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Explore a 44-minute conference talk from the Data Science Festival Oktoberfest 2024 where Oren Matar delves into the challenges and solutions of extracting structured information from natural language using generative AI. Learn how transformer-based models like GPT can be optimized for information extraction tasks, with a focus on converting unstructured text into predefined formats. Discover effective best practices including Constrained Generative AI techniques for eliminating syntactic errors, and explore pre-processing, data generation, and augmentation methods that enable near-perfect accuracy in extracting temporal information. Gain practical insights into improving NLP applications through structured output generation, with content suitable for those with basic transformer architecture knowledge. The presentation, aimed at introductory level students, demonstrates how to overcome common challenges in natural language to SQL conversion and similar structured extraction tasks.
