Consider also looking into R-trees [1], which are like a balanced quadtree and is commonly used for indexing more complex spacial data (i.e. polygons/areas).
I'm pretty ambivalent about generative AI's effect on my happiness/motivation.
Often talking to Claude/using AI agents to build software is really enjoyable/motivating, and it also makes it easier to get the satisfaction from completing projects.
But it also tends to make me think about how quickly the technology is developing. This makes me anxious about x-risks from AI, which makes it harder to get work done.
They have good margins on inference at API costs, i.e. $5/$25 per mtok input/output. They are almost certainly making losses on subscriptions, at least if people max out rate limits.
In the past 30 days I have burned $78.19 in API token costs with my $20/month Claude Pro subscription. In January I burnt over $300 in API token costs.
[1]: https://en.wikipedia.org/wiki/R-tree