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#112 AVOIDING AGI APOCALYPSE - CONNOR LEAHY

Machine Learning Street Talk (MLST)

CHAPTER

Training AI: Balancing Methods and Biases

This chapter examines the complexities of training AI models, particularly the differences between black box and white box techniques. It discusses various fine-tuning methods, such as instruct fine-tuning and reinforcement learning from human feedback (RLHF), while highlighting the models' unexpected behaviors and potential biases. The conversation underscores the challenges in aligning AI outputs with human preferences and maintaining creativity without sacrificing truthfulness.

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