. They install cultural norms because they have learned that efficacious controls require consistency across all business practices, not convenient ones. - Risk outpaces controls. Risk is an adaptive adversary; either literally with the ingenuity of the criminal, or as a function of the entropy in any complex physical system. - Every general control trends to a 99%+ false positive rate. The simple way to think about it is static logic adjudicating a dynamic world means even hyper-tailored controls drift in their impact over time. Think how many times you have pulled from a TSA line for secondary screening. - General purpose controls that are at odds with environment specific dynamics will create substantial friction and that friction will lead to business practices that work around the control, leaving them uncontrolled. Think refusals for doctors doing biological research. - Compliance programs focus on what is knowable. This means they crave control of inputsand not just outputs. The tightness of the causal link between input controls and real world outcomes defines the efficacy versus cost of the program. - Provenance is a critical pillar in domains like financial services, aviation, and manufacturing. A bank has to be able to substantiate Source of Wealth and Source of Funds. An airplane has to have serialized tracking of a part in order to trace potential causes of an issue. A manufacturing company has to assert that none of its suppliers has used sweat shop labor. - Compliance is organizationally exhausting. Installing a process that is hyper attenuated to the thousandth straight false positive is a very difficult systems design challenge. - Human power dynamics introduce substantial entropy. The Korean Pilot case study extrapolates across many domains. Relative talent, power, and understanding have to be modeled both cooperatively and competitively which is hard. Why this matters for AI: - While the intention may be to control unsubstantiated future risk, any actual implementation of a program is going to be limited by what we can actually control for. The more this relies on creativity of potential risks, the wider the collateral impact on benign use will be. If it is untethered from what is measured, it will become a projection of a belief system that is unfalsifiable. Like wiping down your groceries during Covid. - Risk management will create safety theatre not safety outcomes the more it is done at a general level. The application of the technology in specifically controlled contexts will be dramatically more effective, measured only by success in controlling risks, than any generalized logic. There is both enormous deadweight loss in universal logic applied to specific outputs, and more importantly if you are singularly focused on risk reduction, enormous false positives that lead to exhaustion that lead to knowable bad outcomes. - The natural consequence of this for any motivated and empowered overseer is that the cost of controls will also move to the edge, i.e. specific customer use. - Provenance. The supply chain for AI is the data and RL environments. Opening the kimono and establishing rigorous controls on what inputs are used in models is the obvious place to start. I suspect this is the last place those advocating for controls will want to start, but it seems like the place with the highest impact with most control for a motivated overseer. - Banks have very strict KYC controls, weapons are subject to ITAR. If you were a startup bank that was facilitating terrorist financing or sanctions evasions before you could mature your compliance program, you would be sent to jail. There seems to be low hanging fruit if you are optimizing for risk reduction and I’m curious why programs that aren’t sufficiently onerous for the stated risk haven’t been implemented already. - The asymmetry in expertise will lead to psychological pressures, as this whole fiasco and the herding behind it is already clearly demonstrating. Let’s spend our time arguing about efficacy not “should or should not.”

On the 25th anniversary of 9/11, Palantir honors the nearly 3,000 lives lost, the families who carry their memory, and the heroes who ran toward danger. These heroes answered the call that day—and continue answering it by keeping America safe and strong today. We are grateful to all those who have defended our country and protected our freedoms, both then and now. We will never forget.

From wafer to first token, every step matters. NVIDIA’s @alexneefus shares how NVIDIA and @PalantirTech are using open models to help supply chain teams identify disruptions earlier, evaluate scenarios faster, & make more informed decisions, with human expertise at the center.

“Dr. Karp talks about chips and ontology. This is ontology for chips.” At AIPCon 11, @nvidia reveals how it is partnering with Palantir to build and run their supply chain on Palantir.

“The sheer scale of our supply chain, the fact that we're on an exponential growth curve, makes solving this problem and calculating this problem nearly intractable.” “That's what we worked with Palantir to build, and we called it Command Center.”

30B post-trained on the Ontology loop beat 550B Specialization > scale “Supply chains are the operating system of the physical economy, and AI factories are among the most complex systems ever built.” “NVIDIA has arguably the most valuable, intricate, and complex supply chain in the world.” “This doesn’t mean the smaller model is more capable overall. Its gains are concentrated in the domain it was post-trained on.”

The model is not the system. AIP Evolve optimizes production AI across models, prompts, context, and logic — reducing cost without surrendering control. Change the model. Change the prompt. Change the logic. Own the system.

Vulcan puts CAD in the Ontology Measure, Annotate, Slice, Act. Engineering geometry becomes operational data palantir.com/docs/foundry/an…

"We're using 100% of the technology, because it's been custom built to exactly what we need." For over 100 years, @GoodfellowBros has self-performed some of the most demanding heavy civil work in the West, such as grading, structural concrete, and underground utilities, from the mainland to the middle of the Pacific. Now they're building their next century on sovereign ground with Palantir: a platform built from the ground up, owned outright, and made to run at 100% capacity.

Night shift

“Open Weight model adoption is accelerating.” “In short, Palantir continues to lead the charge in putting AI in production for Western Institutions, without any allegiance to a particular LLM. As different models leapfrog one another in performance, Palantir's model-agnostic platform helps organizations capitalize on advancing model capabilities while avoiding the risk of LLM vendor lock-in.” “While that shouldn't be a surprise, we are intrigued by how many leading brands are already seeing notable benefits from leveraging open weight models (it's not just experimental). In this note, we review some interesting data points that have surfaced over the past few days, as well as why we believe Palantir remains well-positioned to capitalize on this theme.” “Palantir has positioned itself as a model-agnostic central operating system. CEO Dr. Alex Karp has been one of the most outspoken figures in tech in terms of warning about rising AI costs, the potential dangers of exposing valuable enterprise data to LLMs, etc.; that position is seemingly proving prescient.”

"Lexus/Nexus"... 🤨

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It was great to have @Raekwon at our office again. Congratulations to the Wu-Tang Clan on their farewell tour. Never forget your OGs.