Скачать с ютуб How RAG (Retrieval-Augmented Generation) talks with your private data using LLM | AI Heroes 2023 в хорошем качестве

How RAG (Retrieval-Augmented Generation) talks with your private data using LLM | AI Heroes 2023

🎟️ 2024 ticket SPECIAL PRICE: https://ticket.synesthesia.it/events/... More information: https://aiheroes.it/2024/ ⏩ Chapter: 00:00 intro 03:13 Retrieval-Augmented Generation (RAG) 03:42 Generation part 05:48 Retrieval-Augmented 07:10 RAG diagram 09:09 What is a vector & Similarity? 12:21 Embedding 14:34 Vector databases available 15:24 Vector database + LLM 16:41 Split the documents in chunk 17:45 Text splitter 19:18 LangChain 21:15 DEMO: Build a RAG using LangChain + ChatGPT + Elasticsearch 23:20 Installing some dependencies 25:04 Compare vectors 27:10 Loading PDF document 27:55 Split the document in Chunks 29:14 Vector search 29:54 Chat with your data and get the answers with document and resource In this presentation, we will introduce a recent proposal in AI that is called Retrieval-Augmented Generation (RAG). This technique is able to leverage the natural language capabilities of Large Language Model (LLM) such as ChatGPT in order to query a private database. You can literally ask question about your data, without the need to fine-tune an LLM with all your private data. We will show also an example of RAG using Langchain, an open source framework for writing applications for LLM. We will execute a demo with a few lines of Python to chat with private data using a vector database like Chroma or Elasticsearch. 🎤 ENRICO ZIMUEL, Principal Software Engineer, Elastic 📍AI Heroes was hosted in Turin, 1 December. Attended by 240+ participants and broadcast to an additional 50+ participants. The event was highly interactive with excellent presentations, high value networking and lots of engagement between the participants. ✅ Tweet:   / aiheroes_it   ✅ Connect:   / aiheroes-it   ✅ Read: https://t.me/aiheroes #aiheroes #RetrievalAugmentedGeneration #machinelearning #langchain #aimodels #chatgpt #llms #elasticsearch #VectorDatabase #aiengineering #pythondevelopment