Researchers have developed a method to train Variational Autoencoders (VAEs) that can be used remotely through inference endpoints. This allows users to decode data without needing to download or store large models, reducing computational costs and improving scalability. --- Why it matters: This matters for engineers working on large-scale AI applications because it enables more efficient use of resources and reduces the need for complex infrastructure setup. Source: https://huggingface.co/blog/remote_vae