AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。
Nvidia and Palantir announced on Thursday that they’re working together to bring “sovereign AI to critical supply chains,” kicking off initially with Nvidia’s own sprawling supply chain. The news builds on a partnership that kicked off last October, when the duo said they would combine Nvidia’s AI computing and models with Palantir’s software to help companies use AI to make complex operational decisions. Then in June, they expanded that effort into sovereign AI, allowing organizations to run and customize Nvidia’s AI models inside tightly controlled environments while keeping sensitive data and model weights under their own control. Now, they are taking things a step further by applying that technology inside Nvidia itself. A proving ground for sovereign AI The companies have fine-tuned Nvidia’s 30-billion-parameter Nemotron 3.5 Lightning model on decisions made by Nvidia’s supply-chain operations team. Palantir’s Foundry and Artificial Intelligence Platform (AIP) platform bring together the data behind those decisions, while its Ontology acts as a live map connecting components, factories, capacity and production commitments. Nvidia’s cuOpt software, meanwhile, works out how scarce parts could be distributed, with Nemotron weighing the wider context and recommending what planners should do. They then plan to “extend the learnings from Nvidia’s deployment” to companies in other sectors, including manufacturing, energy, healthcare, automotive and aerospace. Palantir’s own customers will be able to build versions tailored to their own supply chains by training Nemotron on their proprietary data using Foundry and AIP, then run the resulting system on-premises or through cloud and colocation providers. So, in effect, Nvidia and Palantir are putting the sovereign AI partnership they outlined in June into practice inside Nvidia, while using that deployment as a proving ground for an architecture other companies can adapt to their own use-cases. Nvidia as a test case As the world’s most valuable public company at $4 trillion market cap, there’s good reason for Nvidia to start close to home. Its supply chain spans millions of parts, thousands of suppliers and a global network of manufacturing partners, with the company saying a single Vera Rubin rack contains some 1.3 million parts. Those components have to arrive in the right place at the right time: if one part is missing, assembly can stall while everything that arrived earlier sits waiting. “Supply chains are the operating system of the physical economy, and AI factories are among the most complex systems ever built. Jensen Huang And that complexity is what Nvidia founder and CEO Jensen Huang says makes supply chains a natural target for the technology. From chips and memory to manufacturing, networking, power and cooling, he argues that building modern AI systems increasingly depends on coordinating an enormous web of companies and components. “Supply chains are the operating system of the physical economy, and AI factories are among the most complex systems ever built,” Huang says in a statement. Palantir co-founder and CEO Alex Karp goes further, arguing that Nvidia’s operations provide an unusually demanding environment in which to put the companies’ approach to the test. “Nvidia has arguably the most valuable, intricate, and complex supply chain in the world.” “Nvidia has arguably the most valuable, intricate, and complex supply chain in the world,” Karp adds in a separate statement. Open for business The open-model piece is central to what Nvidia and Palantir are pitching. Because Nemotron is open-weight, companies can fine-tune it on their own operational data and keep the resulting model, data and inference inside their own environment. That is the practical appeal of “sovereign AI” here. It also fits Nvidia’s broader direction. Last week, Nvidia agreed to acquire Hugging Face, one of the main hubs for open models. Huang said at the time that Hugging Face would remain open and hardware-neutral, while Nvidia has increasingly cast open models as a way for developers and enterprises to retain control over how they build and deploy AI. The supply-chain experiment gives that argument a useful proof point. Nvidia and Palantir fine-tuned the 30B Nemotron 3.5 Lightning on historical allocation decisions, then tested it against the much larger 550B Nemotron 3 Ultra. Lightning scored 86.7% accuracy, versus 55.5% for Ultra — despite Ultra having roughly 18 times as many parameters. The caveat is key: this was Nvidia and Palantir’s own benchmark, built around a narrow supply-chain task. Even the companies say the smaller model was better only in the domain it had been trained for. That, though, is precisely the playbook they want other companies to copy: start with an open model, teach it your own business, and keep the result under your control. The post “AI factories are among the most complex systems ever built”: Nvidia and Palantir turn Nvidia’s supply chain into a proving ground for sovereign AI appeared first on The New Stack.