Tag: Retrieval-Augmented Generation
-
Slashdot: Anthropic Builds RAG Directly Into Claude Models With New Citations API
Source URL: https://slashdot.org/story/25/01/27/2129250/anthropic-builds-rag-directly-into-claude-models-with-new-citations-api Source: Slashdot Title: Anthropic Builds RAG Directly Into Claude Models With New Citations API Feedly Summary: AI Summary and Description: Yes Summary: Anthropic has introduced a new feature called Citations for its Claude models, enhancing their ability to provide accurate and traceable responses by linking answers directly to source documents. This development…
-
Simon Willison’s Weblog: Anthropic’s new Citations API
Source URL: https://simonwillison.net/2025/Jan/24/anthropics-new-citations-api/#atom-everything Source: Simon Willison’s Weblog Title: Anthropic’s new Citations API Feedly Summary: Here’s a new API-only feature from Anthropic that requires quite a bit of assembly in order to unlock the value: Introducing Citations on the Anthropic API. Let’s talk about what this is and why it’s interesting. Citations for Retrieval Augmented Generation…
-
Hacker News: What I’ve learned about writing AI apps so far
Source URL: https://seldo.com/posts/what-ive-learned-about-writing-ai-apps-so-far Source: Hacker News Title: What I’ve learned about writing AI apps so far Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides insights on effectively writing AI-powered applications, specifically focusing on Large Language Models (LLMs). It offers practical advice for practitioners regarding the capabilities and limitations of LLMs, emphasizing…
-
Hacker News: AI Engineer Reading List
Source URL: https://www.latent.space/p/2025-papers Source: Hacker News Title: AI Engineer Reading List Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text focuses on providing a curated reading list for AI engineers, particularly emphasizing recent advancements in large language models (LLMs) and related AI technologies. It is a practical guide designed to enhance the knowledge…
-
Docker: Meet Gordon: An AI Agent for Docker
Source URL: https://www.docker.com/blog/meet-gordon-an-ai-agent-for-docker/ Source: Docker Title: Meet Gordon: An AI Agent for Docker Feedly Summary: We share our experiments creating a Docker AI Agent, named Gordon, which can help new users learn about our tools and products and help power users get things done faster. AI Summary and Description: Yes Summary: The text discusses a…
-
Cloud Blog: Introducing Vertex AI RAG Engine: Scale your Vertex AI RAG pipeline with confidence
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/introducing-vertex-ai-rag-engine/ Source: Cloud Blog Title: Introducing Vertex AI RAG Engine: Scale your Vertex AI RAG pipeline with confidence Feedly Summary: Closing the gap between impressive model demos and real-world performance is crucial for successfully deploying generative AI for enterprise. Despite the incredible capabilities of generative AI for enterprise, this perceived gap may be…
-
Hacker News: KAG – Knowledge Graph RAG Framework
Source URL: https://github.com/OpenSPG/KAG Source: Hacker News Title: KAG – Knowledge Graph RAG Framework Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text introduces KAG (Knowledge Augmented Generation), a framework leveraging large language models (LLMs) to enhance logical reasoning and Q&A capabilities in specialized domains. It overcomes traditional challenges in vector similarity and graph…
-
Irrational Exuberance: Wardley mapping the LLM ecosystem.
Source URL: https://lethain.com/wardley-llm-ecosystem/ Source: Irrational Exuberance Title: Wardley mapping the LLM ecosystem. Feedly Summary: In How should you adopt LLMs?, we explore how a theoretical ride sharing company, Theoretical Ride Sharing, should adopt Large Language Models (LLMs). Part of that strategy’s diagnosis depends on understanding the expected evolution of the LLM ecosystem, which we’ve build…