Practical AI

Vector databases for machine learning

Jun 22, 2021

Edo Liberty, Founder and CEO of Pinecone, shares insights on vector databases and their revolutionary impact on machine learning. He explains how vector similarity search outperforms traditional databases, allowing rapid searches through billions of embeddings. The conversation navigates the evolution of big data, the development of memory capabilities, and the unique challenges of high-dimensional data. Liberty also sheds light on Pinecone's dual role as a vector database and search engine, emphasizing its ease of integration into machine learning workflows.

42:37

Creator website

Episode guests

Edo Liberty

Highlights

AI Chapters

Episode notes

Vectors unify all kinds of data

02:36

Like a monkey climbing a tree to get to the moon

01:22

Intro

3min

Navigating the Big Data Landscape

12min

Navigating the New Memory Paradigm

4min

Understanding Facial Recognition through Vector Representations

3min

Navigating the Complexity of Vector Database Architecture

2min

Understanding Pinecone: Beyond Database and Search Engine

12min

Integrating Pinecone into ML Workflows

7min

Pinecone is the first vector database for machine learning. Edo Liberty explains to Chris how vector similarity search works, and its advantages over traditional database approaches for machine learning. It enables one to search through billions of vector embeddings for similar matches, in milliseconds, and Pinecone is a managed service that puts this capability at the fingertips of machine learning practitioners.

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Featuring:

Edo Liberty – Website, GitHub, LinkedIn, X
Chris Benson – Website, GitHub, LinkedIn, X

Show Notes:

Something missing or broken? PRs welcome!

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