Trying to build a web scale semantic image search. Anyone wants to hack with me?

I did see tiefvision, yes. Somehow, their approach didn't quite work for me, although that was the first attempt. Maybe it's good when you have only few classes of images ("only dresses") and modest amounts of training data.

..there are no direct private messages on HN, right? I have an email in the blog post, just in case there is no other way

Good question. Right now I am using AWS spot instances + credits bought for Bitcoin. This makes the thing maybe 70 times cheaper than on-demand instances paid normally.

But when I go above several billions of images, I'll need some investment for sure :-)

Tineye indexed about 20 billions of images, and my estimates show that I should be fine with my own resources up to 1B. This is good enough to improve and test the tech

Google searches for exact match + image classification + text search, and also recognizes some famous images (such as Eiffel tower). E.g. if Google sees an unfamiliar image, it converts it to something like a "red swivel chair", and searches for that (so no way it can find the same object unless it is really unique).

I want to make it possible to just snap a picture of anything and find this object. Try to take a picture and search for it on Google Images.

Although, I should say, image search in Baidu works way better than Google's