Researchers from Anthropic managed to extract millions of interpretable features from their Claude 3 Sonnet model, making it easier to identify and understand specific behaviors and patterns within the model​. 
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Researchers from Anthropic managed to extract millions of interpretable features from their Claude 3 Sonnet model, making it easier to identify and understand specific behaviors and patterns within the model​. 
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This advance in understanding closed source AI models could make them safer by showing how specific features relate to concepts and affect the model’s behavior.
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This advance in understanding closed source AI models could make them safer by showing how specific features relate to concepts and affect the model’s behavior.
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Read the Article: 
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Read the Article: 
https://www.anthropic.com/research/mapping-mind-language-model?utm_source=substack&utm_medium=email
https://www.anthropic.com/research/mapping-mind-language-model?utm_source=substack&utm_medium=email
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Read The Paper: 
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Read The Paper: 
https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html
https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html
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Researchers from Anthropic managed to extract millions of interpretable features from their Claude 3 Sonnet model, making it easier to identify and understand specific behaviors and patterns within the model​. 

This advance in understanding closed source AI models could make them safer by showing how specific features relate to concepts and affect the model’s behavior.

Read the Article: https://www.anthropic.com/research/mapping-mind-language-model?utm_source=substack&utm_medium=email

Read The Paper: https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html
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clem RoymanLuo
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CarlAinsworth456