The article explores how Generative AI systems, particularly Gemini and Copilot, create diverging data color schemes using Mocha Mousse, Pantone's Color of the Year. Diverging color schemes are vital in data visualization, combining two color sequences with a neutral midpoint to indicate critical values. The author compares color scheme outputs from both AI tools, noting subtle differences linked to the initial Hex codes used. The discussion highlights the background of Pantone's systems, emphasizing their significance across various creative fields and the utility of AI in enhancing visual data representation.
In data visualization, diverging data color schemes are created by joining two sequential color sequences together with a neutral midpoint.
I specifically asked both Gen AI systems to 'Specify a five class diverging color scheme for Mocha Mousse with a neutral - white midpoint and color hex codes that passes color deficiency tests.'
The differences in the color schemes specified by each Gen AI tool are slight and based on the initial color Hex code each system selected as a match to Mocha Mousse.
Pantone's Color of the Year Concept involves producing proprietary color spaces used across various industries for accurate color reproduction.
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