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Add Faiss byte vector support blog #3458
Add Faiss byte vector support blog #3458
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Signed-off-by: Fanit Kolchina <[email protected]>
Signed-off-by: Fanit Kolchina <[email protected]>
@pajuric Please edit the meta when you get a chance. Thank you! |
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@kolchfa-aws Editorial review complete. Please see my comments and changes and let me know if you have any questions. Thanks!
Cc: @pajuric
## Future enhancements | ||
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In future versions, we plan to enhance this feature by adding an `on_disk` mode with a `4x` compression level in Faiss. This mode will accept `fp32` vectors as input, perform online training, and quantize the data into byte-sized vectors, eliminating the need for performing external quantization. | ||
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Line 185, first sentence: "compression level in Faiss" => "Faiss compression level"?
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OpenSearch 2.17 introduced support for Faiss byte vectors, enabling you to store quantized byte vector embeddings efficiently. This reduces memory consumption by up to 75%, lowers costs, and maintains high performance. These advantages make byte vectors an excellent choice for large-scale similarity search applications, especially where memory resources are limited, and applications that handle large volumes of data within the signed byte value range. | ||
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## Future enhancements |
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Nit: This section should probably precede the conclusion.
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Done
Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: kolchfa-aws <[email protected]>
Signed-off-by: Fanit Kolchina <[email protected]>
Signed-off-by: kolchfa-aws <[email protected]>
@pajuric Editorial comments addressed. This blog will be ready to publish once we update the meta and date. Thanks! |
Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: kolchfa-aws <[email protected]>
Add Faiss byte vector support blog
Closes #3420
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By submitting this pull request, I confirm that my contribution is made under the terms of the BSD-3-Clause License.