#retrieval-augmented-generation-rag

[ follow ]
#model-context-protocol-mcp #llm-based-labeling #document-ranking #human-in-the-loop-ai #enterprise-search
Data science
fromInfoQ
1 week ago

Scaling Human Judgment: How Dropbox Uses LLMs to Improve Labeling for RAG Systems

Dropbox uses LLM-augmented human labeling to improve document retrieval quality in RAG systems, addressing the bottleneck of ranking millions of enterprise documents for relevance to user queries.
Artificial intelligence
fromTechzine Global
2 months ago

RAG '2.0': the Instructed Retriever links AI agents to the right data

The Instructed Retriever extends RAG to retrieve up to 70% more relevant, context-aware business information while mitigating LLM instruction-following and reasoning shortcomings.
Artificial intelligence
fromInfoQ
2 months ago

NextGen Search - Where AI Meets OpenSearch Through MCP

Search is shifting from keyword-based to semantic, conversational, agentic AI using LLM-powered agents, MCP, and OpenSearch to provide contextual, multi-modal insights.
Artificial intelligence
fromInfoQ
4 months ago

Reducing False Positives in Retrieval-Augmented Generation (RAG) Semantic Caching: A Banking Case Study

Semantic caching stores query-response vector embeddings to reuse answers, reducing LLM calls while improving response speed, consistency, and cost efficiency.
fromDigiday
4 months ago

AI royalties for small and midsize publishers: collective licensing's next big play

Don't credit OpenAI's ChatGPT, credit corporate LLMs - enterprise RAG is what's creating royalty revenue for publishers. RAG - retrieval augmented generation - kicks in when a user (or system) prompts the LLM, which then pulls the relevant content from various sources to deliver the best answer. Over the last two years, it has been quietly expanding its licensing agreements for generative AI usage, with approximately 5,000 publishers from its 30,000-strong publisher network now opted in for this.
Artificial intelligence
Tech industry
fromComputerWeekly.com
5 months ago

Forget training, find your killer apps during AI inference | Computer Weekly

Most organizations will not train AI models in-house; they will focus on production inference, fine-tuning, data curation using RAG, vector databases, prompts, and co-pilots.
Artificial intelligence
fromTechCrunch
5 months ago

New project makes Wikipedia data more accessible to AI | TechCrunch

Wikidata Embedding Project provides vector-based semantic access to nearly 120 million Wikimedia entries, enabling LLMs to query rich, structured knowledge via MCP.
Artificial intelligence
fromComputerWeekly.com
5 months ago

Cloudian launches object storage AI platform at corporate LLM | Computer Weekly

Cloudian's Hyperscale AI Data Platform provides on-premise S3 storage plus Nvidia GPUs and RAG architecture to enable secure, rapid natural-language querying of corporate data.
[ Load more ]