
Vectara recognized for model development and AI knowledge management
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Vectara recognized for model development and AI knowledge management
Read more
Hybrid search has the power to vastly improve in-app experience allowing users to find what they are looking for quickly, and allows tuning between semantic and lexical search

TL;DR In this blogpost we cover the importance of retrieval models for search and generative AI use-cases, and we announce the release of our new state-of-the-art multilingual retrieval model, named Boomerang, that is available for use in the Vectara platform. We compare performance numbers between Boomerang and several other embedding APIs and models and demonstrate Boomerang’s high quality retrieval and generalization capabilities. Finally we discuss real-life quality improvements seen by a Vectara design partner for their use-case.

For app developers and product managers, implementing hybrid search into your application can be a game-changer for findability and improved user experiences. We break down the process of implementation, best practices, and considerations for when you want to bring hybrid search to your products and users.

Traditional approaches for eCommerce search have hit their limits, especially when there is a wide variety of products and services and wide variability in how they are described. We explored technical options to tackle this issue, and found that combining traditional keyword based approaches with modern semantic search techniques yielded the best results

Dive deep into the mechanics of Vector Search, where data meets geometry to redefine the future of search algorithms.

Rethinking the human-computer interface in the era of GenAI

Seeking knowledge about our world is something that all of us need. It is a task that goes back to the dawn of human civilization, ever since we figured out…

Natural language processing can ease common frustrations while delivering relevant answers and unexpected insights.

Semantic search, based on deep neural networks, is changing information retrieval.
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