How AI Is Built

#1 Chang She on Multimodal AI, Storing 1 Billion Vectors, Building Data Infrastructure at LanceDB

Apr 5, 2024

Explore how LanceDB, a database for AI, revolutionizes data infrastructure with Rust, enabling multimodal AI and billion-scale vector search. Learn about its performance surpassing Parquet, embedding the internet, and optimizing data for AI engineers' ease. Dive into the future of LanceDB for AI lifecycles and surprising use cases, offering faster experimentation and model database enhancements.

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Quick takeaways

LanceDB facilitates fast experiments on terabytes of unstructured data, enhancing ML and AI success.

Transition from C++ to Rust improved productivity, tooling support, and code safety for LanceDB development.

Deep dives

Creating a Database Optimized for AI with Lance CB

Lance CB, designed as a database for AI, addresses the challenges faced by ML teams dealing with unstructured data in multimodal AI applications. The co-founders observed significant difficulties in handling various data types like images, videos, and PDFs due to a lack of optimized data infrastructure. Their background in open source development, including creating the Pandas library, fueled their passion to enhance data tools for modern AI needs, aiming to streamline workflows and enhance productivity.

Introduction

3min

Rust: A Shift in Data Libraries and AI Development

6min

Enhancing Performance and Data Modeling in Lands2B with Apache Arrow and Pedantic

8min

Exploring Multi-Modal Models and Data Management for AI Development

4min

Evolution and Future of Recommendation Systems in Production

7min

Innovative Usage of Lance in Production

7min

Imagine a world where data bottlenecks, slow data loaders, or memory issues on the VM don't hold back machine learning.

Machine learning and AI success depends on the speed you can iterate. LanceDB is here to to enable fast experiments on top of terabytes of unstructured data. It is the database for AI. Dive with us into how LanceDB was built, what went into the decision to use Rust as the main implementation language, the potential of AI on top of LanceDB, and more.

"LanceDB is the database for AI...to manage their data, to do a performant billion scale vector search."

“We're big believers in the composable data systems vision."

"You can insert data into LanceDB using Panda's data frames...to sort of really large 'embed the internet' kind of workflows."

"We wanted to create a new generation of data infrastructure that makes their [AI engineers] lives a lot easier."

"LanceDB offers up to 1,000 times faster performance than Parquet."

Chang She:

LanceDB:

Nicolay Gerold:

Chapters:

00:00 Introduction to LanceDB

02:16 Building LanceDB in Rust

12:10 Optimizing Data Infrastructure

26:20 Surprising Use Cases for LanceDB

32:01 The Future of LanceDB

LanceDB, AI, database, Rust, multimodal AI, data infrastructure, embeddings, images, performance, Parquet, machine learning, model database, function registries, agents.

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How AI Is Built

#1 Chang She on Multimodal AI, Storing 1 Billion Vectors, Building Data Infrastructure at LanceDB

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

Creating a Database Optimized for AI with Lance CB

Transition to Rust for Enhanced Efficiency in Development

Facilitating Multi-Model AI Applications with Lance DB

Remember Everything You Learn from Podcasts