Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now When large language models (LLMs) emerged, ...

A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used ...

Alexander Slagg is a freelance writer specializing in technology and education. He is an ongoing contributor to the CDW family of magazines. Agencies awash in oceans of data might seem like an ideal ...

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 ...

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...

RAG can make your AI analytics way smarter — but only if your data’s clean, your prompts sharp and your setup solid. The arrival of generative AI-enhanced business intelligence (GenBI) for enterprise ...

As the AI infrastructure market evolves, we’ve been hearing a lot more about AI inference—the last step in the AI technology infrastructure chain to deliver fine-tuned answers to the prompts given to ...

Memgraph, a leader in open-source, in-memory graph databases, is introducing a new capability designed to accelerate business adoption of graph-based retrieval-augmented generation (GraphRAG), Atomic ...

To operate, organisations in the financial services sector require hundreds of thousands of documents of rich, contextualised data. And to organise, analyse and then use that data, they are ...

This free eBook that covers enhancing generative AI systems by integrating internal data with large language models using RAG is free to download until 12/3. Claim your complimentary copy of ...