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249 points colesantiago | 1 comments | | HN request time: 0.793s | source
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ot ◴[] No.40751253[source]
Very unexpected acquisition. I don't think that Rockset is a suitable infrastructure for RAG, a purpose-built inverted index would be far more efficient (both in terms of compute and storage), so I'm not sure how much of the technology would actually be useful for them.

I can think of two options

- Pure acqui-hire: virtually all of Rockset engineering leadership is ex-Meta, and OpenAI has been hiring several senior infra engineers from Meta, so these are all people that have worked together previously.

- OpenAI is building some product where customers can ingest large amounts of data, which could be managed by the Rockset infrastructure as source of truth, and then indexed by their RAG systems.

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simonw ◴[] No.40751908[source]
RAG doesn't have to involve vector search.

The (very thin) blog post said "Enhancing our retrieval infrastructure" - my guess is this is more about other forms of retrieval, like constructing and executing SQL queries and using the results to help answer questions.

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zurfer ◴[] No.40752396[source]
Last time I heard of Rockset was at the Snowflake Summit where they positioned as a faster DWH.

Looking at the landing page now it seems they almost pivoted into semi/unstructed data.

To your point, I feel like nobody knows exactly how to do RAG really well (fast and accurate). I also doubt the Rockset team has it figured out but it seems like there is an opportunity to build a new kind of database/memory system and OpenAI believes the Rockset team can help.

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1. ethbr1 ◴[] No.40753687[source]
I think OpenAI also realized they're an AI major without a dance partner, when it comes to context.

Google (Android, Gmail, Maps, G Office), Apple (iPhone, Mail, Maps, Productivity), Microsoft (Office365, Windows, XBox).

In terms of moat and lock-in, that leaves OpenAI vulnerable to last mile customer hijacking.