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<lom:langstring xml:lang="en">Meaning and Language in Artificial Intelligence’s own  Linguistic Turn</lom:langstring>

  
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<lom:langstring xml:lang="en">This paper examines the rapid development of generative visual artificial intelligence, particularly text-to image models, through the lens of 20th-century philosophy of language. It contrasts the one-to-one 
symbolic representation reminiscent of early Wittgenstein and traditional AI with the subsymbolic, 
conceptual synthesis found in modern neural networks like CLIP and diffusion models. The paper traces 
the technological evolution from GANs to diffusion, analyzing the implications for creativity, originality, 
and the machine&#39;s capacity for metaphor. It argues that while current models can visually render complex 
concepts by learning from vast datasets, they struggle with true abductive reasoning and novel metaphor 
creation, thus highlighting the persistent limits of machine understanding when compared to human 
language.</lom:langstring>

  
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<lom:langstring xml:lang="en">Philosophy of Language</lom:langstring>

  
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