What if your AI could not only retrieve information but also uncover the hidden relationships that make your data truly meaningful? Traditional vector-based retrieval methods, while effective for ...
Microsoft is making publicly available a new technology called GraphRAG, which enables chatbots and answer engines to connect the dots across an entire dataset, outperforming standard ...
Anthropic’s Model Context Protocol (MCP) and Microsoft’s GraphRAG are emerging as complementary approaches to improve AI-assisted academic research. MCP enables large language models to connect ...
While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...
Anthropic’s Model Context Protocol (MCP) is standardizing how LLMs connect to tools, APIs, and databases, but risks like tool overload and context gaps remain. Experts suggest combining MCP with graph ...
When I first wrote “Vector databases: Shiny object syndrome and the case of a missing unicorn” in March 2024, the industry was awash in hype. Vector databases were positioned as the next big thing — a ...
Generative AI depends on data to build responses to user queries. Training large language models (LLMs) uses huge volumes of data—for example, OpenAI’s GPT-3 used the CommonCrawl data set, which stood ...
It would be a gross oversimplification—and a great disservice to the profession—to consider the next generation of KM solely in terms of new breakthrough technologies. Autonomous agents, language ...
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