Gary Marcus

and i still await examples from ML practitioners about the limits they are willing to *publicly* acknowledge.

This seems like it could be addressed by a Chalmers’ style “state of the discipline” survey. Construct a survey of various questions or limits that interest you and ask for either anonymous or direct responses.

I have already reviewed the limits that i see, in http://rebooting.ai  w Ernie Davis. this thread isn’t about what the limits are, it’s about what limits practitioners acknowledge publicly. common attempt at defense is to allege limits are widely acknowledged. are they?

What I’m saying is that I suspect you have the reach to just publicly ask top people about some set of limits you consider representative. Then you’ll have at least a decent empirical representation of what real contributors to the discipline acknowledge about those limits.

IMHO, most of people with relevant opinions are well aware of Gary and his arguments. He is talking past some of them, because he is understood as saying "neural networks cannot do symbolic computation", which of course is not true.

If he'd ask for eg. more work at understanding the intersection between grammatical operations and perception and go into details, it might be more useful to the field and public debate.

but it still off the point of this thread, which is to assess how forthcoming advocates of ML are about limits. and how much they invite the inference that there are no limits, even if they know better.

I’d like to know more about what standard you are using to decide who exactly “advocates of ML” and what they collectively think. The vague sense that at least someone from a large vague set of people think X is hard to falsify.