The session from Srinath Godavarthi, Director, Divisional Architect at Capital One, focuses on enhancing outcomes for customers and businesses by optimizing generative AI's performance and output quality.

It highlights the importance of foundation models, their challenges, and the variability in output quality, including issues like hallucinations caused by noisy training data.

The discussion covers four main strategies for improving model performance: prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and building models from scratch.

Each method has its advantages, with prompt engineering offering quick improvements and fine-tuning providing specialized adaptations for specific tasks. Ultimately, the choice of strategy depends on the use case and the complexity involved.

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