'JPEG of thought'
In The Register, a very interesting breakdown of what's going on when generative AI edits decent writing and churns out an "improvement" that is so horridly dull:
Stage 1: Metaphoric cleansing. The AI identifies unconventional metaphors or visceral imagery as "noise" because they deviate from the training set's mean. It replaces them with dead, safe clichés, stripping the text of its emotional and sensory "friction."
Stage 2: Lexical flattening. Domain-specific jargon and high-precision technical terms are sacrificed for "accessibility." The model performs a statistical substitution, replacing a 1-of-10,000 token with a 1-of-100 synonym, effectively diluting the semantic density and specific gravity of the argument.
Stage 3: Structural collapse. The logical flow – originally built on complex, non-linear reasoning – is forced into a predictable, low-perplexity template. Subtext and nuance are ablated to ensure the output satisfies a "standardized" readability score, leaving behind a syntactically perfect but intellectually void shell.
The result, suggests Claudio Nastruzzi, is a "JPEG of thought" -- meaning an end product that is "visually coherent but stripped of its original data density through semantic ablation."