NVIDIA Unveils AI Blueprint for 3D Object Generation, Revolutionizing Scene Creation for Artists

Scene It to Believe It: Populate 3D Worlds Quickly With NVIDIA AI Blueprints

The new NVIDIA AI Blueprint for 3D object generation simplifies scene creation, and the new Microsoft TRELLIS NVIDIA NIM microservice accelerates performance by 20%, all powered by NVIDIA RTX. 3D artists are constantly prototyping. In traditional workflows, modelers must build placeholder, low-fidelity assets to populate 3D scenes, tinkering and adjusting the core elements until they're in place. From there, visuals can be refined, detailed and finalized. Prototyping is time consuming and often comprises throwaway work, forcing artists to spend time on tedious modeling rather than on creative exploration. Generative AI assists artists by expediting intermediate tasks like suggesting and generating draft objects to prototype a scene. But it can be technically challenging to connect multiple AI models to unleash these accelerated workflows. NVIDIA AI Blueprints help address this challenge by providing sample workflows so users can skip the hypertechnical stages and quickly benefit from advanced generative AI techniques. Plus, AI Blueprints can be tailored for each user's particular needs. NVIDIA today released the AI Blueprint for 3D object generation -- a workflow that lets 3D artists create up to 20 3D objects to prototype a scene from a simple text prompt. In addition, the new Microsoft TRELLIS NVIDIA NIM microservice works within the AI Blueprint for 3D object generation to generate high-quality 3D assets 20% faster than with the native model. Generate, Prototype, Repeat 3D projects start with an idea's genesis, followed by the careful consideration of visual details such as themes, locations, decors, colors, textures and more. Even after populating a scene with assets, artists must review and edit individual and collective visuals multiple times. The new NVIDIA AI Blueprint for 3D object generation gives users a pipeline to automate the prototyping process. Start by providing an artistic idea through a prompt, and the blueprint's built-in large language model (LLM) will brainstorm 20 possible objects to include in the scene. The Llama 3.1 8B NVIDIA NIM microservice accelerates the results. NVIDIA SANA -- a text-to-image framework that quickly synthesizes high-resolution images -- generates previews to showcase the potential objects. Each object can be regenerated, modified or discarded, giving the artist complete creative control. Then, artists can convert each object from a high-quality preview into a ready-to-use 3D model with the new Microsoft TRELLIS NVIDIA NIM microservice, which simplifies deploying this state-of-the-art model and accelerates it by 20%. In addition, the collection of up to 20 3D assets are primed for instant use or further refinement in Blender, an open-source 3D platform, which the AI Blueprint for 3D object generation automatically exports to. Artists can also export to other popular 3D applications. Setting up this series of workflows would normally take time and require technical knowledge, as well as experimentation with different models to select a suitable pipeline. NVIDIA AI Blueprints ease the process of getting started by preselecting proven workflows, simplifying deployment on NVIDIA GeForce RTX and RTX PRO GPUs by packaging the required components together. Microsoft TRELLIS Microsoft TRELLIS, a cutting-edge 3D asset generation model developed by Microsoft Research, is capable of generating richly detailed 3D assets, complete with complex shapes and textures, from text or image prompts. It's especially useful for game design, architecture and digital media production, as it can produce preview-ready materials and product-level objects. High-quality text-to-image 3D models available for consumer use tend to be difficult to set up. The Microsoft TRELLIS NIM microservice seamlessly integrates within the NVIDIA AI Blueprint for 3D object generation, saving considerable time for artists. When used in the blueprint, the Microsoft TRELLIS NIM microservice is 20% faster with PyTorch optimizations that unlock even quicker iteration. The average time saved is approximately 6 seconds per object generated on an NVIDIA GeForce RTX 5090 GPU. For 3D freelancers generating hundreds of assets across dozens of scenes, these are extraordinary savings. The Microsoft TRELLIS NIM microservice is supported on all NVIDIA GeForce RTX 50 Series and 40 Series GPUs -- desktop and laptop -- with 16GB or more. Ready, Aim, Deploy Get started with the NVIDIA AI Blueprint for 3D object generation by following these instructions: Detailed instructions and necessary files can be found on NVIDIA Build and GitHub. Explore a variety of expertly curated AI Blueprints, including the AI Blueprint for 3D-guided generative AI, and NIM microservices today. Plus, attendees of the IFA consumer electronics and home appliances trade show can attend a session on "How AI Is Changing Content Creation" on Saturday, Sept. 6, at 2pm CET to hear Sean Kilbride, director of professional visualization technical marketing at NVIDIA, and other panelists discuss how creators are integrating AI into their workflows to unlock new creative approaches, speed up production and push the boundaries of content creation. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, productivity apps and more on AI PCs and workstations. Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X -- and stay informed by subscribing to the RTX AI PC newsletter. Join NVIDIA's Discord server to connect with community developers and AI enthusiasts for discussions on what's possible with RTX AI. Follow NVIDIA Workstation on LinkedIn and X. See notice regarding software product information.

Nvidia reckons its new AI pipeline is the end of tedious prototyping for 3D artists

The new AI Blueprint can populate a scene from a simple text prompt. Prototyping can be a time-consuming process for 3D artists and developers, requiring hours of manual tweaking on models that might only end up getting scrapped. Nvidia reckons its latest AI Blueprint can help make that a thing of the past by applying generative AI to 3D modelling. At the electronics trade show IFA Berlin today, the maker of many of the best graphics cards, launched its new AI Blueprint for 3D Object Generation. The pipeline allows artists to use text prompts to populate 3D scenes with models that can then be modified in Blender, one of the best 3D modelling software programs, if needed. Nvidia notes that in traditional workflows, 3D artists create placeholder assets to populate prototypes of 3D scenes, adjusting core elements before visuals can be refined and finalised. A lot this is throwaway work, it says, and artists lose time on tedious modeling when they could be engaged in creative exploration. The new customisable Nvidia AI Blueprint for 3D object generation aims to speed up the process by providing a simple pipeline through which artists can automate the prototyping process using text prompts. The artist can start by providing an idea through a prompt. The blueprint's built-in large language model will then generate 20 possible objects to include in the scene with the Llama 3.1 8B NVIDIA NIM microservice accelerating the results. NVIDIA SANA, a text-to-image framework, generates previews of the potential objects, and each one can be regenerated, modified or discarded, giving the artist creative control. The assets can also be refined in Blender (automatic export is provided) or in other 3D modelling software. The assets can then be converted into ready-to-use 3D models via the Microsoft TRELLIS Nvidia NIM microservice, which accelerates the process. Microsoft TRELLIS is a 3D asset generation model developed by Microsoft Research that allows users to generate detailed 3D assets with complex shapes and textures using text or image prompts. While high-quality text-to-image 3D models for consumer use can be difficult to set up, TRELLIS NIM integrates with the Nvidia AI Blueprint, simplifies deployment and accelerates generation by 20% on Nvidia RTX GPUs. Nvidia says that with PyTorch optimisations, the average time saved is approximately 6 seconds per object on an Nvidia GeForce RTX 5090 GPU (see below for today's deals). You can learn more about the pipeline in the Nvidia AI Garage blog. If you need to upgrade your setup for 3D work, see our pick of the best laptops for 3D modelling.