Before I start, I seriously have no idea what Elastic is and How it works. I am ML Engineer and has recently been assigned the task for Image - Image similarity. I developed a model which will compare the distances between the vectors provided by the model such as
Manhattan, Euclidean, cosine etc. I could do it easily but the problem is that I have this huge data around 20M images and I can not store all the vectors in memory for starters and even if I do, it is practically impossible for me to compare with each and every unit as it'll be
So I want to know that are there any algorithms for Vectors searching just there is text search algo like
My vectors look like:
[0.2,0.1,0.04,......] etc. They can be any dimensional depending on the use case. But is there any algorithm which can get me
top-k search results.