859: BAML: The Programming Language for AI, with Vaibhav Gupta

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 [email protected] 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

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

• Número de episodios: 894
• Último episodio: 2025-06-03
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