Progress and Challenges
Sebastian discusses the progress made in natural language understanding, with models achieving better performance on question answering tasks. However, he highlights the need for deeper understanding and more challenging data sets to approach human-level performance. The use of models in generating data sets is seen as a promising trend in improving both models and data sets in a cyclical loop. Kyle brings up the example of the perihelion of Mercury to emphasize the importance of continuous exploration and advancement in scientific understanding.In this clip
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