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This article discusses AI's influence on mathematics, using compressed sensing as an example of applied pure math, and critiques the 'open problem culture' that prioritizes puzzle-solving over understanding.
A 2017 presentation by David Donoho at the AMS discusses how high-dimensional geometry is revolutionizing the MRI industry, likely through compressed sensing and related mathematical techniques.
This paper proposes a framework for conditional generative compressed sensing, proving stable recovery bounds for prompt-conditioned models and demonstrating how prompt matching influences sampling distributions in experiments with Stable Diffusion.