NEWS

screenshot 2026 06 01 091715

NVIDIA gives factories a new AI brain

As factories move from isolated automation to plant-wide intelligence, manufacturers need AI systems that can connect live machine signals, quality systems, work instructions and operational alerts into a unified decision layer. 

At GTC Taipei at COMPUTEX, NVIDIA announced the NVIDIA Factory Operations Blueprint (FOX) – a reference design for building an autonomous factory manager agent that continuously monitors and reasons across the real-time data and orchestrates a fleet of speciality agents and machines to quickly resolve issues at scale. 

FOX helps developers build secure, centralised factory manager agents for orchestrating and optimising specialised industrial AI agents for quality control, material transport and worker safety. Built with NVIDIA NemoClawAI-Q Blueprint and NVIDIA Nemotron open models, the blueprint provides a customisable foundation for connecting factory systems, automating model development and running intelligent operations at scale.

The blueprint is optimised to run on NVIDIA DGX Station, the ultimate deskside AI supercomputer companion for factory managers. 

DGX Station is powered by the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip, featuring 20 petaflops of FP4 performance and 748GB of coherent memory, and is capable of running large AI models up to 1 trillion parameters, making it ideal for developing and running powerful AI agents locally. 

The superchip features the NVIDIA Blackwell Ultra GPU connected to a high-performance NVIDIA Grace CPU using the NVIDIA NVLink-C2C interconnect to deliver best-in-class system communication and performance, ideal for lightning-fast interactions between NemoClaw and AI models.

Key capabilities of the FOX blueprint include:

  • Connecting factory systems and agents: FOX integrates with industrial data sources, machines, applications and robot fleets, and can connect to specialised agents from leading software developers through standard application programming interfaces and agent skills.
  • Automating AI model training: Using NVIDIA TAO skills, factory manager agents can automate the full model-training lifecycle – identifying accuracy gaps, sourcing or synthetically generating training data, fine-tuning models and redeploying them into production.
  • Operating intelligent factory workflows: Visual inspection, process compliance and material transport agents can be managed with NVIDIA open models and blueprints, including the NVIDIA Metropolis Blueprint for video search and summarization (VSS). Real-time factory data can also be visualised in an operational twin built with NVIDIA Omniverse libraries.

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