Designers’ jobs to crash or GLIDE
OpenAI has extended the capabilities of its text-to-image software from two dimensions into three with the release of Point•E, an open source project that produces 3D images from text prompts.
The AI research firm has attracted considerable attention for its DALL•E software, which like rival projects Stable Diffusion and Midjourney can generate realistic or fantastical images from descriptive text.
While Point•E shares the bullet point symbol used in OpenAI’s DALL•E branding, it relies on a different machine learning model called GLIDE. And presently, it’s not nearly as capable. Given a text directive like « a traffic cone, » Point•E produces a low-resolution point cloud – a set of points in space – that resembles a traffic cone.
The result is nowhere near the quality of a commercial 3D rendering in a film or video game. But it’s not supposed to be. Point clouds represent an intermediate step – once fed into an 3D application like Blender, they can be turned into textured meshes which look more like familiar 3D imagery.
« While our method still falls short of the state-of-the-art in terms of sample quality, it is one to two orders of magnitude faster to sample from, offering a practical trade-off for some use cases, » explain OpenAI researchers Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, and Mark Chen in a paper [PDF] describing the project.
