Mistral launches new code embedding model that outperforms OpenAI and Cohere in real-world retrieval tasks
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retrieval
Visa’s AI edge: How RAG-as-a-service and deep learning are strengthening security and speeding up data retrieval
Visa has reduced data retrieval from hours to mere minutes and blocked $40 billion in fraud thanks to gen AI…
Evaluating Retrieval Augmented Generation for large-scale codebases
In a previous post, we introduced our approach to building a RAG-based system—designed to power generative AI coding…
more accurate code retrieval with lower dimensional, quantized embeddings – Voyage AI
TL;DR – Introducing voyage-code-3, our next-generation embedding model optimized for code retrieval. It outperforms OpenAI-v3-large and CodeSage-large by an average…
OpenSPG/KAG: KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.
English | 简体中文 | 日本語版ドキュメント KAG is a logical reasoning and Q&A framework based on the OpenSPG engine and large…
Introducing cascading retrieval: Unifying dense and sparse with reranking
We’re excited to announce new cascading retrieval capabilities, further advancing AI search applications. These enhancements make it seamless to combine…
Pinecone expands vector database with cascading retrieval, boosting enterprise AI accuracy by up to 48%
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Breaking the cloud backup ‘black box’ with intelligent data mapping and retrieval
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