OpenAI has released a new tool called Point-E, which allows users to generate 3D objects based on simple text input.
The tool uses a combination of a text-to-image model and an image-to-3D model to achieve this. The text-to-image model is trained on labeled images to understand the associations between words and visual concepts. When a text prompt is inputted, such as “a 3D printable gear, a single gear 3 inches in diameter and half inch thick,” the model generates a synthetic rendered object.
The image-to-3D model, on the other hand, is trained on images paired with 3D objects, allowing it to effectively translate between the two. The synthetic image generated by the text-to-image model is fed into the image-to-3D model, which produces a point cloud representing the 3D object.
Point clouds are easier to synthesize from a computational standpoint compared to traditional 3D objects, but they do not capture fine-grained shape or texture. To address this limitation, the Point-E team trained an additional AI system to convert the point clouds to meshes. Meshes, made up of vertices, edges, and faces, are commonly used in 3D modeling and design, and allow for a more detailed representation of the object.
The model was trained on a dataset of several million 3D objects and associated metadata, and is able to produce colored point clouds that frequently match text prompts. However, the system is not perfect and can sometimes produce inaccurate or incomplete models. Despite these limitations, Point-E’s efficiency and potential for generating 3D models from text input alone make it a promising development in the field of artificial intelligence.
One of the major advantages of Point-E is its speed and efficiency. The process can be completed on a single graphics card and takes only 1-2 minutes to generate the final image. While the resulting 3D object may not be perfect, the tool has the potential to be a useful tool for creating 3D models based on text input alone. However, running Point-E does require some technical know-how. The code is available on GitHub, but users will need to have python installed and be familiar with running command-line tools and programs.
Despite its limitations, Point-E is a promising development with the potential to be a game-changer in the creation of 3D models, with applications in 3D printing, entertainment, social media, game development and animation. In the future, we expect it to create photorealistic 3D models based on text input in realtime. As AI continues to advance, tools like Point-E will only become more sophisticated and powerful, and will likely revolutionise the way that 3D models are created.
While Point-E is not the first 3D model generator to be developed, it is certainly one of the most promising. The OpenAI team notes that while the system is not yet as accurate as the state-of-the-art techniques, it produces samples in a small fraction of the time, which could make it more practical for certain applications, or could allow for the discovery of higher-quality 3D objects.
As AI-generated 3D models become more prevalent, they will likely find use in a variety of industries, such as film and television, interior design, architecture, and various science fields. Architectural firms could use them to demo proposed buildings and landscapes, while engineers could leverage them as designs for new devices, vehicles, and structures.
Currently, 3D models creation can be a time-consuming process, often taking several hours to several days. With tools like Point-E, this process could be significantly streamlined and made more efficient. As a result, the use of 3D models in various industries is likely to increase, and the demand for AI-generated 3D models will only continue to grow.
Point-E has the potential to revolutionise the way that 3D models are created. As the technology continues to advance, we can’t wait to see what the future holds for this powerful tool.
PSYBER
Email: info@psyber.nl
Phone: +31646328914
🦾Digital Innovation 🌞 Management Strategies 🏛 AI Governance 🧱 Enterprise Architecture 🏄♂️ Business Agility 🗝 CyberSecurity 👓 KYC 👨💻 Cyberpsychology ⚡️ Sustainability ⭐️ Future of Work 🌍 Global Operations 📊 ESG
