21–24 of 24 posts
By exposing my database to services somewhere else in the network. Oh and somewhere else is the US.
Fat chance in hell I can anyone in my company look at that or even think about legally applying it with some serious data. (I'm in EU. Yes, a lot of people and companies use US services. Currently it looks like NONE of these can legally do.)
It looks interesting, but it needs a on premise solution.
I had a look, so how would I bring my data into it. By exposing my database to services somewhere else in the network. Oh and somewhere else is the US. Fat chance in hell I can anyone in my company look at that or even think about legally applying it with some serious data. (I'm in EU. Yes, a lot of people and companies use US services. Currently it looks like NONE of these can legally do.) It looks interesting, but…
I had a look, so how would I bring my data into it. By exposing my database to services somewhere else in the network. Oh and somewhere else is the US. Fat chance in hell I can anyone in my company look at that or even think about legally applying it with some serious data. (I'm in EU. Yes, a lot of people and companies use US services. Currently it looks like NONE of these can legally do.) It looks interesting, but…
For the cloud platform though (console.shaped.ai), i'd recommend just testing with some synthetic or deanonymized data or our demos and then if you're interested in BYOC reach out after April!
Is there a major difference between pgvector and shapedql?
You can think of Shaped more like a vector store + feature store + ML inference combined into one service. This bundling is what makes it so easy to get state-of-the art real-time recommendations and search performance. E.g imagine trying to build a feed with pgvector, you need to build all of the vector encoding logic for your catalog, then you need to build user embeddings, the models to represent that and then hav…