Exploring BAML: Enhancements in Token Efficiency and Performance Optimization

In this week’s guest interview, Vaibhav Gupta talks to Jon Krohn about creating a programming language, BAML, that helps companies save up to 30% on their AI costs. He explains how he started tailoring BAML to facilitate natural language generation interactions with AI models, how BAML helps companies optimize their outputs, and he also lets listeners into Boundary’s hiring process.

This episode is brought to you by ODSC, the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn:

• (04:53) What BAML stands for
• (14:33) Making a prompt engineering a serious practice
• (18:00) How BAML helps companies
• (23:30) Using retrieval-augmented generation (RAG)
• (43:09) How to get a job at Boundary

Additional materials: www.superdatascience.com/859