[sdenton4]

"It's impressive what large statistical models can do but they still can not solve sudoku so something is clearly missing here because neural networks do not have feedback loops and backtracking."

Again, the things you ask for exist. Recurrent networks and reinforcement learning both have feedback loops. (And there's a reasonable argument that residual networks can be interpreted as 'unrolled' recurrent networks.)

Here's a completely random paper on reinforcement learning for Sudoku with non-zero win rates (and a few other games): https://arxiv.org/abs/2102.06019

I'm not sure anyone's bothered to take a real crack at Sudoku specifically. It's another example of a weak indicator, though: someone will happily solve it if you're willing to call it the bar for intelligence. Given where we're at on game-playing generally, it seems very doable with current technology.

"at what point do you suppose there will be statistical models with symbolic understanding?"

Understanding again has no real definition, so this is open to endless argument. I think it's fair to say that DALL-E understands what an astronaut looks like, though.

[goodtraveler]

Ok, thanks for the references.