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This analogy makes even more sense when we remember that a common technique used by lossy compression algorithms is interpolation—that is, estimating what’s missing by looking at what’s on either side of the gap. When an image program is displaying a photo and has to reconstruct a pixel that was lost during the compression process, it looks at the nearby pixels and calculates the average.
✏️ ChatGPT takes two points in “lexical space” and fills in what would occupy the location between them (e.g. tell me about world history as if you were a pirate)
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