[vineyardmike]

> If you’re going to be creating embeddings for similarity search, the first thing you need to ask yourself is what makes two vectors similar such that two embeddings should even be close together?

I have no association with Cohere, but in their docs clearly say that their embedding were trained so two similar vectors have similar "semantic meaning". Which is still pretty vague, but it's at least clear what their goals were.

> Selling “embeddings as a service” is a bit like selling hashing as a service.

Coincidentally, Cohere also aggressively advertises that they want you to fine-tune and co-develop custom models (with their proprietary services).

[nostrebored]

But this is the GPs point — that doesn’t mean they’re optimized for retrieval.