@TTTrouble

Man I took a break from getting into the weeds of the AI papers but I really appreciate that you’re still at it man, and it inspires me to jump back into the jungle. You’ve definitely been a fantastic source of knowledge and helped me break down some of this stuff in a really meaningful way. Keep up the great work!

@kevinxu9562

GOATED damn thank you so much for making a video on this! Timing is goated, just started going through your diffusion series as I'm trying to build a diffusion model!

@vladandronik5711

Thanks for sharing! Struggled a bit with understanding flows, but you explained everything really nicely

@VisionTang

Thanks you a lot for sharing this! It helps me a lot

@mathiasbang1999

Hey I was wondering if you could clarify something for me. You say that the [154; 4096] matrix holds the "fine grained" information, but when explaining the MM-DiT block setup Y is marked as fine grained information. It does seem to make more sense for the Y to be fine grained information in my opinion as it is post reduction information, however as I am not entirely sure I would love for you to maybe correct me on that :). Really appreciate the video! makes a lot of sense overall

@alexalex-lz8sg

Cool, what about latent adversarial diffusion distillation(LADD) video?

@zeogod100

I stopped watching when you named the image height "L", BLASPHAMY!