AI Agent · Nvidia · Agentic AI · NVIDIA Blog
Industrial Software Leaders Build Secure, Autonomous AI Engineers With NVIDIA NemoClaw
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Accelerated computing has revolutionized industrial engineering, compressing simulation times from weeks to hours.
Key facts
- P-1 AI is building Archie, an AI mechanical and electrical engineer that already works with data center cooling and critical power systems, and will soon work for automotive, aerospace and national
- At GTC Taipei at COMPUTEX, NVIDIA and more than a dozen engineering software providers are showcasing how autonomous AI agents automate this entire workflow
- Users can easily deploy NemoClaw from NVIDIA DGX Spark personal AI supercomputers, as well as through enterprise data centers and cloud service providers
- Industrial software leaders are building AI engineers for computer-aided engineering (CAE) and electronic design automation (EDA) use cases across automotive, aerospace, semiconductors
Summary
Today’s remaining challenges sit in the end-to-end workflow surrounding the simulations: computer-aided design, meshing, simulation setup and debugging, as well as post-processing and generating summary reports of these processes. At GTC Taipei at COMPUTEX, NVIDIA and more than a dozen engineering software providers are showcasing how autonomous AI agents automate this entire workflow. These AI engineers are based on NVIDIA NemoClaw, an open blueprint for building specialized, long-running agents with a secure runtime and frontier models. NemoClaw includes a choice of harness, meaning it can be integrated with various orchestration frameworks enterprises use to deploy and coordinate agents, such as OpenClaw and Hermes, as well as a model router and NVIDIA NeMo libraries for customization.