I scraped 1.94M Airbnb photos for opium dens, pet cameos, and messy kitchens(burla-cloud.github.io) |
I scraped 1.94M Airbnb photos for opium dens, pet cameos, and messy kitchens(burla-cloud.github.io) |
It's content marketing plain and simple for Burla towards people that view this site. It was highly likely done by employees at both Burla and AirBNB together as a joint project.
The branding is a bit much, fair call, but the intent here was just to explore what these agents can actually build when you give them access to large amounts of compute.
As an experitisement, I guess it gets the name out there but not in any way I'd want for my business.
“Drug-Den vibes” apparently means the owner is poor or a photo is obscured or badly lit.
This Inside Airbnb?
Community Guidelines
Please:
Only take the data you need. Do not scrape data from the site, if you would like to subscribe to the data directly, please email data@insideairbnb.com
That's a lot of budget - would have been nice if they'd made an actual donation to the project, instead of pounding the project's servers and bandwidth when there are much better ways to interact with the data.
I’ll make a donation to support the project regardless. Appreciate you raising it.
Most of the bad TV placement ones are also boring because they're just over a fireplace. Technically correct, but not noteworthy. However, I did find one that was truly spectacular [1] (still live for now) and left me with more questions than answers.
[0]: https://www.airbnb.com/rooms/988178752120341661 / https://archive.is/xnvC5
[1]: https://www.airbnb.com/rooms/41725492 / https://archive.is/IyMvT
I've had shitty and small apartments many times and that doesn't prevent me from cleaning it. especially if I'm going to rent it out
>Scale Python across 1,000 CPUs or GPUs in 1 second. Burla is a high-performance parallel processing library with an extremely fast developer experience. Scale batch processing, vector embeddings, inference, or build pipelines with dynamic hardware.
Edit: Author comment was flagged dead. They work at burla which is a managed cloud service for parallelizing python
As an exercise a sample of 1000 photos would've been enough. As a database, knowing a listing has a cat in the picture or a funny review doesn't offer any real value.
I wonder what the footprint is of such an exercise.
How much does it cost to send a billion people an hour of video every day? Almost all of the resources tech uses is for pointless or even negative things.
What % of compute/bandwidth do you think is used for "real value"? I would guess it is well below 1%.
It's hardly the only thing, but it's part of the problem.
This post is a bit lighter on that disclosure than I'd like (and isn't as obvious as a Show HN would be) but I feel I missing some big portion of the backstory to this comment?