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Topic: AI interpretability

AI interpretability refers to the ability to understand and explain the inner workings and decision-making processes of artificial intelligence systems, which is crucial for their safe and responsible development.

More on: AI interpretability

The podcast episodes discuss the importance of AI interpretability, often described as the ability to 'open the black box' of large language models and other complex AI systems.

Researchers are using techniques from psychology, neuroscience, and other fields to reverse-engineer these models and gain a better understanding of how they 'think' and make decisions. This knowledge is crucial for ensuring the safe and ethical development of powerful AI systems, as highlighted in the episodes.

For example, this episode features a detailed discussion on Anthropic's breakthrough research in AI interpretability, while this episode explores the psychological and neuroscientific approaches being used to crack open the 'black box' of large language models. Another episode discusses the importance of AI interpretability for effective governance and regulation of AI systems.

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