Algorithmic Data Curation
Infinite Curiosity Pod with Prateek Joshi
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Optimizing Model Size and Data Size in Machine Learning
The chapter challenges misconceptions about the direct correlation between data size and model size in machine learning, citing the Chinchilla paper to explore the optimal trade-off between the two. It emphasizes the importance of training smaller, specialized models for efficient deployment and increased reliability, discussing the evaluation of models and data curation approaches in alignment with desired use cases.
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