It's easy for humans once they're taught what variables mean and after 10 or so years of exposure to a real world multimodal training set that's orders of magnitude more data than GPT has seen. Also, algebra is not so easy for people with IQs lower than 90, so not exactly all humans right? What exactly am I supposed infer about how GPT or other AIs and human brains operate from this apples to cars comparison?
You don't have to point out failure modes of GPT, I know what they are. The question we're discussing here is what this indicates, if anything, about how these systems operate as compared to human brains, and whether the differences come down to training data or the fundamental architecture.
