This example and others like it really reinforce for me the idea that LLMs fundamentally don't "understand" things the same way humans do and it's not a problem that's going to be fixed by more training or more GPUs. Generative AI is cool and can do impressive stuff, but despite being many generations into the models now with ever improved capabilities, we're constantly given little reminders like this that they're not actually intelligent. And in my opinion, they're unlikely to ever get there absent some fundamentally disruptive change in how they work rather than just iteratively better models.

This is probably OK...LLMs don't have to be AGI to be useful. But it is worthwhile being realistic about their limitations because it's often easy to forget without seeing examples like this. And as you point out, the impact of those limitations is often not as obvious.