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# vectordatabase

Vector databases are purpose-built databases that are specialized to tackle the problems that arise when managing vector embeddings in production scenarios.

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LLM Models and RAG Applications Step-by-Step - Part III - Searching and Injecting Context

LLM Models and RAG Applications Step-by-Step - Part III - Searching and Injecting Context

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11 min read
Implementing Complex Semantic Search with MongoDB

Implementing Complex Semantic Search with MongoDB

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4 min read
OpenRAG: An Open-Source GenAI Application to Supercharge Data Queries with Large Language Models

OpenRAG: An Open-Source GenAI Application to Supercharge Data Queries with Large Language Models

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3 min read
Move your data into (or out of) ANY Vector Database

Move your data into (or out of) ANY Vector Database

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1 min read
Azure Index AI & MS Fabric

Azure Index AI & MS Fabric

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15 min read
AIM Weekly for 16 Sept 2024

AIM Weekly for 16 Sept 2024

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2 min read
Generative Audio

Generative Audio

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8 min read
Speech to Speech RAG

Speech to Speech RAG

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4 min read
Text to IRIS SQL with LangChain

Text to IRIS SQL with LangChain

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18 min read
ColBERT Live! Makes Your Vector Database Smarter

ColBERT Live! Makes Your Vector Database Smarter

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8 min read
Exploring RAG: Why Retrieval-Augmented Generation is the Future?

Exploring RAG: Why Retrieval-Augmented Generation is the Future?

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2 min read
Debunking 6 common pgvector myths

Debunking 6 common pgvector myths

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9 min read
Open source semantic embedding, search & clustering in NodeJS

Open source semantic embedding, search & clustering in NodeJS

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3 min read
AIM Weekly 19 August 2024

AIM Weekly 19 August 2024

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8 min read
Word-embedding-with-Python: doc2vec

Word-embedding-with-Python: doc2vec

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2 min read
Exploring Word Embeddings: python implementation of Word2Vec and GloVe in Vector Databases

Exploring Word Embeddings: python implementation of Word2Vec and GloVe in Vector Databases

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5 min read
Semantic Search and Algorithms

Semantic Search and Algorithms

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3 min read
From Notebook to Serverless: Creating a Multimodal Search Engine with Amazon Bedrock and PostgreSQL

From Notebook to Serverless: Creating a Multimodal Search Engine with Amazon Bedrock and PostgreSQL

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3 min read
Desplegando una Aplicación de Embeddings Serverless con AWS CDK, Lambda y Amazon Aurora PostgreSQL

Desplegando una Aplicación de Embeddings Serverless con AWS CDK, Lambda y Amazon Aurora PostgreSQL

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6 min read
Vector Databases vs Graph Databases: Which is Best for Retrieval-Augmented Generation (RAG)?

Vector Databases vs Graph Databases: Which is Best for Retrieval-Augmented Generation (RAG)?

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4 min read
100 Days of Generative AI - Building Your First RAG Application Using Open-Source tools: Day 8

100 Days of Generative AI - Building Your First RAG Application Using Open-Source tools: Day 8

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5 min read
AI-Powered Bot using Vectorized knowledge Architecture

AI-Powered Bot using Vectorized knowledge Architecture

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4 min read
Construyendo un Motor de Búsqueda Multimodal con Amazon Titan Embeddings, Aurora Serveless PostgreSQL y LangChain

Construyendo un Motor de Búsqueda Multimodal con Amazon Titan Embeddings, Aurora Serveless PostgreSQL y LangChain

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4 min read
De Notebook a Serverless: Creando un Motor de Búsqueda Multimodal con Amazon Bedrock y PostgreSQL

De Notebook a Serverless: Creando un Motor de Búsqueda Multimodal con Amazon Bedrock y PostgreSQL

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4 min read
Deploying Serverless Embedding App with AWS CDK, Lambda and Amazon Aurora PostgreSQL

Deploying Serverless Embedding App with AWS CDK, Lambda and Amazon Aurora PostgreSQL

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6 min read
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