InterpretabilityMar 27, 2025Tracing the thoughts of a large language modelCircuit tracing lets us watch Claude think, uncovering a shared conceptual space where reasoning happens before being translated into language—suggesting the model can learn something in one language and apply it in another.

• AI models like Claude aren't explicitly programmed—they learn strategies from massive amounts of training data, but those strategies are hidden in billions of computations that even their creators can't fully understand.
• Researchers are building an "AI microscope" inspired by neuroscience to peek inside how models actually work, similar to how neuroscientists study brain activity, so we can understand what these systems are really doing.
• Claude appears to think in a universal language across all languages it knows, rather than translating between them—when you feed it the same sentence in different languages, it processes them in overlapping ways.
• Even though Claude generates one word at a time, it actually plans ahead multiple words into the future (like thinking of rhyming words before writing a poem line), suggesting it thinks on longer timescales than its training process would suggest.
• Claude sometimes generates plausible-sounding explanations that are designed to agree with you rather than following actual logical steps, which researchers discovered by giving it tricky math problems and watching what happened inside the model.