{"id":553799,"date":"2026-07-22T09:39:20","date_gmt":"2026-07-22T09:39:20","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/553799\/"},"modified":"2026-07-22T09:39:20","modified_gmt":"2026-07-22T09:39:20","slug":"nvidia-backs-hybrid-ai-to-reshape-computer-graphics","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/553799\/","title":{"rendered":"Nvidia backs hybrid AI to reshape computer graphics"},"content":{"rendered":"

AI agents orchestrating classical tools to build controllable, physically accurate virtual worlds<\/p>\n

At Siggraph this week Nvidia set out a vision for the future of computer graphics: neither traditional rendering nor generative AI alone is enough.<\/p>\n

A key theme is the limitation of today\u2019s neural graphics and generative models: while they can create images and videos in seconds from simple prompts, they struggle with fine-grained control and artistic direction. Nvidia\u2019s answer is a hybrid approach \u2014 one in which AI agents orchestrate established graphics and physics tools, using classical techniques as building blocks inside AI-driven workflows.<\/p>\n

Nvidia presented 21 papers of groundbreaking research in this area. \u201cAll are grounded in 3D and physics, and all are directable by creators,\u201d said Rev Lebaredian, VP of physical AI simulation at Nvidia during a press briefing.<\/p>\n

Among the highlights is ArtiFixer<\/a>, an AI model that turns messy real-world 3D captures into clean, complete virtual scenes.<\/p>\n

\u201cThis is a model that can take a rough, very incomplete and noisy 3D scan of the real world and turn it into a clean and complete 3D scene,\u201d said Lebaredian. \u201cIt fixes situations where you have noisy or missing input data when you\u2019re making your Gaussian Splat.\u201d<\/p>\n

ArtiFixer also includes a new method for predicting photoreal global illumination straight from a scene\u2019s geometry \u2014 without tracing a single ray.<\/p>\n


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\n <\/p>\n


\n AI content is independently produced by the AEC Magazine editorial team.
\n HP and NVIDIA supports the creation of this content, but all opinions
\n and coverage remain editorially independent. \n <\/p>\n

<\/p>\n

\"AEC<\/p>\n

\"Find<\/p>\n


\n <\/a><\/p>\n

While ArtiFixer is useful for VFX and games, Nvidia expects major uptake in real-world applications such as architecture, city planning, GIS, and preparing environments to train and test robots.<\/p>\n

To make AI agents practical in production, Nvidia is promoting Model Context Protocol (MCP), which allows agents to work with existing DCC tools including Adobe, Blender, Unreal Engine, SideFX Houdini, Foundry tools and Canva without a web of custom plugins.<\/p>\n

MCP lets AI systems move data between applications, automate tedious tasks, and effectively serve as a natural-language interface for users with little or no 3D experience.<\/p>\n

In Unreal Engine, Nvidia says MCP opens the door to assistants that can reason over scenes, assets and project state.<\/p>\n

In Blender, a lightweight MCP server offered through Blender Lab provides a natural-language interface to Blender\u2019s Python API, documentation and complex setups.<\/p>\n

\"\"Unreal Engine MCP
\nOmniverse, disaggregated: atomic libraries for physical AI<\/p>\n

Nvidia is extending its modular, agent-friendly philosophy to Omniverse<\/a>, its long-running environment for physics-based, USD-centric simulation of the physical world.<\/p>\n

Originally designed as a more monolithic platform, Omniverse has already shifted toward a microservices and cloud-based model to address heavy compute requirements and ease integration.<\/p>\n

Now Nvidia is going further, by expanding its Agent Toolkit with new Omniverse libraries \u2014 a collection of software components that give AI agents tools and skills to add physical AI capabilities to existing applications and prepare 3D content for simulation.<\/p>\n

These Omniverse libraries expose core capabilities \u2013 from RTX rendering to physics and sensor simulation \u2013 in a form that is \u2018agent friendly\u2019, making it straightforward for AI systems to call them, and can be embedded in existing products, not just in Omniverse-branded applications.<\/p>\n

\u201cWe\u2019re providing low-level, core, atomic Lego pieces you can use to assemble simulations of the physical world,\u201d said Lebaredian.<\/p>\n

Nvidia is already showcasing several concrete integrations including PTC Onshape: using Omniverse\u2019s CAD-to-sim-ready asset generation so mechanical designs can be turned into simulation-ready USD assets for robotics and other physical AI use cases.<\/p>\n

\"\"Nvidia Omniverse libraries<\/p>\n

Main Image caption: ArtiFixer turns messy real-world 3D captures into clean, complete virtual scenes.<\/p>\n

Related articles:<\/p>\n

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