The article discusses the concept of treating text as images to improve the efficiency of language models, drawing on a recent OCR paper that suggests "optical compression" allows models to extract more information from images than from text. It explores the implications of this approach for AI processing and compares it to human memory, ultimately questioning the conventional methods of text consumption in AI.
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