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Sara Hooker - The Hardware Lottery, Sparsity and Fairness

Machine Learning Street Talk (MLST)

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Exploring the Historical Challenges and Diverging Approaches in Deep Learning

This chapter explores the historical barriers to deep neural networks in the 2000s, focusing on issues related to understanding and hardware limitations. It highlights the contrasting views within the machine learning community regarding the need for computational power versus the significance of interpretability and expertise in advancing AI.

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