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Achieving provably beneficial, human-compatible AI

Practical AI

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Deep Learning Demystified

This chapter explores the complexities of deep learning within AI, emphasizing its historical context and the significance of foundational techniques. It discusses the implications of classification errors in AI, the intricacies of loss functions, and proposes a novel approach for AI to express uncertainty for improved outcomes.

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