Been using this for my dog walks too. There's something oddly satisfying about turning a boring loop around the block into "wait, does that bin have a lid?" Never thought trash cans would be the thing that got me into mapping.
Really impressive for a 13 year old, and refreshingly honest writeup. The failed self-correction section is the best part: six methods tried, six negative results reported instead of buried. That's rarer than the architecture itself. Curious whether the shared+LoRA bidirectionality idea holds up once you run it past 2000 steps.
How does this compare to JuiceFS or SeaweedFS in terms of metadata latency? The LSM tree approach is interesting but compaction pauses on a remote-backed store seem like they could be painful.
The detection problem is genuinely hard. Even desktop AI agents I've been working with recently can control Spotify, fill forms, navigate apps — all indistinguishable from human interaction at the OS level. If that's hard to detect at the application layer, detecting AI-generated music at the audio layer seems like a cat and mouse game that Tidal will struggle to win without self-reporting from uploaders.
been using long youtube lectures for this for years. the sweet spot is something just interesting enough that your brain can't fully let go, but not interesting enough to actually keep you awake. theoretical physics talks hit it perfectly for me.
the problem is occasionally you find one that's genuinely fascinating and you're suddenly wide awake at 3am having learned something.
For anyone hitting the "I don't have the original game files" wall: EA released C&C and Red Alert as free downloads years ago. Just search "cnc-comm red alert download" , totally legit.