I love this post for two reasons. First, it's a great reminder to question assumptions about high abstraction mathematical models that tries to say something about reality. And to not take what a community of even scientists say as stable truth. Ask a room full of signal processing engineers if it's possible to do better than the sampling theorem, and they'll confidently – with bravado – tell you that such an idea is ridiculous. Second, the end is a great example of a "proof by incentive" argument, which is one of my favourite ways to produce trust in a theorem.
Proof by incentive is a terrible argument. There are a ton of cranks out there offering money for proof that the Earth is round or whatever, and holding up the lack of takers as proof that whatever nonsense they espouse is correct. All it proves I’m these cases is that either nobody cares about them, or their standards of proof are crazy.
I think the author here is clearly correct, I just don’t think their $1,000 offer does anything to demonstrate it.
I read this comment before reading the article and got excited to read an article showing how the "establishment" was wrong. Much to my surprise, the article was saying the exact opposite! I'm still not really sure how to read this comment in a way that makes sense.
The comment is digitized brain noise in ASCII form. It just shows that if there's too much unfiltered noise before keyboard sampling, the signal can't be reconstructed.
