https://build.nvidia.com/nvidia/genai-3d-guided
https://github.com/NVIDIA-AI-Blueprints/3d-guided-genai-rtx
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Search results for: “nvidia”
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Vulkan Gaussian Splatting – Real-Time GPU-Accelerated Gaussian Splatting with NVIDIA DesignWorks Sample vk_gaussian_splatting
https://github.com/nvpro-samples/vk_gaussian_splatting
vk_gaussian_splatting is a new Vulkan-based sample that demonstrates real-time Gaussian splatting, a cutting-edge volume rendering technique that enables highly efficient representations of radiance fields. It is the latest addition to the NVIDIA DesignWorks Samples.
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NVidia Physical AI – Collection of commercial-grade datasets for physical AI developers
https://huggingface.co/collections/nvidia/physical-ai-67c643edbb024053dcbcd6d8
🔹 15TB of high-quality, standardized synthetic data
🔹 320,000+ trajectories for robotics training
🔹 1,000+ OpenUSD assets, including a SimReady collection -
Nvidia CUDA Toolkit – a development environment for creating high-performance, GPU-accelerated applications
https://developer.nvidia.com/cuda-toolkit
With it, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library.
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Nvidia unveils $3,000 desktop AI computer for home LLM researchers
https://arstechnica.com/ai/2025/01/nvidias-first-desktop-pc-can-run-local-ai-models-for-3000
https://www.nvidia.com/en-us/project-digits
Some smaller open-weights AI language models (such as Llama 3.1 70B, with 70 billion parameters) and various AI image-synthesis models like Flux.1 dev (12 billion parameters) could probably run comfortably on Project DIGITS, but larger open models like Llama 3.1 405B, with 405 billion parameters, may not. Given the recent explosion of smaller AI models, a creative developer could likely run quite a few interesting models on the unit.
DIGITS’ 128GB of unified RAM is notable because a high-power consumer GPU like the RTX 4090 has only 24GB of VRAM. Memory serves as a hard limit on AI model parameter size, and more memory makes room for running larger local AI models. -
NVidia – High-Fidelity 3D Mesh Generation at Scale with Meshtron
https://developer.nvidia.com/blog/high-fidelity-3d-mesh-generation-at-scale-with-meshtron/
Meshtron provides a simple and scalable, data-driven solution for generating intricate, artist-like meshes of up to 64K faces at 1024-level coordinate resolution. This is over an order of magnitude higher face count and 8x higher coordinate resolution compared to existing methods.
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NVIDIA GauGAN360 – AI driven latlong HDRI creation tool
https://blogs.nvidia.com/blog/2022/08/09/neural-graphics-sdk-metaverse-content/
Unfortunately, png output only at the moment:
http://imaginaire.cc/gaugan360/
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NVidia – NeRF AI Recreates Unconstrained Scene Views From Photos in 2 seconds
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