Understanding approximate nearest neighbor algorithm
Hi, This post is about the approximate nearest neighbor (ANN) algorithm. The code for this post is here, where I provide an example of using a framework and a python implementation. Most python implementation were written with the help of a LLM. I’m amazed, how helpful they are for learning new things. I see them like a drunken professor, which with the right approach will be a very helpful tool. As a next step in understanding RAGs, I want to have a closer look at approximate nearest neighbor algorithms. Basically, the purpose is to find the closest vector to a query vector in a database. Since I’m also interested into the implementation, I follow mostly this amazing blog post. Vector search is the basic component of vector databases and their main purpose. ANN algorithms are looking for a close match instead of an exact match. This loss of accuracy allows an improvement of efficieny, which allows the search through much bigger datasets, high-dimensional data and real-time apllications. ...