[rm999]

>A "vector" in vector search solutions is a dense vector generated by a transformer model.

Just a clarification that vectors are much broader than text vectors generated by transformer models. A more common application has been recommender models built on matrix factorization and other similar approaches. Word 2 Vec was another popular way to generate vectors dating back to 2013. Vectors are a very general approach with many benefits regardless of how they were generated. That is what makes these vector search libraries so exciting.

I wrote an article about the power of matrix factorization vectors for music recommendations back in 2016: https://tech.iheart.com/mapping-the-world-of-music-using-mac...

We also discussed how we used convolutional neural networks (deep networks, but not transformers) to build vectors on the acoustic content of music: https://tech.iheart.com/mapping-the-world-of-music-using-mac...