1/ If you're into ML, hosting vector search databases can be expensive. At a super high level, an ML algorithm converts content (text, images, or audio) into v

1/ If you're into ML, hosting vector search databases can be expensive. At a super high level, an ML algorithm converts content (text, images, or audio) into vectors (aka embeddings). Similar content should generate similar embeddings, so a large RAM lets you keep more embeddings in memory allowing more search. Large ram also makes training models easier. 2/ Data leaks can be fun to explore, but are often gigabytes of data. More ram makes them faster to query.