I remember reading that for k-d trees to be able to split on k dimensions the dataset needs to be > 2^k, which becomes unwieldy pretty quickly

… yes to the 2^k only because if not met, the performance devolves to a linear search. By themselves, k-d trees can handle any number of records.

yep, also i think while they could have issues with dataset sizes less than 2^k, it's interesting to note their use in accelerating clustering algos like dbscan. they do make neat visualizations though https://marimo.app/?slug=x5fa0x