Peek inside an AI’s ‘brain.’ Anthropic’s “circuit tracing” maps how language models think, step by step, from poetry planning to medical reasoning and saying no to harmful requests. We translate the science into plain English, spotlight wins, admit limits, and explore why this transparency matters for safer AI for everyone.
This episode is a guided tour of how researchers are opening the black box of AI. Anthropic’s “circuit tracing” is like drawing a wiring diagram for a language model: it shows which parts light up, how information travels, and why the model lands on a particular answer—or refuses a harmful request.
We keep it human-friendly. Instead of math, you’ll hear clear analogies: special “translators” that help one layer of the model talk to another, and map-like graphs that trace the flow of ideas. Then we visit real case studies on Claude 3.5 Haiku—multi-step reasoning, planning in poetry, multilingual patterns, even medical problem solving and built-in safety behaviors.
No hype without honesty: the method still struggles with attention circuits, sometimes rebuilds signals imperfectly, and the maps can get complex fast. But understanding these inner circuits is a leap toward AI you can audit, improve, and trust. If you’re curious about how we make powerful models safer and more accountable, this is your on-ramp.
Rabbit Hole 
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