23
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 22 May 2025
23 points (100.0% liked)
technology
23788 readers
352 users here now
On the road to fully automated luxury gay space communism.
Spreading Linux propaganda since 2020
- Ways to run Microsoft/Adobe and more on Linux
- The Ultimate FOSS Guide For Android
- Great libre software on Windows
- Hey you, the lib still using Chrome. Read this post!
Rules:
- 1. Obviously abide by the sitewide code of conduct. Bigotry will be met with an immediate ban
- 2. This community is about technology. Offtopic is permitted as long as it is kept in the comment sections
- 3. Although this is not /c/libre, FOSS related posting is tolerated, and even welcome in the case of effort posts
- 4. We believe technology should be liberating. As such, avoid promoting proprietary and/or bourgeois technology
- 5. Explanatory posts to correct the potential mistakes a comrade made in a post of their own are allowed, as long as they remain respectful
- 6. No crypto (Bitcoin, NFT, etc.) speculation, unless it is purely informative and not too cringe
- 7. Absolutely no tech bro shit. If you have a good opinion of Silicon Valley billionaires please manifest yourself so we can ban you.
founded 4 years ago
MODERATORS
As someone who has to deal with a lot of boilerplate construction permits all day, this is actually something that AI could be useful for.
I'm creating the permits, so I have total access to the spatial design databases for internal QA, but permit reviewers with the city/county usually only receive a PDF or some other document format.
These drawings frequently have thousands of dimensions each, and tallying them up by hand can be a bear. Training a hyper specific model to look at an image of a permit page and highlight areas where possible dimensional conflicts could be or find other commonly overlooked mistakes would be really helpful.
They absolutely just mean slapping a screenshot into GPT3o and calling it a day though...
That sounds more like a scenario that would benefit from electronic data integration, not heuristics-based machine learning. There's way too much stuff that still uses formats designed for human consumption.
Totally agree, migrating to using spatial databases and accepting permits in forms other than paper/PDF would make everyone's lives so much easier.
The industry still isn't very caught on to geospatial stuff at that scale though. Most draftsman work is still just draftsman work, a very manual process. Having a way to help validate and pre-screen those permits would still be helpful while people start migrating to better systems over the next decade or so.