Getting an LLM to Make Me a Tool for Enriching My Icons' Color Metadata (blog.jim-nielsen.com)

A creative user has leveraged a large language model (LLM) to develop a customized tool for tagging the color metadata of over 2,000 icons, streamlining a labor-intensive process. The tool enables visual categorization by displaying two columns: one for icons already tagged by color and another for untagged icons that the LLM proposes might belong to a specific color category. By implementing a “hue histogram” analysis, the LLM processes each image file, ranks icons based on their color distribution, and facilitates user decision-making through an interactive interface. This development is significant for the AI/ML community as it exemplifies the practical application of LLMs in generating ad-hoc solutions that improve productivity and maintain user control over subjective tasks. The emphasis on quick, disposable code rather than production-grade solutions highlights how LLMs can assist in creating individualized tools tailored to specific needs, combining basic web technologies like HTML and JavaScript. This approach not only accelerates workflows but also demonstrates the potential for LLMs to serve as collaborative partners in creative processes, enhancing efficiency while empowering users to make final decisions.