RAG

AI CosmosDB Large Language Models

Ask The Expert: Intelligent Apps with Azure Cosmos DB (APAC Replay)

Join the Azure Cosmos DB team for an engaging session on the versatile vector database capabilities of Azure Cosmos DB. Discover the seamless integration of your operational and transactional data with native vector indexing and search functionalities, specifically tailored for AI applications. Learn how to build RAG pattern solutions and manage chat history by seamlessly […]

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AI Generative AI Large Language Models

Why You Need Better Knowledge Graphs for Your RAG

This video is from Leann Chen. RAG (Retrieval-Augmented Generation) has become the hype of Generative AI applications, so are knowledge graphs. You see lots of graph-based LLM apps out there and you’re probably building one too. However, how you construct knowledge graphs determines the quality of your LLM-based application. Solely relying on GPT-4 for extracting […]

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AI Generative AI Large Language Models

Uncovering the Power of RAG: A Guide to Retrieval Augmented Generation

This video is from Don Woodlock. How do you create an LLM that uses your own internal content? You can imagine a patient visiting your website and asking a chatbot: “How do I prepare for my knee surgery?” And instead of getting a generic answer from just ChatGPT, the patient receives an answer that retrieves […]

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AI Livestream

Happy Valentine’s Day

This video is from FranksWorldTV.

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AI Azure Generative AI

Revolutionize RAG and Search with Azure AI Document Intelligence

This video is from Global AI Community. Retrieval Augmented Generation (RAG) is a design pattern commonly used in Document Generative AI (e.g., chat with your document). Semantic chunking is a key step in RAG to get efficient storage and retrieval. The session will introduce the latest capabilities provided by Azure AI Document Intelligence to enable […]

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AI Large Language Models

Stanford CS25: V3 I Retrieval Augmented Language Models

Language models have led to amazing progress, but they also have important shortcomings. One solution for many of these shortcomings is retrieval augmentation. I will introduce the topic, survey recent literature on retrieval augmented language models and finish with some of the main open questions. via Stanford Online.

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Big Data Data Databricks

Introduction to Vector Search

High level introduction to Vector Search from Databricks. Brief demonstration of how to index a Delta table and execute similarity search using Databricks Vector Search’s new offering.

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AI Economics of AI Large Language Models

How to Summarize Legal Docs like a Pro with Mixtra’s RAG Pipeline

This video from Mervin Praison shows that the legal profession will never be the same Post-AI. Welcome to an innovative journey in the legal tech world! In today’s video, I’m thrilled to show you how to create a chatbot that can summarize and query legal documents. This is a game-changer for lawyers and legal professionals, […]

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AI Large Language Models

How to Build Production-Ready RAG Applications: Jerry Liu

This video is from AI Engineer. Large Language Models (LLM’s) are starting to revolutionize how users can search for, interact with, and generate new content. Some recent stacks and toolkits around Retrieval Augmented Generation (RAG) have emerged where users are building applications such as chatbots using LLMs on their own private data. This opens the […]

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