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The Data Dilemma in Deep Learning
This chapter explores the critical role of data in enhancing deep learning performance while addressing the trade-offs between data scaling and generalization. It emphasizes the need for improved methodologies in large-scale data annotation and the implications of AI technologies on personal autonomy. Additionally, it highlights the importance of shifting focus from computational advancements to data quality and efficiency in advancing AI systems.