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Blog - page 16
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Cut the Bull... Detecting Hallucinations in Large Language Models
Vectara launches the open source Hughes Hallucination Evaluation Model (HHEM) and uses it to compare hallucination rates across top LLMs including OpenAI, Cohere, PaLM, Anthropic’s Claude 2 and more.
Top Large Language Models (LLMs): GPT-4, LLaMA 2, Mistral 7B, ChatGPT, and More
The top large language models along with recommendations for when to use each based upon needs like API, tunable, or fully hosted.
Retrieval Augmented Generation (RAG) Done Right: Retrieval
In RAG, retrieving the right facts from your data is crucial, and choosing the right embedding model to power your retrieval matters!
Learning to Measure AI Search with Vectara
AI-powered search is everywhere – new projects, products and companies are appearing to solve age-old challenges. But how ‘good’ is an AI-powered search engine – and how can we measure this?
Using Hybrid Search to Improve In-App Product Search
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
How Vectara's New Boomerang Model Takes Retrieval Augmented Generation to the Next Level via Grounded Generation
Learn about the benefits of Vectara’s new embedding model “Boomerang,” including how our version of Retrieval Augmented Generation (RAG), called Grounded Generation, is smarter than other systems
Introducing Boomerang – Vectara’s New and Improved Retrieval Model
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.
Retrieval Augmented Generation (RAG) Done Right: Chunking
How to properly chunk your text data to optimize performance of retrieval augmented generation
How to Implement Hybrid Search Into Your Product for Better Customer Experiences
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.
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