What is the primary difference between DALL.E 2 and GLIDE in terms of how they utilize text embeddings during the image generation process?

The primary difference between DALL.E 2 and GLIDE is that DALL.E 2 uses CLIP embeddings to carry information from the text prompt, while GLIDE does not use CLIP embeddings and instead trains the entire model from scratch using the raw text prompt.

DALL.E 2 utilizes CLIP embeddings, which are generated by a text encoder trained with contrastive learning to match images with text descriptions. These embeddings are used throughout the image generation process, allowing DALL.E 2 to condition its outputs on these embeddings. On the other hand, GLIDE does not use CLIP embeddings. Instead, it processes the raw text prompt directly and trains the entire generative model from scratch. This means GLIDE relies on its own Transformer-based text encoder to guide the image generation process without the aid of pre-trained embeddings like those from CLIP.