Retrieval-augmented generation (RAG) has become a go-to architecture for companies using generative AI (GenAI). Enterprises adopt RAG to enrich large language models (LLMs) with proprietary corporate ...
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 ...
The advent of transformers and large language models (LLMs) has vastly improved the accuracy, relevance and speed-to-market of AI applications. As the core technology behind LLMs, transformers enable ...
The hype and awe around generative AI have waned to some extent. “Generalist” large language models (LLMs) like GPT-4, Gemini (formerly Bard), and Llama whip up smart-sounding sentences, but their ...
How to implement a local RAG system using LangChain, SQLite-vss, Ollama, and Meta’s Llama 2 large language model. In “Retrieval-augmented generation, step by step,” we walked through a very simple RAG ...
Ten AI concepts to know in 2026, including LLM tokens, context windows, agents, RAG, and MCP, for building reliable AI apps.
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