In episode 119 of the Acceleration Economy Minute, I share an update on Databricks and a new toolkit for driving large language model (LLM) apps.
This episode is sponsored by Acceleration Economy’s AI Ecosystem Course, available on demand. Discover how AI has created a new ecosystem of partnerships with a fresh spirit of customer-centric cocreation and renewed focus on reimagining what is possible.
Highlights
00:18 — Databricks has announced a new Retrieval Augmented Generation (RAG) toolkit
for its data intelligence platform that will help customers build, launch, and run large language model (LLM) driven apps for diverse use cases.
Which companies are the most important vendors in data? Check out the Acceleration Economy Data Modernization Top 10 Shortlist.
01:01 — The new Databricks tools make it easier for companies to create RAG apps which are notoriously difficult to develop because they require collecting data — structured or unstructured — from multiple sources. The data then needs to go through a preparation process to make it actionable. The tools currently in public preview include:
- A vector search service for semantic search on existing tables
- Fully managed foundation models providing paper token-based LLMs
- A quality monitoring interface for users to oversee production performance
- Development tools to compare and evaluate various LLMs
