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Opensearch datastax blog post, new member bits #2946

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Update _posts/2024-06-06-opensearch-partnering-with-datastax-on-gener…
…ative-ai.md

Co-authored-by: Nathan Bower <[email protected]>
Signed-off-by: Nate McCall <[email protected]>
zznate and natebower authored Jun 13, 2024

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commit 8bb24276e6b0f12add666466d41b1e302aa8666e
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Amazon sponsors OpenSearch to ensure the continuing existence => Amazon sponsors the OpenSearch project

that users could use, modify, and extend however they wish => could use -> can use

The OpenSearch community is full of active contributors, maintainers, and partners => In addition to AWS, the OpenSearch community ...

OpenSearch supports hybrid vector/text search with score normalization, and sparse vector search => OpenSearch supports semantic search with vector embeddings, multi-modal search, hybrid search with score normalization, and sparse vector search.

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Thanks for the review! Suggested changes have been made and have merged latest.

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Thanks @zznate!

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@@ -16,7 +16,7 @@ has_science_table: false

DataStax and the OpenSearch Project team are announcing a series of integration efforts to support Generative AI developers. Retrieval Augmented Generation (RAG) is a key design pattern in Generative AI. RAG Applications work by assembling context from a variety of sources, which is then processed by an LLM to provide an intelligent and relevant response. Serving these applications requires a mix of data retrieval and storage capabilities and we, OpenSearch and DataStax, are committed to working together to serve the broad needs of Generative AI developers.
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To power the explosive growth within the Generative AI space, we need to keep innovating on the tooling available to developers. These tools require access to a variety of enterprise data and we want to be there to provide that access in whatever common format is required. Being able to retrieve data in the most flexible ways possible is a necessary catalyst for getting RAG and GenAI knowledge applications to production.
To power the explosive growth within the generative AI space, we need to keep innovating on the tooling available to developers. These tools require access to a variety of enterprise data, and we want to be there to provide that access in whatever common format is required. Being able to retrieve data in the most flexible ways possible is a necessary catalyst for getting RAG and generative AI knowledge applications to production.

Amazon sponsors the OpenSearch project to ensure the continuing existence of an open source search engine that users can use, modify, and extend however they wish. In addition to AWS, the OpenSearch community is full of active contributors, maintainers, and partners. For Generative AI specifically, OpenSearch brings:
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