[brucephillips]

https://m.cacm.acm.org/magazines/2017/6/217734-deep-learning...

[comstock]

Looks like great incremental progess. Have you seen the state of Japanese<->English translation? It’s almost completely useless.

I really don’t see this as a huge win for deep learning, anything else?

[brucephillips]

Whether progress is incremental is an ill defined question. I don't consider "super human translation" to be incremental. The key point here is that deep learning has produced significant results. I'm not sure why you care to argue semantics.

[comstock]

Well, I’m interested in understanding how valuable deep learning is and if lives up to the hype.

Better translation of European languages (which wasn’t a totally unsolved problem anyway) doesn’t seem to be something that really lives up to the hype.

Particularly as the article cited doesn’t seem to back up its statements very well.

So... anything else?

[brucephillips]

If super human translation doesn't impress you, what will?

[comstock]

The article doesn’t make that statement. The article doesn’t provide data to support any statements (it’s a pop science piece).

The original blog:

https://research.googleblog.com/2016/09/a-neural-network-for...

Is better suggests deep learning resulted in maybe 10% improvement. Isn’t as good as human in all cases.

[brucephillips]

Ah I misread "as good" as "better". It's still an epsilon difference, though. And the article lists other applications that have had "step wise" improvements, which is the opposite of incremental of course.

Also, you didn't answer the question.