
DEVELOPER . NVIDIA . COM {
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Title:
PhysicsNeMo | NVIDIA Developer
Description:
NVIDIA PhysicsNeMo is an open-source python framework for building, training, and fine-tuning physics AI models at scale.
Website Age:
32 years and 2 months (reg. 1993-04-20).
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Custom-built
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💥 Very Strong Traffic: 200k - 500k visitors per month
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How Does Developer.nvidia.com Make Money? {💸}
Display Ads {🎯}
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$3,210 per month
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Keywords {🔍}
nvidia, physicsnemo, models, training, physics, weather, build, engineering, digital, download, scale, developers, climate, model, physicsml, resources, framework, neural, applications, documentation, explore, opensource, data, software, omniverse, architectures, development, started, develop, simulations, twin, read, earth, cloud, reference, customize, twins, accelerate, cae, nim, kit, utilities, surrogate, enabling, realtime, predictions, operators, gnns, computational, fluid,
Topics {✒️}
developing physics-ml models ai-accelerated digital twins physics-informed neural networks nvidia accelerates weather combine physics-driven causality purely physics-driven models user-comprehensible error messages training physics-ml models enabling real-time predictions generate higher-fidelity data open-source software open-source python framework nvidia physicsnemo framework climate ecosystem high-quality software physics-ml models home nvidia physicsnemo nvidia physicsnemo supports nvidia physicsnemo container nvidia nim™ microservice features latest news nvidia ai enterprise dli teaching kit accelerate physics-ml generative ai models data-driven architectures includes training recipes art pretrained models earth-2 weather analytics enhance engineering simulations enterprise-grade development nvidia ngc™ catalog gpu cloud resources multiple physics domains understand error rates nvidia physicsnemo nvidia physicsnemo digital twins train ai models diffusion models trained industrial scale problems real time reference samples show simple python apis optimize research applications physics-based fourier feature networks enterprise-grade support graph neural networks physics-ml
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