Building high-level features using large scale unsupervised learning

Re:Building high-level features using large scale unsupervis... by marshallp on Friday June 22, 2012 @02:31AM (#4145726)

I put the singularity bit in to make it relevant for those who are non-technical. This experiment is significant because it shows that large artificial neural networks can be made to work. People have tried and failed at this for decades.

This technigue was "discovered" by geoff hinton at the university of toronto in 2005. However, nobody at tried (or maybe got enough funds) to try it this scale.

If this continues to work at larger and larger scale, this would be a machine learning technique that can work accurately on tasks that are hugely important to society

- accurate speech recognition - human level compuer vision (make human manual labor redundant)

[ Parent | on HN ]

Re:Building high-level features using large scale unsupervis... by _b8r0 on Friday June 22, 2012 @03:50AM (#4145873)

Even so, the singularity bit is editorializing a link to a white paper on an equally significant scale. Nowhere in the link is the singularity referenced.

As for the point about it being for non-technical people, I don't understand where you're coming from. This is hacker news. If people don't understand it and don't upvote it, then that's their problem, not yours.

[ Parent | on HN ]

Re:Building high-level features using large scale unsupervis... by Chlorus on Friday June 22, 2012 @03:37AM (#4145848)

"I put the singularity bit in to make it relevant for those who are non-technical." Yeah, I'm sure there's a lot of those on HN...I'd expect this kind of crap in something like Wired, but not here.

[ Parent | on HN ]