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Tag: AWS

  • Use private data securely with an LLM

    Use private data securely with an LLM

    Large language models (LLMs) are amazing but one shortcoming is that they wont be able to answer questions related to your private data. This is where RAG or retrieval-augmented generation comes in. RAG is a technique that lets you use LLMs with your private data. Dont roll your own RAG RAG architecture has quite a…

  • Power up LLM bots with RAG + Hybrid search

    Power up LLM bots with RAG + Hybrid search

    Retrieval-Augmented Generation or RAG is important because it helps LLMs give more accurate answers by also including content (or context) from your private data. See this post on how you can implement RAG quickly and securely. With RAG, your private data is stored as an embedding in a vector database. Depending on the user query,…

  • Build highly scalable AI platforms like the Deutsche Bahn

    Build highly scalable AI platforms like the Deutsche Bahn

    Deutsche Bahn has developed an AI platform that is scalable, secure, and efficient. They have a dedicated AI platform team and their focus was on rapid project initiation, reduced maintenance costs, and effective management of AI and machine learning tools across diverse data analytics teams. AWS Sagemaker has helped them achieve their goals. For an…