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#300 End to End AI Application Development with Maxime Labonne, Head of Post-training at Liquid AI & Paul-Emil Iusztin, Founder at Decoding ML

DataFramed

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Enhancing AI Responses through Feature Extraction

This chapter explores the process of extracting features from text documents to improve AI interactions, emphasizing the importance of breaking down large documents into manageable 'chunks.' It discusses techniques like supervised fine-tuning and the innovative GRPO algorithm designed to enhance preference alignment in AI models, ensuring relevant responses. Additionally, it addresses the complexities of fine-tuning large language models and the significance of data in shaping effective outputs.

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