You are mistaken. Ladleys papers detailing the explorative method and his figurative routines adopted by “A fast learning algorithm for deep belief nets” was the firecracker that started deep learning.
Also anyone who references wired.com should be shown the door
> anyone who references [Source] should be shown the door
Well - (exportable input) -, we are past the age of editorial boards (but for The Economist, probably) and in the age of independent journalists lending efforts inconsistently to different publishers.
Honest question, which paper is this? The 2012 one? The 2006 Hinton paper was the trigger surely - that's what I used and was filled with things that worked very quickly on GPUs.
Shouldn't this argument be easy to settle with a simple citation search?
Step 1 - Rank papers by number of citations
Step 2 - Which of the most cited papers is the earliest?
One paper will be the most cited. One paper will be the earliest.
Unless they are the same there is not _one_ answer, what you get is an efficient set (the earliest paper with at least X citations / the most cited paper as of D).
And of course there is the problem of making the list of relevant papers in the first place.
Uh not really. That would have been "A fast learning algorithm for deep belief nets" in 2006.
Also weird how this list completely ignores speech recognition. Deep learning's success in speech recognition predates AlexNet and motivated Google to create TPUs [1], and, more generally, invest in deep learning.
[1] https://www.wired.com/video/watch/the-story-behind-google-s-...