This is the first blog post in a series on hybrid search. This first post focuses on efficient hybrid retrieval and representational approaches in IR...
A new search experience for Vespa-related content - powered by Vespa, LangChain, and OpenAI’s chatGPT model - our motivation for building it, features, limitations, and...
This post demonstrates how to use recently announced BGE embedding models in Vespa. We evaluate the effectiveness of two BGE variants on the BEIR trec-covid...
In this post, we’ll see how to accelerate embedding inference and retrieval with little impact on quality. We’ll take a holistic approach and deep-dive into...
We are thrilled to announce significant updates to Vespa’s support for inference with text embedding models that maps texts into vector representations.
Announcing global-phase re-ranking support in Vespa, unlocking efficient re-ranking with precise cross-encoder models. Cross-encoder models minimize distraction in retrieval-augmented completions generated by Large Language Models....
Deep-learned embeddings are popular for search and recommendation use cases. This post introduces the concept of using reusable frozen embeddings and tailoring them with Vespa....
Announcing multi-vector indexing support in Vespa, which allows you to index multiple vectors per document and retrieve documents by the closest vector in each document....
Distilling the knowledge and power of generative Large Language Models (LLMs) with billions of parameters to ranking models with a few million parameters.
If you are planning to implement search functionality but have not yet collected data from user interactions to train ranking models, where should you begin?...
This blog post describes how your organization can unlock the full potential of multimodal AI-powered vector representations using Vespa -- the industry-leading open-source big data...
This blog post describes Vespa's industry leading support for combining approximate nearest neighbor search, or vector search, with query constraints to solve real-world search and...
Part one in a blog post series on billion-scale vector search. This post covers using nearest neighbor search with compact binary representations and bitwise hamming...
This is the fourth blog post in a series of posts where we introduce using pretrained Transformer models for search and document ranking with Vespa.ai....
This is the third blog post in a series of posts where we introduce using pretrained Transformer models for search and document ranking with Vespa.ai....
This is the second blog post in a series of posts where we introduce using pretrained Transformer models for search and document ranking with Vespa.ai....
This is the first blog post in a series of posts where we introduce using pretrained Transformer models for search and document ranking with Vespa.ai....
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