Introduction Large Language Models (LLMs) such as ChatGPT, Gemini, and Claude are...
RAG integra il retrieval di documenti aziendali negli LLM per risposte accurate su dati privati, senza fine-tuning costoso. Riduce hallucination, abilita aggiornamenti real-time della knowledge base, protegge dati sensibili e abbatte i costi di manutenzione.
Introduction
Large Language Models (LLMs) such as ChatGPT, Gemini, and Claude are incredibly powerful. They can answer questions, generate code, summarize documents, and assist with various tasks.
However, they have one major limitation:
They only know what they were trained on.
If you ask them about your company's internal documents, private PDFs, or the latest information that wasn't part of their training data, they may provide incorrect answers or simply not know the answer.
Why retrieval-augmented generation has become the foundational pattern for building useful AI — and...
Introduction: The Place of Large Models in RAG and Lingering Questions Retrieval-Augmented...
RAG sounds complicated. It's not. But a lot of introductions to RAG make it sound more mysterious...
Large language models are confidently wrong about anything they were not trained on: your internal...
You ask ChatGPT about your company's internal policies. It makes something up. It sounds confident....
In this post we'll explore the basics of retrieval augmented generation by creating an example app that uses bge-large-en for…
