> I feel very comfortable saying, as a mathematician, that the ability to solve grade school maths problems would not be at all a predictor of ability to solve real mathematical problems at a research level.
At some point in the past, you yourself were only capable of solving grade school maths problems.
The statement you quoted also holds for humans. Of those who can solve grade school math problems, very, very few can solve mathematical problems at a research level.
We're moving the goalposts all the time. First we had the Turing test, now AI solving math problems "isn't impressive". Any small mistake is a proof it cannot reason at all. Meanwhile 25% humans think the Sun revolves around the Earth and 50% of students get the bat and ball problem wrong.
Thank you for mentioning the "bat and ball" problem. Having neither a math nor CS background, I hadn't heard of it - and got it wrong. And reflecting on why I got it wrong I gained a little understanding of my own flawed mind. Why did I focus on a single variable and not a relationship? It set my mind wandering and was a nice morsel to digest with my breakfast. Thanks!
You missed the point. Deep learning models are in the early stages of development.
With recent advancements they can already outperform humans at many tasks that were considered to require AGI level machine intelligence just a few years ago.
At some point in the past, you yourself were only capable of solving grade school maths problems.