Finance Intern - SEC Reporting

Vertiv Holdings Co. and NVIDIA introduce AI Factory approach using NVIDIA DSX and Vertiv factory-built infrastructure. Published on 10/21/2026 at 08:50 am EDT S&P Capital IQ Vertiv Holdings Co. and NVIDIA introduced an AI factory approach that combines rapid configuration and virtual validation of pre-engineered reference architectures with factory-built deployment. The approach is designed to move AI factories from project kickoff to productive capacity faster and, under defined assumptions, generate up to 30% more cumulative token output within the first 12 months with the same installed capacity. The Vertiv and NVIDIA approach starts instead with pre-engineered AI factory reference architectures that can be rapidly configured to customer and site requirements, virtually validated before deployment, then translated into factory-built infrastructure. Teams can start with pre-engineered AI factory reference designs and rapidly configure them for specific compute, power, cooling and facility requirements in a shared virtual environment. The approach combines the NVIDIA Vera Rubin DSX AI Factory reference design and NVIDIA Omniverse DSX Blueprint, with Vertiv SimReady power and cooling assets, integrated with Dassault Systèmes' 3DEXPERIENCE agentic platform. Rather than developing an integrated infrastructure design from scratch, teams can configure and virtually validate proven reference designs against project requirements, interfaces and constraints. In the modeled scenario, this reduces the time from requirements to a configured and validated AI factory solution from approximately 30 days to three days, a 10x improvement. Vertiv is also contributing SimReady OpenUSD assets of its power and cooling equipment to SimReady Central Library on Hugging Face. The library helps engineering teams discover and reuse validated equipment assets in AI factory digital twins, reducing asset preparation and helping teams evaluate infrastructure options during design. Once the AI factory configuration is validated, Vertiv prefabricated solutions shift more assembly, integration and testing into the factory before equipment reaches the site. These solutions include Vertiv? OneCore, a hybrid-built data center solution that integrates critical power, thermal management and supporting infrastructure, and Vertiv? SmartRun, a prefabricated overhead infrastructure system for high-density power distribution, liquid cooling, networking and containment. By moving more infrastructure work off-site, teams can reduce field complexity and on-site integration requirements. In the modeled scenario, the factory-built approach reduces the infrastructure deployment period from approximately 90 days to 45 days, a reduction of up to 50%. Combined with the faster configuration and validation enabled by pre-engineered reference designs, the modeled approach reduces these stages from approximately 120 days to 48 days. That can make productive AI capacity available about 10 weeks sooner, generating up to 30% more cumulative token output within 12 months of project kickoff with the same installed capacity. (C) S&P Capital IQ - 2026

Vertiv and NVIDIA have introduced an AI factory approach that pairs pre-engineered reference designs with factory-built infrastructure. Announced at NVIDIA GTC Berlin, it aims to bring AI capacity online sooner. In modelled scenarios, it yields up to 30% more cumulative token output in the first 12 months at the same installed capacity. The modelled approach cuts configuration and validation from about 30 days to three, and deployment from about 90 days to 45. Together, that trims these stages from roughly 120 days to 48, making capacity available about 10 weeks sooner. Polar Data Centers is using the factory-built model for the first 41 MW phase of its AI data center at Herøya, Norway, which is scalable to 100 MW.

European partners adopt NVIDIA DSX to build more efficient AI factories using digital twins. 15 hours ago NVIDIA has announced that European partners are adopting its DSX AI Factory Platform to build AI factories that use less water and less power for the same output. The news came at GTC Berlin on 21 October 2026. Cooling and power. NVIDIA's DSX reference designs combine closed-loop liquid cooling with outdoor dry coolers, which reject heat without evaporating water. The company says this can bring facility cooling water use close to zero. At 2 GW scale, it estimates savings of 54 million litres of water per day compared with cooling-tower systems, roughly the daily use of 180,000 households. Vera Rubin infrastructure supports 100% liquid cooling with coolant temperatures up to 45°C, though local climate determines whether supplemental mechanical cooling is needed during peak heat. On power, DSX MaxLPS allocates power dynamically within a facility's fixed budget. NVIDIA says it can generate the same number of tokens with up to 30% less power. Lambda tested it on HGX B200 systems and reported 24% more cluster token throughput and 19% more GPU capacity within a fixed power budget. Nscale tested it on four GB300 NVL72 racks in Iceland and reported 49% higher inference throughput and 37% more managed GPU capacity within the same 264 kW provisioned budget. Digital twins and simulation. The industrial software angle centres on DSX Sim and the new SimReady Central library on Hugging Face, which holds validated power and cooling equipment assets from partners such as Vertiv. * Nscale is using DSX Sim to build digital twins of its Portugal and Iceland facilities, testing power, cooling and infrastructure configurations before deployment. * Siemens is using DSX Sim to simulate power, cooling and acoustics. * Dassault Systèmes and Vertiv are developing digital twin models of Vertiv's OneCore infrastructure using model-based systems engineering. * PTC is working on creating simulation-ready assets from computer-aided design files. * Schneider Electric is working with AVEVA on digital twins spanning design, construction and operations. * ABB is developing SimReady assets for evaluating source-to-rack power architectures and advancing 800 VDC development. * Procore has integrated its construction management platform with DSX Sim. Grid flexibility and operations. DSX Flex lets AI factories adjust workload power draw in response to utility needs, demand-response events and energy prices. In an early trial involving Emerald AI, EPRI, Nebius, the UK's National Grid and NVIDIA, a Blackwell Ultra cluster reduced its power draw by up to 40% during simulated grid events while critical workloads kept running. For operations, NVIDIA is releasing three new open-source DSX OS components in developer preview: Config Manager for network configuration, Rack Management Service for power, inventory, firmware and switches, and Cluster Readiness Engine, which validates GPU clusters and isolates node failures. Power and cooling partners. Trane Technologies and Eaton built an integrated grid-to-chip design for the Vera Rubin DSX AI Factory Reference Design, and Trane published seven thermal management reference designs, including three 250 MW DSX-based cooling designs. Under the DSX Ready programme, LiquidStack GigaModular and Vertiv's 2.3 MW CoolChip are qualified coolant distribution units, and Hitachi Energy's battery energy storage system earned DSX Ready BESS qualification. GE Vernova, Hitachi Energy and Siemens Energy are working with NVIDIA on energy-system and grid planning. Leadership comment. Warren Barkley, VP of DSX product management at NVIDIA, said, "Europe's technology leadership depends on how efficiently we turn power and infrastructure into intelligence." Josh Payne, founder and CEO of Nscale, said, "Europe's AI ambitions demand that we make every megawatt count."