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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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Debunking 6 common pgvector myths
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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
Cover image for AIM Weekly 19 August 2024

AIM Weekly 19 August 2024

5
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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

1
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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
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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
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Desplegando una Aplicación de Embeddings Serverless con AWS CDK, Lambda y Amazon Aurora PostgreSQL

5
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6 min read
Vector Databases vs Graph Databases: Which is Best for Retrieval-Augmented Generation (RAG)?
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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
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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

1
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4 min read
Construyendo un Motor de Búsqueda Multimodal con Amazon Titan Embeddings, Aurora Serveless PostgreSQL y LangChain
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Construyendo un Motor de Búsqueda Multimodal con Amazon Titan Embeddings, Aurora Serveless PostgreSQL y LangChain

2
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4 min read
De Notebook a Serverless: Creando un Motor de Búsqueda Multimodal con Amazon Bedrock y PostgreSQL
Cover image for 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

1
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4 min read
Deploying Serverless Embedding App with AWS CDK, Lambda and Amazon Aurora PostgreSQL
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Deploying Serverless Embedding App with AWS CDK, Lambda and Amazon Aurora PostgreSQL

2
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6 min read
Building a Multimodal Search Engine with Amazon Titan Embeddings, Aurora Serveless PostgreSQL and LangChain
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Building a Multimodal Search Engine with Amazon Titan Embeddings, Aurora Serveless PostgreSQL and LangChain

1
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4 min read
PGVector's Missing Features
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PGVector's Missing Features

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4 min read
Quick tip: Build Vector Embeddings for Video via Python Notebook & OpenAI CLIP
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Quick tip: Build Vector Embeddings for Video via Python Notebook & OpenAI CLIP

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7 min read
AIM Weekly 02 September 2024
Cover image for AIM Weekly 02 September 2024

AIM Weekly 02 September 2024

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2 min read
Help: creating Anthropic based OpenAI Assistants-like API

Help: creating Anthropic based OpenAI Assistants-like API

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1 min read
Vector Streaming with EmbedAnything
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Vector Streaming with EmbedAnything

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4 min read
How to choose a vector database: Pinecone, Weaviate, MongoDB Atlas, SemaDB

How to choose a vector database: Pinecone, Weaviate, MongoDB Atlas, SemaDB

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2 min read
How to build a movie recommendation app without the complexities of vector databases
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How to build a movie recommendation app without the complexities of vector databases

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7 min read
Mocking an LLM Embedder Targeting MongoDB Atlas

Mocking an LLM Embedder Targeting MongoDB Atlas

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8 min read
Retrieval Augmented Generation with Citations

Retrieval Augmented Generation with Citations

2
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5 min read
🌐 MongoDB在金融行业: 向量搜索和ACID事务 💰
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🌐 MongoDB在金融行业: 向量搜索和ACID事务 💰

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1 min read
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