So you guys developed and implemented state of the art neural network vector search from scratch? in a year? and something better than libraries with tens of contributors over years of research?
Most vector search research teams are a lot smaller than you suggest, and haven't been around that long (e.g. the FAISS paper was published in 2017).
From public info, you can see they have at least one researcher working there. It's believable to me that they could have some new innovations, especially since the product space they're focusing on is different from other teams working on vector search. State-of-the-art for a specific set of constraints is still state-of-the-art.
However, considering how much of their edu-marketing content is posted to HN, it would be great if they could share more details about the internals of their index with the community. One of the great things about vector search is how many techniques are open sourced or documented in papers :).
Disclaimer: I work on vector search at a different company
