We've already discussed this in one of the other threads, but I'll just repeat here that this isn't correct. With overwhelmingly high probability a Gaussian matrix will satisfy the restricted isometry property, which implies that appropriately L1-regularized least squares will return the exact solution.

I do wonder if it would have been better to include something along the lines of "with probability 1" to the claim that non-Bayesian methods can solve it easily. Compressed sensing isn't magic, even though it's very close.

any agent that is intelligent enough to behave at all functionally close to the level of a human would be robust to context changes.

Humans get tripped up by context changes very frequently. It's not obvious to me where you think this robustness would come from.