Earlier quoted context omitted.
Ok, I'll bite. Let's assume a modern cutting edge model but even with fairly standard GQA attention, and something obviously bigger than just monosemantic features per neuron. Based on any reasonable mechanistic interpretability understanding of this model, what's preventing a circuit/feature with polysemanticity from representing a specific error in your code? --- Do you actually understand ML? Or are you just parro…
Ok, let's chew on that. "reasonable mechanistic interpretability understanding" and "semantic" are carrying a lot of weight. I think nobody understands what's happening in these models -irrespective of narrative building from the pieces. On the macro level, everyone can see simple logical flaws.
Quick question, do you know what "Mechanistic Interpretability Researcher" means? Because that would be a fairly bold statement if you were aware of that. Try skimming through this first: https://www.alignmentforum.org/posts/NfFST5Mio7BCAQHPA/an-ex...
> On the macro level, everyone can see simple logical flaws.
Your argument applies to humans as well. Or are you saying humans can't possibly understand bugs in code because they make simple logical flaws as well? Does that mean the existence of the Monty Hall Problem shows that humans cannot actually do math or logical reasoning?