vector database

AI Generative AI Large Language Models

RAG Explained

Oftentimes, GAI and RAG discussions are interconnected. Learn more about about RAG is and how it works alongside your databases, LLMs and vector databases for better results with Luv Aggarwal and Shawn Brennan. AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdmP2c

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AI Large Language Models

Armchair Architects: LLMs & Vector Databases (Part 2)

In this episode of the Azure Enablement Show, Uli, Eric and David continue their discussion of vector databases and LLMS, including when to use prompt engineering, and the importance of fine-tuning your data. Uli suggests that there are two things that LLMs aren’t good at, then offers tips on workarounds. The conversation wraps up with […]

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AI Generative AI Large Language Models

Episode 2: Indexes in LlamaIndex

This video from Weaviate • Vector Database covers the three indexes (Vector Store Index, List Index, and Tree Index) and walk through the architecture design. The video ends with a demo using the Vector Store Index and List Index. You can clone the notebook here to get started: https://github.com/weaviate/recipes/tree/main/integrations/llamaindex/indexes-episode2

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AI Large Language Models

LlamaIndex and Weaviate – Episode 1: Data Loading

This video is from Weaviate • Vector Database. We will walk through three examples of using LlamaIndex’s data loaders for reading files from a file system, webpage, and Notion! We then pipe this data into Weaviate! The full list of data loaders hosted on LlamaHub is here: https://llama-hub-ui.vercel.app/ Further, this video will show how to […]

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AI Azure Generative AI Large Language Models

Armchair Architects: LLMs & Vector Databases (Part 1)

Vector databases are designed to store, manage, and index massive quantities of high-dimensional vector data efficiently that can help different types of queries, such as nearest neighbor. In this episode of the Azure Enblement Show, Uli, Eric and David discuss how vector databases convert data to integers, cover some of the use cases of vector […]

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CosmosDB

How to Building a vector similarity search app with Azure AI Vision and PostgreSQL

Vector search is a method that helps you find similar items based on their content rather than exact matches on properties like keywords, tags, or other metadata, as keyword-based search systems do. In this session, we will discuss vector search with Azure AI Vision and Azure Cosmos DB for PostgreSQL. This video is from Azure […]

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AI Data

OpenAI Embeddings and Vector Databases Crash Course

This video is from Adrian Twarog. Embeddings and Vectors are a great way of storing and retrieving information for use with AI services. OpenAI provides a great embedding API to do this. Postman lets you make these with easy at https://www.postman.com/ (today’s sponsor) In this video we will explore how to create a Vector Database […]

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AI Data

Vector databases are so hot right now. WTF are they?

Vector databases are rapidly growing in popularity as a way to add long-term memory to LLMs like GPT-4, LLaMDA, and LLaMA. Learn how popular vector databases like Pinecone and Weaviate can store ML embeddings to integrate with tools like ChatGPT.

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AI Data

Vector Databases simply explained! (Embeddings & Indexes)

This video is from AssemblyAI. Vector Databases simply explained. Learn what vector databases and vector embeddings are and how they work. Then I’ll go over some use cases for it and I briefly show you different options you can use.

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