Using ChatGPT and GPT-4 to Generate 3D Content in Omniverse
TLDRIn a dynamic demonstration, Mario Viviani from NVIDIA's Omniverse team introduces the Rune Generator, an AI extension that revolutionizes scene creation. Using GPT-4 and Deep Search, Mario efficiently builds and furnishes complex virtual environments such as warehouses and reception areas. The demo highlights the extension's ability to generate diverse and spatially aware placements of virtual objects, showcasing the powerful integration of AI and APIs in the Omniverse platform. This technology not only speeds up the design process but also enhances the accuracy and variety of scene elements, promising exciting possibilities for future development.
Takeaways
- 🚀 Mario Viviani from Nvidia's Omniverse team introduces a new AI extension called Rune Generator, showcasing the power of combining AI and APIs for accelerated scene building.
- 🎨 The AI used in the demo includes GPT-4 and Deep Search, which are utilized to enhance the creation of a warehouse and a reception room within the Omniverse platform.
- 📐 Mario begins by creating a floor plan and generating a small warehouse space, using a new curve to define the area for item placement.
- 🛠️ A prompt is used to instruct GPT-4 to add common items found in a warehouse, which are then automatically loaded into the scene by Deep Search.
- 🧱 The generated warehouse scene includes a variety of items like palettes, shelvings, and different units, all arranged in a logical and spatially aware manner.
- 🛋️ For the reception room, Mario creates a larger area and uses a prepared prompt to generate items suitable for a comfortable lounge where customers can wait.
- 🔍 Deep Search is highlighted as an ecosystem of services that allows users to search for content stored in the nucleus server using natural language queries, enhancing the search for assets.
- 🛒 The AI successfully generates a reception room with a front desk, sofas, coffee table, armchairs, and an informative display stand, demonstrating its ability to understand context and spatial relationships.
- 🔄 Deep Search Swap is introduced as a feature that allows users to quickly iterate through different variations of an object by using AI to search for and propose alternatives.
- 📚 The importance of combining AI technologies like GPT-4 and Deep Search is emphasized for their potential in creating powerful tools for content creation and scene building.
- 🔗 Mario encourages viewers to explore the Omniverse extension documentation to learn how to build new tools, indicating the platform's support for user innovation.
- 🌟 The demo concludes with excitement for the future of AI in content creation and the anticipation of the tools that creators will develop using these advanced technologies.
Q & A
Who is giving the demo of the new AI extension for Omniverse?
-Mario Viviani from the Nvidia, Omniverse team is giving the demo.
What is the name of the new AI extension for Omniverse?
-The new AI extension for Omniverse is called Rune generator.
Which AI services are used in the demo?
-The AI services used in the demo are GPT-4 and Deep Search.
What is the purpose of the Rune generator extension?
-The purpose of the Rune generator extension is to accelerate scene building by combining AI and APIs.
How does the AI help in generating a list of items for the scene?
-GPT-4 generates a list of items, connects to Deep Search, and loads those items into the scene.
What is the first room that Mario decides to create in the demo?
-The first room that Mario decides to create is a small warehouse.
What is the second room created in the demo?
-The second room created in the demo is a reception room for visitors of the warehouse.
How does Deep Search help in selecting and iterating through different items?
-Deep Search is an ecosystem of services that allows Omniverse users to search for content stored in the nucleus server using natural language queries, enabling quick iteration through different item variations.
What is the significance of spatial awareness in the AI-generated scene?
-Spatial awareness ensures that all items are correctly disposed and there is a logic to the order of the items, making the scene look realistic and well-organized.
How can Deep Search be customized for individual users?
-Deep Search can be trained on an individual's own data, allowing for more personalized and accurate search results based on the user's specific needs.
What is the final message from Mario regarding the future of AI in Omniverse?
-Mario expresses excitement about the future of AI in Omniverse and encourages users to explore the extension documentation and create new tools with it.
Outlines
🚀 Introduction to AI Extensions in Omniverse
Mario Viviani from the Nvidia Omniverse team introduces Rune, a new AI extension for Omniverse. He demonstrates how AI and APIs can speed up scene building using GPT4 and Deep Search. The demo involves creating a warehouse and a reception room, starting with a floor plan and generating room contents using AI prompts. The process showcases the ability to quickly generate and arrange items within a scene, highlighting the spatial awareness and efficiency of the AI.
🔍 Deep Search: Enhancing Scene Customization
The second paragraph focuses on the capabilities of Deep Search, an ecosystem that allows Omniverse users to find content stored on a nucleus server using natural language queries. It emphasizes the power of combining GPT's natural language understanding with Deep Search's ability to find assets. The demo shows how users can easily replace objects in a scene using the Deep Search swap feature, which automatically suggests alternatives based on AI-driven searches. This part of the presentation illustrates the potential for iterative design and customization within the Omniverse platform.
Mindmap
Keywords
💡Omniverse
💡Rune Generator
💡GPT-4
💡Deep Search
💡Scene Building
💡AI Room Generator
💡Natural Language Queries
💡Spatial Awareness
💡Item Disposition
💡APIs
💡Content Generation
Highlights
Mario Viviani from Nvidia's Omniverse team demonstrates a new AI extension called Rune Generator.
The extension combines AI and APIs to accelerate scene building in Omniverse.
GPT-4 and Deep Search are the AI systems used in the demo.
A warehouse and a reception room are envisioned for the scene building.
A new curve is created to define the area for items in the warehouse.
Rooms are generated by selecting the curve and providing a prompt for the room's content.
GPT-4 generates a list of items, which are then loaded into the scene using Deep Search.
The AI gracefully disposes a variety of items, including palettes and shelvings, within the scene.
The reception room is created with a prompt that includes a front desk and a comfortable lounge.
The AI accurately generates items relevant to a reception area, including sofas, a coffee table, and armchairs.
GPT-4 demonstrates spatial awareness by correctly disposing items within the defined area.
Deep Search is introduced as an ecosystem of services for searching content stored in the nucleus server.
Deep Search uses AI to find assets based on natural language queries, improving search accuracy with more descriptive terms.
Deep Search can be trained on custom data, showcasing the power of combining it with GPT's natural language capabilities.
An extension called Deep Search Swap is used to quickly iterate through different object variations using AI.
The demo concludes by emphasizing the potential of AI and its integration with Omniverse for future tool development.
The audience is encouraged to explore the Omniverse extension documentation to learn how to create new tools.