Data retrieval and embeddings enhancements from MongoDB set the stage for a year of specialized AI

Data retrieval and embeddings enhancements from MongoDB set the stage for a year of specialized AI - SiliconANGLE ...
InfoQ

Enhancing AI Capabilities: Google Cloud Integrates Vector Search in Managed Databases

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
InfoQ

Amazon Aurora PostgreSQL Adds pgvector to Support Embeddings from Generative AI

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
VentureBeat

New DeepMind study reveals a hidden bottleneck in vector search that breaks advanced RAG systems

Vector embeddings are the backbone of modern enterprise AI, powering everything from retrieval-augmented generation (RAG) to semantic search. But a new study from Google DeepMind reveals a fundamental ...
Searchenginejournal.com

Introduction To Vector Databases And How To Use AI For SEO

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...
VentureBeat

The vector database is a new kind of database for the AI era

Companies across every industry increasingly understand that making data-driven decisions is a necessity to compete now, in the next five years, in the next 20 and beyond. Data growth — unstructured ...
InfoWorld

What is vector search? Better search through AI

Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable. Suppose you wanted to ...