Vector Embeddings for Machine Learning

The VVA doesn't search through data by keywords, but rather through its meaning. And it uses vector embeddings as a tool for that. So without any SIMD, we can use something called the dot product. The dot product is a simple calculation where basically you multiply each element of the first vector with the same corresponding element of the second vector and then sum up all of those elements.