But embedding-based semantic search can handle arbitrary sized databases. I fully believe context windows are going to grow: I am skeptical they will grow to cover "all your company's documents" or even "the full encyclopedia" sizes.
> I fully believe context windows are going to grow: I am skeptical they will grow to cover "all your company's documents" or even "the full encyclopedia" sizes.
This is the type of statement that I feel like is often/usually wrong -- at least for the common case. The last time I had this argument was about CDs and how eventually we'll start burning them because they'll be in the cloud, and my friend arguing that storage and network bandwidth would make that impractical if everyone did it.
I expect context window compression or smart ways to embed them so they still provide useful context in "most" cases, even if not-lossless, will be an active area of research.
EDIT: That said, looking a the original question -- I do think vector embeddings are still useful in their own right and somewhat orthogonal to context window sizes. IMO.
