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DALL·E 2 can take an image and create different variations of it inspired by the original. In January 2021, OpenAI introduced DALL·E. One year later, our newest system, DALL·E 2, generates more realistic and accurate images with 4x greater resolution.
DALL·E: Creating images from text. We’ve trained a neural network called DALL·E that creates images from text captions for a wide range of concepts expressible in natural language. Illustration: Justin Jay Wang.
Modern text-to-image systems have a tendency to ignore words or descriptions, forcing users to learn prompt engineering. DALL·E 3 represents a leap forward in our ability to generate images that exactly adhere to the text you provide.
Generative models. Illustration: Ludwig Pettersson. This post describes four projects that share a common theme of enhancing or using generative models, a branch of unsupervised learning techniques in machine learning.
Explore resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's developer platform.
In our work, we first show that better generative models achieve stronger classification performance. Then, through optimizing GPT-2 for generative capabilities, we achieve top-level classification performance in many settings, providing further evidence for analysis by synthesis.
Experiment with DALL·E, an AI system by OpenAI.
Sora is an AI model that can create realistic and imaginative scenes from text instructions.
More than one million people are using DALL·E, the AI system that generates original images and artwork from a natural language description, as a creative tool today. Artists have already created remarkable images with the new Outpainting feature, and helped us better understand its capabilities in the process.
Glow models can generate realistic-looking high-resolution images, and can do so efficiently. Our model takes about 130ms to generate a 256 x 256 sample on a NVIDIA 1080 Ti GPU. Like previous work, we found that sampling from a reduced-temperature model often results in higher-quality samples.