> It also makes it easier for AWS to comply with censorship requirements.

Does it, how? Why would it be the vector store that would make it easier for them to censor the content? Why not censor the documents in S3 directly, or the entries in the relational database. What is different about censoring those vs a vector store?

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resters 4 days ago | parent [-]

Once a vector has been generated (and someone has paid for it) it can be searched for and relevant content can be identified without AWS incurring any additional cost to create its own separate censorship-oriented index, etc. AWS can also add additional bits to the vector that benefit its internal goals (scalability, censorship, etc.)

Not to mention there is lock-in once you've gone to the trouble of using a specific embedding model on a bunch of content. Ideally we'd converge on backwards-compatible, open source approaches, but cloud vendors want to offer "value" by offering "better" embedding models that are not open source.

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simonw 4 days ago | parent | next [-]

Why would they do that? Doesn't sound like something that would attract further paying customers.

Are there laws on the books that would force them to apply the technology in this way?

	▲	resters 4 days ago \| parent [-]
		Not official laws that we can read, but things like that are already in place per the Snowden revelations.

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whakim 4 days ago | parent | prev | next [-]

Regardless of the merits of this argument, dedicated vector databases are all running on top of AWS/GCP/Azure infrastructure anyways.

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barbazoo 4 days ago | parent | prev | next [-]

And that doesn't apply to any other database/search technology AWS offers?

	▲	resters 4 days ago \| parent [-]
		It does to some but not to most of it, which is why Azure and GCP offer nearly the exact same core services.

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3 days ago | parent | prev [-]

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