Similarity Search, Quantization, Faiss, Machine Learning, Hands On Tutorials.
created centroids k is usually chosen as a power of 2 for more efficient memory usage. This way, the memory required to store an encoded vector is n * log(k) bits. The collection of all centroids inside a subspace is called a codebook. Running n clustering algorithms for all subspaces produces n