Pyramid JIT

Linum describes Pyramid JIT, an approach for training text-to-image generation models without using a variational autoencoder to compress images into latent space. Removing the VAE could simplify training pipelines and change how diffusion-based image models are built. Technical readers are discussing the potential efficiency gains and trade-offs of abandoning the standard latent compression step used by most current systems.