Diffusion models explained in 4-difficulty levels

that was aweeeeessssommmmmmeeeee

Thank You !

Nice explanation! I feel like the video title is misleading, it is just one explanation going deeper and not complete without the deeper levels of knowledge and differs a lot from other videos that start from zero the explanation at different levels. This is more like 4 shades of Diffussion :D Thanks for sharing!

❤🎉 amazing lecture

Such a great video to dive in! I'm live streaming learning about Diffusion, right now!

This video was awesome! Well done :) and thank you

Wow! There’s another video if yours below this one, and your hair is so different that I didn’t recognize that it’s you.

Great

I want to understand diffusion models so I can understand how it's possible for artificial intelligence to produce an image. Your explanation helps. A bit.

Any level >= 5 ?

Appreciate your explanation skill.
Q. What is diffusion model
Ans. Let's say you tell your best friend, Sarah, about this amazing new flavor. Sarah gets excited and tells her friend, Tom. Then Tom tells his cousin, Emily. Emily, in turn, tells her family, and the news keeps spreading from person to person, creating a chain reaction. This process of your ice cream flavor information spreading from one person to another is like how a drop of ink spreads in water. At first, it's just a small spot, but then it spreads out and covers more and more area as time goes on.

In the diffusion model, experts study how things, whether it's information, ideas, or products like your ice cream flavor, spread through a community of people. They try to understand how fast it spreads, how many people it reaches, and what factors influence its spread. By understanding these patterns, they can learn a lot about how people share and adopt new things!

It would be good if you also explain the reverse process in detail as you explained the forward process

really amazing video thank you very much! subbed! :)

I need level 5/6/7 of explanations

She might not have technical background. No technical person will mispronounce variance as variation.

Good explanation but i do hate when papers add needless maths and physics which are tangential at best when they should be describing their model in a simple way.

Great explanation of diffusion models. Thank you.

This is an excellent video. Love the format. Well done, more please!

bewbs

wow someone finally pulled this off

In the level 1 explanation, what’s the point of introducing the phrase “thermodynamic equilibrium”? Most lay people understand what it means when we say food coloring diffuses into clear water. Reminding the viewer why that happens from a physics standpoint makes the level 1 explanation less clear, not more clear.

Thank you so much for the elegant explanation.

I dunno about all that, I just type in 'boobs' and the thing delivers. Whatever math those silicon wafers decide to subject themselves to, that's on them.

Tysm <3

Can someone explain why do we need to know the initial position of the ink in water if we already knew where the ink was first introduced?

Sorry, but this video is very frustrating. Nothing was explained in terms of either the technique for reversing or how it relates to new image creation when prompting, which is obviously what we are mostly interested on.

This is very good intro for quick understanding of the concept 👍

6 minutes explaining nothing and at the end.. blablabla super fast about convolution... and nothing clear :/

thanks for this

there is the whole language part missing.

Great explanation!

Having just watched 5 videos on this, umm, "topic?" I feel as if I have been in a coma for 25 years. I am looking for the simplest possible explanation on how this whole AI thing works, yet there don't seem to be any videos that can explain that without using already established terminology that, to me, is completely foreign. Your video is obviously well made, and you are good at explaining this, especially with the example of a drop of paint in water, but I am obviously so far from even beginning anything beyond. Apart from understanding "noise", I have no clue as to what "diffusion", or "model" or anything means. I could always watch videos on any topic, i.e. quantum physics, rocket science, robotics, or anything, and get the basic idea, but this time I feel like I'm years behind... If you could make a video explaining this as if you would explain it to someone in kindergarten, I would definitely come back and watch

Learnt a lot of new things from this video.

Why it is called as UNet
Why it is called as diffusion model.
What diffusion model does and how it does.
Thanks

Can we take a moment to appreciate how silly it is to say, "we're gonna explain this in 4 levels - 1 being the easiest, 4 being the hardest"

and immediately starting level 1 with: "diffusion models were inspired by non-equilibrium thermodynamics from physics and as you can understand from the name this field deals with system d that are not in thermodynamic equilibrium"

next time ask ChatGPT to write it for you lmao, imagine going up to a five year old and being like,
"Hey kid, you're familiar with thermodynamic equilibrium right? Well the area of machine learning concerned with image generation using diffusion models takes that principle, but is inspired by its inverse."

Fine, you add noise to an image and then restore it. VERY simple concepts (even if very hard in practice). But the magic of DALL-E, Midjourney & Stable Diffusion is the creation of NEW images. This is the third video I'm watching that explains the same trivial diffusion concept. Guess I'll have to ask ChatGPT instead.

diffusion model can add noise to image1 and then in the revers process it make a different image (not the same) ?????? plz rpns?

'3/4/5-levels' looks like a very powerful way of explaining concepts. I'd like to see the higher levels be longer, and really drill down into the heart of the matter. So that the final level is communicating at an expert level. +1 / subbed.

A very confusing, yet somehow great explanation of diffusion models. Thank you!

what role do images in the training set play? are diffusion models violating copyright or not?

meanwhile some artist have their art been trained as a SD models....having their art stolen in a way , people are loosing jobs , replaced by ai already ..i 'm waiting for this tech to be used for fake news , propaganda , terrorism , .;maybe some laws will appear instead of screwing up artists

Beautiful woman, can you share you instagram? :D)

This feels like it should not be possible...then again, its not too different from us humans imagining faces in the clouds. Computers just take this hallucination to the next level.

@AssemblyAI

Why 255 (Probability Density Graph), does it have to do with binary? Network Engineer here, and I am trying to draw correlations between IP address ranges being 255 and subnet ranges being 255 and the graph you displayed. They all have binary masks in common hence why I am asking.

Good job.

Regarding level 3. Is every single pixel diffused at each step, or there is a subset that is randomly chosen? Is the sampling separate for every pixel or we take one value and then multiply it by each pixel? Subsequent diffusions work on the already diffused value, I guess (we don't try to remember what was the mean of the original pixel, but just use the new one)?

The explanation of adding noise was well done, but the reverse process--by far the strangest process--was not really explained at all. You introduced, but did not explain, some learning process. This unexplained process "somehow" gets back the image. Every "explanation" of SD always skips over this step! Why? (Also skipped, how the text prompt is "combined" with the image. Folks mumble about CL??, but never clearly explain it.) You are a very very good presenter. Please take 15 minutes to "explain" SD.

Beautiful❤

This was so helpful. Love this format of starting easier and add layers of explanations.

Fascinating stuff, Great explanation.

my brain cannot handle this