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It contrasts the one-to-one \nsymbolic representation reminiscent of early Wittgenstein and traditional AI with the subsymbolic, \nconceptual synthesis found in modern neural networks like CLIP and diffusion models. The paper traces \nthe technological evolution from GANs to diffusion, analyzing the implications for creativity, originality, \nand the machine's capacity for metaphor. 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