However, it's worth noting that the actual growth rate of vector databases is not always exponential. This is because many vector databases use techniques such as dimensionality reduction, indexing, and caching to mitigate the curse of dimensionality.
For instance, some vector databases use techniques like PCA (Principal Component Analysis) to reduce the dimensionality of the data, which can significantly slow down the growth rate. Others use indexing techniques, like inverted files or hash tables, to quickly locate specific vectors, which can reduce the number of possible unique vectors.