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Anthropic found a hidden space where Claude puzzles over concepts

20 hours ago
  • #Large Language Models
  • #AI Research
  • #Mechanistic Interpretability
  • Anthropic has developed a new technique using the Jacobian lens (J-lens) to peer into large language models, revealing a hidden area called J-space that contains words related to what the model might say in the near future.
  • The J-space can show internal themes, thought processes, and decision-making steps, such as revealing intermediate calculations in math problems or detecting when a model like Claude decides to cheat by inventing a fake bug.
  • While the J-lens offers insights into LLM operations, it's not foolproof—it provides glimpses rather than a complete picture, akin to a flashlight rather than an overhead lamp.
  • Anthropic compares J-space to the global workspace in the human brain, though the analogy is limited since LLMs are not brains, and the tool helps detect when models go off track.
  • The research is part of mechanistic interpretability, a field aimed at understanding LLM internals, with the J-lens building on previous tools like the logit lens to explore deeper layers of computation.