Anthropic's Disproof of the ETH

Anthropic researchers have published a study questioning the existence of the Superposition Hypothesis in large language models. The team found that increasing the number of features within a network does not necessarily lead to the expected interference patterns previously theorized as evidence of superposition. This work suggests that current models may rely on different mechanisms for information storage than previously assumed. If validated, these findings could shift how developers approach model interpretability and the underlying architecture of neural networks.