Mostly for automation. Bots don't need to read and they are very happy to parse data. People like to use bots to run thousands or millions of simulated games t

Mostly for automation. Bots don't need to read and they are very happy to parse data. People like to use bots to run thousands or millions of simulated games to test how good their bot is at chess and have it ranked. Other people like to use the bots that were created to play chess as practice toward a certain skill level. Beginners can pick bots that are proven to be beginner level, through thousands or millions of simulated games. The smaller the data footprint for the games, the faster and more efficiently the bots can play, which reduces cost and time. In a more practical sense, AI/ML algorithms can be more efficient with tiny data sizes for a bunch of complicated reasons. So, overall, this is "nerd sniping" to develop better chess players, both human and automated. It's not the most extensible presentation, I'll grant you, but I'm sure it's as fun as Regex Golf, or any other data-packing stuff. P.S. I'm sure the comp-sci dev in you already knew all this; this is just a bill in case anyone read your comment and truly didn't already know all of this.