In almost all (all?) latent diffusion models, the VAE that sandwiches the diffusion model is not a real VAE: the KL loss has a weight of 10^-5 and there is an additional GAN loss that significantly boosts the visual quality. So it's more an adversarial auto-encoder than anything else.

Okay this JPL article has more details. It actually used image data as context which is pretty impressive!

https://www.nasa.gov/missions/mars-2020-perseverance/perseverance-rover/nasas-perseverance-rover-completes-first-ai-planned-drive-on-mars/

The output as markup makes sense, but what is the input context?

Ah I see it does have a built-in labeler. Maybe adjusting these settings will help: https://bsky.app/profile/moderation.bsky.app

Does bsky have a built-in spam label? I know you can subscribe to labelers (many exist for spam/bots) and when you do, you choose whether labeled accounts just have a label or are hidden. It would be nice to have a “show hidden” UX though.

Lol that latex compile time pause in a demo video. Use @typst.app!

Call Schumer's office today at (202) 224-6542. Then get on the phone to Jeffries at (202) 225-5936. 7/