I did the same with my taxes that I needed to file in Oct after getting extension in April. Added the return and all supporting docs to a Claude project. Found 2 big issues and 4 smaller ones, all legit. Basis and depreciation calc for two rental properties were way off. Also IRA basis stuff was wrong those two were heavily in my favor to correct. Felt a little bad peppering the accountant with issues, but he was apologetic and corrected. This is a no brainer use case for me going forward.
My first ever "e2e" ML project during early covid quarantine was a crude vision model to detect pigeons on my balcony (and pigeons only) and play a loud random sound. It almost worked sometimes.
Did a similar thing where I had a neighbor who raised dobermans and rottweilers - it's a bit difficult to code with 8 or 9 large dogs barking in the yard outside your window.
Set up an amp and speakers that would pump out ultrasonic noise when it heard the barking, sending them running to the other side of their house.
I've been pleasantly surprised how well it has worked and how robust it is. It's installed at my parent's house and I am many states away so I was paranoid about making it resilient since i'm usually not there and have to fly to get there. So, i really tried to think of everything I could. I thought it might overheat the first afternoon or have other problems, but it's been running for months now uninterupted. Sometimes the OpenRouter credits run out and it stops catching birds , but it still runs normally and after I re-up the credits, it continues working normally. No need to restart even.
I had been using gemma-4-31B-it llm for cost/accuracy and it was super cheap, about $0.65/month. I had also downscaled the size and back tested on bird/no-bird images from my camera.
But, then I noticed that it was missing birds that were at the back of the pool and I needed to use higher resolution and better models and cost went up 10x. Now, it's to high for my liking and I need to do more model testing to get it down to a few dollars a month that seems reasonable. I can also reduce frequency, I'm doing every 2 mins during daylight hours.
My sense has been that accuracy that I need is only possible with the pretty advanced AI models and that OpenCV type approach wouldn't be good enough. Birds are pretty small in the image of the overall pool that I am working with and discerning them accurately is hard. I think it would be possible for other use cases and basically depends on the image source you are working with and the difficulty of detection within that image.
If you had, say, a camera on the inside of a birdhouse and the whole scene was either empty of taken up by a bird, then that would be easy for an on-device model.
I'm seeing some pretty cool projects for bird detection with YOLO online. They may do more than you need; you probably don't care about the kind of bird, right?
Maybe it would be worth it to spend a few tokens on an implementation, just to try!
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