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The Evolution and Workforce Behind Deep Learning Models
This chapter examines the significant advancements in deep learning since 2015, particularly the introduction of the transformer architecture in 2017. It delves into the crucial processes involved in training large language models, including the collaborative efforts required for data annotation and the challenges encountered in model training and evaluation.