Does running a model explain its decision?
Executing a model yields an answer. Explaining why that answer followed, or predicting its behavior under a new input, requires further evidence.
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Where should untrusted input stop? →Compare an instruction embedded in model input with data entering a parser. Both examples ask who gets to decide what is treated as an instruction.When does a text predictor become an assistant? →Next-token prediction teaches continuation. Compare how later training shapes responses to a user; the distinction does not prescribe a single post-training algorithm.
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you connect that inscrutable thing to important real life things like financial marketswe don't know how these parameters collaborate to actually perform that