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A long-term objective of artificial intelligence is to build “multimodal” neural networks—AI systems that learn about concepts in several modalities, primarily the textual and visual domains, in order to better understand the world. In our latest research announcements, we present two neural networks that bring us closer to this goal. The first neural network, DALL·E, can successfully turn tex
OpenAI today debuted two multimodal AI systems that combine computer vision and NLP: DALL-E, a system that generates images from text, and CLIP, a network trained on 400 million pairs of images and text. The photo above was generated by DALL-E from the text prompt “an illustration of a baby daikon radish in a tutu walking a dog.” DALL-E uses a 12-billion parameter version of GPT-3, and like GPT-3
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