Like a diligent painter but is not

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Very controlled because the painter generator keeps drawing on the training source on one side and then teaches the discriminator on the other side. Also keep grading. After countless rounds of fighting, the painter and the teacher made crazy upgrades and progress, and finally the painter could draw realistic paintings, but the whole process was not easy to control. As he practiced, he often went crazy and output some stuff that no one could understand. At the same time,


his improvement process is essentially a constant imitation of previous works, so he still lacks creativity, resulting in a potentially low ceiling. The diffusion model is a diligent and intelligent painter. He is not a mechanical imitation. Instead, he learned the relationship between the connotation of the image and the image while studying a large number of previous paintings. He Rich People Phone Number List roughly knows what "beauty" in the image should be. It was more like he was thinking about what a certain "style" of such an image should look like. He was a more promising painter than N. In other words, enI chose the diffusion model as a paradigm to create the





Vincent video model, which is a good start at the moment. It chose a potential painter to cultivate. Then another question arises. Because everyone knows the superiority of the diffusion model. In addition to enI, there are many friends who are also doing diffusion models. Why does enI look more amazing? Because enI has such a thinking. I once worked on a large language model. I have achieved very good results and achieved such great success. Is it possible for me to use this experience to achieve a new success? The answer is yes. enI believes that its previous success in large language models is due to the fact that en can be translated into tokens,