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Practically Intelligent

E5: Reliable Software Engineering & LLMs with Adam Azzam

Sep 25, 2023
Adam Azzam, AI Product Lead at Prefect, discusses challenges of merging traditional software engineering with AI engineering. They explore marrying large language models with strongly typed semantic interfaces, suitable problems for Marvin AI, and the benefits of using LLMs in software engineering.
37:28

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Integrating LOMs with classical software engineering presents challenges due to differences in communication and options for working with LOMs are limited, which motivated the development of the open-source project Marvin.
  • Ambient AI aims to seamlessly integrate LOMs into existing software development practices, combining LOM technology with established best practices to enhance and complement existing software.

Deep dives

Working with LOMs can be challenging due to integration difficulties

The podcast episode discusses the challenges that developers face when working with LOMs (Language Output Models) in classical software. Integrating LOMs, which have a natural language interface, with structured software can be difficult due to the differences in how they communicate. The speaker highlights the limited options available for working with LOMs, such as using pre-packaged agents or hyper-specific libraries for specific tasks. However, the discussion revolves around the need to find a solution that combines the advantages of LOMs, such as their ability to understand nuanced computing tasks, with the structured and strongly typed nature of classical software. This challenge serves as the motivation behind the development of the open-source project called Marvin.

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