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Practical AI

Collaboration & evaluation for LLM apps

Jan 23, 2024
Raza Habib, CEO and co-founder of Humanloop, discusses the complexities of prompt engineering in AI development. He emphasizes how even small changes in prompts can drastically alter outputs. Raza highlights the importance of collaboration between technical and non-technical team members for optimizing AI applications. He explores the role of platforms like Humanloop in enhancing these collaborations and the significance of user feedback for refining performance. The conversation also touches on evolving workflows and data privacy in the context of model hosting.
46:14

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Collaboration between non-technical prompt engineers and technical software engineers is crucial for building effective AI-driven apps.
  • Measuring performance in generative AI models is subjective, making evaluation and assessment challenging.

Deep dives

Overview of Human Loop and its Purpose

Human Loop is a platform that helps companies with prompt iteration, versioning, and management, as well as evaluation and monitoring of AI models. It provides a web app with an interactive playground-like environment where domain experts and engineers can collaborate. Domain experts can try different prompts, compare models, and save versions that they find effective. Engineers handle code orchestration, model calls, and setting up evaluation. The platform allows for different forms of evaluation, including unit tests, integration tests, and human evaluation. It also enables monitoring for performance and potential regressions.

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