"The inability of standard neural network architectures to reliably extrapolate — and reason formally — has been the central theme of my own work back to 1998 and 2001, and has been a theme in all of my challenges to deep learning, going back to 2012, and LLMs in 2019."

I think he makes a pretty lucid point that people have been questioning this for a long time, and definitely longer than 3 years. If you think there is some particular feature of LLMs that makes this a temporary hurdle, maybe you should make that point.