DALL-E is 250m: https://arxiv.org/pdf/2102.12092.pdf#page=14 https://arxiv.org/pdf/2102.12092.pdf#page=14 (so 20x larger). CLIP (https://cdn.openai.com/papers/L

DALL-E is 250m: https://arxiv.org/pdf/2102.12092.pdf#page=14 https://arxiv.org/pdf/2102.12092.pdf#page=14 (so 20x larger). CLIP (https://cdn.openai.com/papers/Learning_Transferable_Visual_Models_From_Natural_Language_Supervision.pdf https://cdn.openai.com/papers/Learning_Transferable_Visual_M...) is 400m (34x larger). And ALIGN (https://arxiv.org/abs/2102.05918#google https://arxiv.org/abs/2102.05918#google) is 1800m (155x). (For 47m maybe you're thinking of a cleaned subset from YFCC100M or something that one of them used, but they all use total images an order or two larger than Wit.)