What are the limits of deep learning?

Re:What are the limits of deep learning? by cr0sh on Wednesday January 23, 2019 @02:57PM (#18982104)

> It's roughly comparable to spending all R&D perfecting vacuum tubes in the 1940's

Vacuum tubes continued to be improved all the way up into the early 1960s, long after transistors had taken hold:

https://en.wikipedia.org/wiki/Compactron

One in particular was used mainly in television sets, all the way up into the early 1970s:

https://en.wikipedia.org/wiki/Nuvistor

...it competed with transistors, and was almost as small as some of its contemporary transistor cousins.

Even today, you can't rule out the vacuum tube - for some things, there isn't any substitutes:

http://www.nutsvolts.com/magazine/article/vacuum-tubes-for-t...

...and new ideas for the old technology are being investigated:

http://www.sciencemag.org/news/2012/05/return-vacuum-tube

[ Parent | on HN ]

Re:What are the limits of deep learning? by tabtab on Wednesday January 23, 2019 @06:15PM (#18984214)

I didn't mean to imply that vacuum tubes stopped having uses or stopped improving. My main point is that they stopped being the primary source of electronics and digital processing innovation and progress.

Even if by chance neural/deep-nets stop being the primary source of AI innovation, I'm sure people will find and make improvements in them regardless.

[ Parent | on HN ]