Tag: retrieval accuracy

  • Hacker News: voyage-code-3

    Source URL: https://blog.voyageai.com/2024/12/04/voyage-code-3/ Source: Hacker News Title: voyage-code-3 Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents voyage-code-3, a new embedding model optimized for code retrieval that significantly outperforms existing models in both performance and cost-efficiency. The introduction of Matryoshka learning and advanced quantization techniques allows for reduced storage requirements without compromising…

  • Hacker News: All-in-one embedding model for interleaved text, images, and screenshots

    Source URL: https://blog.voyageai.com/2024/11/12/voyage-multimodal-3/ Source: Hacker News Title: All-in-one embedding model for interleaved text, images, and screenshots Feedly Summary: Comments AI Summary and Description: Yes Summary: The text announces the release of voyage-multimodal-3, a cutting-edge multimodal embedding model that enhances the capability of semantic search and retrieval tasks involving both text and images. Its ability to…

  • Simon Willison’s Weblog: Binary vector embeddings are so cool

    Source URL: https://simonwillison.net/2024/Nov/11/binary-vector-embeddings/#atom-everything Source: Simon Willison’s Weblog Title: Binary vector embeddings are so cool Feedly Summary: Binary vector embeddings are so cool Evan Schwartz: Vector embeddings by themselves are pretty neat. Binary quantized vector embeddings are extra impressive. In short, they can retain 95+% retrieval accuracy with 32x compression and ~25x retrieval speedup. It’s so…