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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​. 
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.
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: 
Read the Article: 
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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: 
Read The Paper: 
link
https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html
https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html
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
👀
clem RoymanLuo
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CarlAinsworth456