Observed Signal · Oct 21, 2026 · Market Signal · Source: Nscale · Impact: 2/5
Nscale is developing digital twins to scale AI infrastructure
Nscale is exploring how simulation can inform the way it designs, deploys, and operates AI data centers with NVIDIA Omniverse Libraries and NVIDIA DSX Sim.
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Recent verified developments and strategic activity across this market segment.
Switch Unveils Advanced AI Factories with NVIDIA Integration
Switch announced the integration of the NVIDIA Omniverse DSX Blueprint into its EVO AI Factory architecture and the LDC EVO operating system. Using NVIDIA Omniverse libraries and OpenUSD, LDC EVO provides a live, physics-accurate 3D digital twin and automation workflows to model, simulate, and operate AI factory facilities in near real-time. The EVO AI Factory supports high-density NVIDIA accelerated computing on Dell PowerEdge servers and has been used to validate configurations such as NVIDIA Grace Blackwell on Dell hardware. Switch cites collaboration with ecosystem partners (including NVIDIA, Dassault Systèmes, Cadence, ETAP, Schneider Electric, SUSE, Dell Technologies, Oxide Computer Company and Procore) and will showcase the EVO AI Factory at NVIDIA GTC 2026 in the DSX AI Infrastructure Pavilion, Booth #91.
Netris Integrates with NVIDIA DSX Air for Enhanced AI Simulation
Netris announced integration and support for NVIDIA DSX Air, NVIDIA’s infrastructure simulation platform introduced at GTC 2026. The integration lets Netris deploy its NAAM (Network Automation, Abstraction, and Multi‑Tenancy) controller inside DSX Air to simulate, validate and iterate full‑fidelity, multi‑tenant AI infrastructure — including Ethernet (NVIDIA Spectrum‑X), NVL72, NVIDIA BlueField DPUs, and virtual/edge networking — before hardware delivery. The combined environment is intended to accelerate ISV integration, pre‑deployment validation (day 0), go‑live (day 1) and ongoing change management (day 2), reduce deployment risk, and enable operators to enforce hardware‑level isolation and dynamically reallocate GPU capacity across tenants.
Nvidia on Physical AI, Jetson, Simulation, and Agents
Nvidia VP and GM Deepu Talla discusses the company’s platform for physical AI and robotics, describing a three‑computer model: data‑center training (GB300, Vera Rubin), simulation (RTX Pro 6000, Omniverse) and edge runtime (Jetson Thor, Orin). Talla says roughly 2.5 million developers and over 10,000 companies build on Jetson today, while the industry ships about one to two million robots annually against an opportunity he pegs at tens of billions. Key themes include the rise of vision–language–action models and world models, the closed sim‑to‑real gap aided by Nvidia’s Omniverse and the open‑sourced Newton physics engine (with Disney Research and Google DeepMind), hybrid edge‑cloud architectures, agentic orchestration for fleets (Nvidia Mega blueprint), and the current industry focus on training and simulation before large‑scale edge deployment.
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