OpenAI DALL·E: Creating Images from Text (Blog Post Explained)

#openai #science #gpt3

OpenAI's newest model, DALL·E, shows absolutely amazing abilities in generating high-quality images from arbitrary text descriptions. Like GPT-3, the range of applications and the diversity of outputs is astonishing, given that this is a single model, trained on a purely autoregressive task. This model is a significant step towards the combination of text and images in future AI applications.

OUTLINE: 0:00 - Introduction 2:45 - Overview 4:20 - Dataset 5:35 - Comparison to GPT-3 7:00 - Model Architecture 13:20 - VQ-VAE 21:00 - Combining VQ-VAE with GPT-3 27:30 - Pre-Training with Relaxation 32:15 - Experimental Results 33:00 - My Hypothesis about DALL·E's inner workings 36:15 - Sparse Attention Patterns 38:00 - DALL·E can't count 39:35 - DALL·E can't global order 40:10 - DALL·E renders different views 41:10 - DALL·E is very good at texture 41:40 - DALL·E can complete a bust 43:30 - DALL·E can do some reflections, but not others 44:15 - DALL·E can do cross-sections of some objects 45:50 - DALL·E is amazing at style 46:30 - DALL·E can generate logos 47:40 - DALL·E can generate bedrooms 48:35 - DALL·E can combine unusual concepts 49:25 - DALL·E can generate illustrations 50:15 - DALL·E sometimes understands complicated prompts 50:55 - DALL·E can pass part of an IQ test 51:40 - DALL·E probably does not have geographical / temporal knowledge 53:10 - Reranking dramatically improves quality 53:50 - Conclusions & Comments

Blog: https://openai.com/blog/dall-e/

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