FeaturedHallucination
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.
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Improving Customer Support with AI: A Deep Dive into Conversational AI
Discover the transformative impact of Conversational AI, including its evolution, current trends, and role in revolutionizing customer support. If you’re thinking about why and how to adopt this technology for customer support, we offer some insights
Retrieval Augmented Generation Buyer's Guide
Regardless of whether you are considering building or buying a RAG solution, you need to understand the players, their offerings, where they accel, and where they are still trying to catch up
Retrieval Augmented Generation (RAG) Done Right: Document Stores
Building a RAG pipeline with Vectara and Elasticsearch
Retrieval Augmented Generation (RAG) Done Right: Database Data
Ingesting data from your database into Vectara: a step by step guide.
Get Diverse Results and Comprehensive Summaries with Vectara’s MMR Reranker
Today, we’re incredibly excited to announce that we’re releasing a new “reranking” capability built into Vectara: one that’s focused on increasing the amount of diversity of the results near the top of the result list.
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
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