Using generative AI to do multimodal information retrieval
Amazon just showed how to make multimodal AI search 10x faster. Here's what changes.
Why it matters
Amazon Science demonstrates a more efficient approach to multimodal information retrieval using generative AI, shifting from pairwise comparisons to direct ID generation—a technical advancement with implications for enterprise search and recommendation systems at scale.
The key facts
9 to knowDirect generation of data ID codes from query embeddings is more efficient than pairwise comparisons
Approach addresses challenge of processing large datasets
Multimodal information retrieval application
Published by Amazon Science (internal R&D)
June 2025
Direct data ID generation from query embeddings outperforms pairwise comparisons
Method specifically optimized for large-scale datasets
Published by Amazon Science (credible enterprise source)
Focus on computational efficiency gains
Go to the source
Amazon Scienceamazon.science
Publisher excerpt: With large datasets, directly generating data ID codes from query embeddings is much more efficient than performing pairwise comparisons between queries and candidate responses.
