Digital twin simulation for megawatt AI data centers: an innovative AVEVA solution! October 23, 2026. AVEVA boosts efficiency in hyperscale data centers. AVEVA offers an integrated digital twin infrastructure that optimizes power, cooling, and workload efficiency in large-scale computing facilities using virtual environments. This innovative approach is realized through an end-to-end digital twin simulation project, developed in collaboration with Schneider Electric, Nscale, and Start Campus, to model and optimize the physical infrastructure operations of AI data centers. Powerful integration with NVIDIA Omniverse DSX Blueprint. Built on the NVIDIA Omniverse DSX Blueprint, the Immersive Twin platform accelerates deployment in high-density data center ecosystems by combining power, cooling, and electrical models with AI workload requirements. Application at Portugal's SINES Data Campus. This simulation technology is being applied to operations at Nscale's SIN01 data center within the 1.2-gigawatt SINES Data Campus in Portugal. Developed by Start Campus, the facility is designed to support high-capacity AI processing and will house over 66,000 NVIDIA Rubin Graphics Processing Units (GPUs). By creating a unified digital model of such a large deployment, operators can assess the thermal and electrical impacts of high-density computing clusters before physical hardware installations are performed. Operational data integration and simulation mechanics. The digital twin infrastructure leverages the OpenUSD framework to cross-platform connect asset data from AVEVA, ETAP, Schneider Electric, and third-party vendors. The system ingests engineering and operational data to create simulations covering process behavior, electrical distribution, and liquid cooling loops. This capability allows facilities to run precise scenarios for hardware configurations, for example, modeling how an increase in rack power density affects the broader power chain, thereby reducing supply risks and minimizing physical infrastructure changes. Workload efficiency and lifecycle management. For AI cloud platforms like Nscale, aligning physical infrastructure performance with computing requirements directly impacts token generation efficiency. AVEVA's software suite, including CONNECT, PI System, Unified Engineering, and Asset Information Management, provides continuous visibility into asset performance. By visualizing these metrics through NVIDIA Omniverse applications, operators manage the entire lifecycle of an AI factory, transitioning from initial facility design to ongoing operational optimization based on active thermal and electrical loads. AVEVA's edge in a competitive landscape. In the data center infrastructure management (DCIM) and physics-based industrial simulation sectors, AVEVA's software portfolio competes with solutions like Siemens Xcelerator and Bentley Systems' iTwin framework. However, a key competitive differentiator of the AVEVA software ecosystem, working in conjunction with Schneider Electric hardware, is its native integration with the NVIDIA Omniverse DSX Blueprint. This architecture provides GPU-accelerated 3D visualization and simulation based on the OpenUSD standard, enabling simultaneous modeling of both physical cooling loops and specific IT workload outputs, such as AI token processing efficiency. While traditional DCIM platforms often monitor this data as separate silos, AVEVA's integrated approach offers a comprehensive view.

Nvidia chief executive officer Jensen Huang said he told UK-based neocloud Nscale to "work around the clock" to fix problems bringing some of its data centres online. Nscale, which Nvidia backs, has faced delays, equipment failures and power constraints, along with investor pushback over its $30 billion IPO valuation target. Speaking at Nvidia's GTC conference in Berlin, Huang said neoclouds will overcome their troubles because AI computing demand is high. "They just need working capital," he said. Other neoclouds have stumbled recently. Australia's Firmus Grid abandoned a $30 billion IPO, and South Korea's Elice had a difficult trading debut. Nvidia also unveiled the DSX Pod, a container-sized mini data centre that arrives with hardware, cabling and plumbing installed and tested.

Microsoft boss warns of AI trust crisis as UK workers lag behind bosses. Tech Reporter Microsoft chief executive Satya Nadella has warned that increasingly powerful AI systems are becoming less trustworthy, as new research exposes a widening confidence gap between UK bosses and their employees. Speaking at Microsoft's Frontier Tour in London on Wednesday, Nadella urged businesses to embrace AI while retaining human oversight, warning that the technology's growing capabilities bring new risks. "Our scaling laws are producing even more powerful models that are less and less trustworthy", he said, arguing that businesses must treat AI systems as "new forms of insiders" and build safeguards around them. His warning comes as Microsoft research revealed that 84 per cent of UK business leaders believe Britain can become a world-leading AI economy within five years, compared with just 41 per cent of employees. The findings suggest a disconnect between executives pushing ahead with AI adoption and workers concerned about what the technology means for their jobs. Stay in the know Three daily briefings with the key market moves and top business and political stories. Employees cited fears over job security and fewer opportunities for younger workers among their concerns. Nadella said businesses must ensure AI strengthens rather than undermines employees' ability to work. "How do you put the human in the loop?" he asked. "How do you really ensure that, ultimately, that sense of empowerment is not lost?" He also warned that businesses risk losing control of valuable knowledge generated through AI systems, urging organisations to retain ownership of both their employees' expertise and the information produced by AI. Britain's AI ambitions face a reality check. The warnings come as the government seeks to position Britain as a global AI powerhouse, with billions pledged towards computing infrastructure and greater adoption across public services. But questions still remain over whether that investment will translate into higher productivity, particularly as businesses grapple with the cost of deploying AI systems and managing their risks. Microsoft itself has committed billions to UK infrastructure, although the country's AI expansion is increasingly constrained by electricity shortages and lengthy grid connection delays. Earlier this week, Microsoft withdrew from a planned £2bn AI data centre project in Essex after developer Nscale faced delays securing sufficient power until the 2030s. The setback highlighted the difficulties facing even the world's largest technology companies as they race to expand Britain's computing capacity. Meanwhile, Nadella highlighted Yorkshire Ambulance Service's use of Copilot to reduce administrative work in the NHS, ahead of plans to make the technology available to as many as 500,000 clinicians and support staff. But expanding access to AI tools is not the same as demonstrating sustained improvements in productivity or patient care. Microsoft's UK and Ireland chief executive Darren Hardman said businesses needed to establish clear limits on what AI systems could access and do. "You can set clear boundaries on the data AI can access. And the actions it can take. With human approval where it matters" he said.