Declarative Machine Learning in Databases and Recommendation Systems

If you've ever wanted a simpler way to integrate AI directly into your database, SuperDuperDB might be the answer. SuperDuperDB lets you easily apply AI processes to your data while keeping everything up-to-date with real-time calculations. It works with various databases and aims to make AI development less of a headache.

In this podcast, we explore:

• How SuperDuperDB bridges the gap between AI and databases.
• The benefits of real-time AI processes within your data deployment.
• SuperDuperDB's framework for configuring AI workflows.
• The future of AI-powered databases.

Takeaways

• SuperDuperDB enables developers to apply AI processes directly to their data stores
• The platform supports real-time computation of embeddings or classifications, keeping the data deployment up to date
• SuperDuperDB provides a framework for configuring AI processes that work in close combination with the data deployment
• The platform supports a variety of databases, including operational and analytical databases
• SuperDuperDB aims to simplify AI development by abstracting the data layer and infrastructure

Duncan Blythe:

• LinkedIn

SuperDuperDB:

• Docs
• Website
• LinkedIn

Nicolay Gerold:

• LinkedIn
• X (Twitter)

Chapters

00:00 Introduction to SuperDuperDB

04:19 Real-time Computation and Data Deployment

13:46 Bringing Compute and Database Closer Together

29:30 Declarative Machine Learning with SuperDuperDB

35:09 Future Plans for SuperDuperDB

SuperDuperDB, AI, databases, embeddings, classifications, data deployment, operational databases, analytical databases, AI development, data science