My take on this is I’d be interested to see how the research goes, and there may be value in doing this approach, and I think that this may be a useful way to get a quantitative estimate/bound in the future, because it relaxes it’s goals.
I’d like to see what eventually happens for this research direction:
Could we reliably give heuristic arguments for neural networks when proofs failed, or is it too hard to provide relevant arguments?
I do want to say that on formal verification/proof itself, I think the most useful application is not proving non-trivial things, but rather to keep ourselves honest about the assumptions we are using.
My take on this is I’d be interested to see how the research goes, and there may be value in doing this approach, and I think that this may be a useful way to get a quantitative estimate/bound in the future, because it relaxes it’s goals.
I’d like to see what eventually happens for this research direction:
Could we reliably give heuristic arguments for neural networks when proofs failed, or is it too hard to provide relevant arguments?
I do want to say that on formal verification/proof itself, I think the most useful application is not proving non-trivial things, but rather to keep ourselves honest about the assumptions we are using.