Deterministic process


"In a paper that will be presented at the International Conference on Machine Learning 2025, the duo developed a mathematical model of trained diffusion models to show that their so-called creativity is in fact a deterministic process —a direct, inevitable consequence of their architecture.

"By illuminating the black box of diffusion models, the new research could have big implications for future AI research —and perhaps even for our understanding of human creativity. 

"'The real strength of the paper is that it makes very accurate predictions of something very nontrivial,' said Luca Ambrogioni, a computer scientist at Radboud University in the Netherlands."

[Looks like flattery is an emergent property alongside above denoising's (pseudo) creativity…]
["For the first time, researchers have shown how the creativity of diffusion models can be thought of as a by-product of the denoising process itself, one that can be formalized mathematically and predicted with an unprecedentedly high degree of accuracy. It’s almost as if neuroscientists had put a group of human artists into an MRI machine and found a common neural mechanism behind their creativity that could be written down as a set of equations."]
["Experts interviewed for this story generally agreed that although Kamb and Ganguli’s paper illuminates the mechanisms behind creativity in diffusion models, much remains mysterious. For example, large language models and other AI systems also appear to display creativity, but they don’t harness locality and equivariance. 'I think this is a very important part of the story,' Biroli said, 'but it’s not the whole story'."]


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