Introducing Search Toolkit★ 72
Mistral AI News6 days agoNew ToolMistral AI introduced Search Toolkit in public preview as a composable framework for AI search infrastructure. It unifies ingestion, retrieval, and evaluation with support for parsing, chunking, embeddings, BM25, dense retrieval, hybrid search, and standard retrieval metrics. The toolkit targets enterprise search, RAG quality improvement, and domain-specific retrieval, with a starter app using Docker, uv, and Vespa.
Unlocking dependable responses with Gemini Enterprise Agent Platform’s Agentic RAG★ 72
Google Research Blog9 days agoReleaseGoogle Research and Google Cloud introduced an agentic RAG framework hosted on Gemini Enterprise Agent Platform. It uses multiple agents to plan, rewrite, route, retrieve, verify sufficient context, iterate, and synthesize answers. Google reports up to 34% factuality accuracy gains over standard RAG, plus 90.1% accuracy in a cross-corpus FramesQA setting with similar latency to single-corpus retrieval.
IBM 發布 Granite Embedding Multilingual R2：具備 32K 上下文與 Apache 2.0 授權，100M 參數以下最強多語言嵌入模型★ 75
Hugging Face Blog30 days agoReleaseIBM has officially released a new multilingual embedding model on the Hugging Face platform called "Granite Embedding Multilingual R2." The model's most…
Hugging Face 推出 RTEB：全新檢索評估標準，為 RAG 系統打造更真實的測試基準★ 80
Hugging Face Blog256 days agoReleaseAs Retrieval-Augmented Generation (RAG) becomes the dominant architecture for enterprises deploying large language models (LLMs), accurately evaluating the…