[ghostcluster]

If you want to rise to an 'empereor has no clothes' caliber piece, it would help to demonstrate a comprehensive understanding of the fields you're criticizing, and not arrogantly cite bad science essays, and not ignore the actual state of the art techniques in that domain.

You need to present the best arguments from the side you want to critique and then prssent a case why you think they are wrong. Calling people names and avoiding difficult challenges to your thesis is not the way to do it.

[sgt101]

Well - I'm not so sure, you're setting a very high bar which makes it difficult for people with a different background to make points (badly in your view, but pretty well in mine) which the community needs to hear.

This isn't a Ph.D. exam, this isn't a thesis - it's an outsider calling BS. I'm not impressed by the counter arguments advanced so far. Let's be honest, Alpha Go and Alpha Go Zero are surprises in that they have shown that Go isn't as astonishingly difficult for approximate search - which everyone thought it was - but until we see the real world applications it's all of intellectual interest.. which is the point of the article.

There are a lot of folks who I respect making claims similar to the company that is featured in the piece, I'm really disappointed by that because everthing that we know about learnability is ignored with the cry "we've got deep networks now". We've don't know why dnn's generalise as well as they do but shouldn't, but it's no excuse to just abandon our sanity and go out and bet large amounts of other people's money on them doing things that they can't.

This money, btw, should be spent on hospitals and roads, not on providing near 7 figures for these people.

[ghostcluster]

If you don't even understand the basics of what's possible in a field and what's not, you can't make a convincing refutation of that field by just calling certain people names and citing bad science essays that you also don't understand.