As LeCun always says: The term "AGI" is a bit ill-formed. What does "general" really mean? Human intelligence is not really general. It's actually very very specialized towards the world we live in. So he prefers the term "human-level intelligence", or maybe super-human-level at some point.
Another implication: It's not really a yes/no property, whether you have AGI or not. It's a level of intelligence. And this level is continuous. And it's also not really one-dimensional.
What does human-level intelligence mean? It's still not very well-defined. You would need to define a number of tests, which measure the performance, and the model need to perform at least as good as a human on average.
So, I assume this is what the author means by "AGI-hard": A problem which requires some model to be at least as good as a human in a wide number of tests.
But I don't think this is necessary for driving. You want it actually to be much better in some tests (computer vision, reaction time, etc) and many other tests don't really matter (eg. logical reasoning, speech recognition, or so). So the autonomous driving problem is not AGI-hard.
Another implication: It's not really a yes/no property, whether you have AGI or not. It's a level of intelligence. And this level is continuous. And it's also not really one-dimensional.
What does human-level intelligence mean? It's still not very well-defined. You would need to define a number of tests, which measure the performance, and the model need to perform at least as good as a human on average.
So, I assume this is what the author means by "AGI-hard": A problem which requires some model to be at least as good as a human in a wide number of tests.
But I don't think this is necessary for driving. You want it actually to be much better in some tests (computer vision, reaction time, etc) and many other tests don't really matter (eg. logical reasoning, speech recognition, or so). So the autonomous driving problem is not AGI-hard.