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Practical AI
Metrics Driven Development
Aug 29, 2024
Shahul Es, Co-founder of Ragas, discusses innovative approaches to evaluating LLM applications. He emphasizes the significance of Metrics Driven Development to systematically measure and enhance performance. The conversation contrasts assessing LLM applications with evaluating models, highlighting the need for tailored metrics and synthetic test data. Shahul shares insights on creating clear standards for better enterprise adoption, ensuring responsible and high-quality AI solutions. Tune in for an engaging deep dive into AI's evolving landscape!
42:12
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Quick takeaways
- RAGAS provides tools that automate evaluation processes for LLM applications, significantly reducing development effort and improving efficiency.
- The podcast emphasizes the importance of adopting metrics-driven development to enhance performance evaluation and decision-making in LLM applications.
Deep dives
Introduction to RAGAS
RAGAS is an open-source library designed to help developers and engineers working with LLM (Large Language Model) applications evaluate their projects more effectively. The founders, Shahul and Jiten, identified a gap in the market while experimenting with LLMs and realized that the evaluation process was often tedious and time-consuming. To address this, RAGAS provides tools and workflows that automate various evaluation techniques, significantly reducing the effort required from developers. By streamlining this process, RAGAS aims to save time and resources, allowing developers to focus more on building applications rather than getting bogged down in manual evaluations.
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Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode