Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Inceptionism: Going Deeper into Neural Networks

googleresearch.blogspot.com

Post reply on HN
Print view View original

51–60 of 166 posts

Re: Inceptionism: Going Deeper into Neural Networks

#51

Post by waffl »

While I think this is beautiful, conceptually, I really am a bit terrified of the potential of this in reverse (the neural network for processing/understanding an image). With Google releasing their 'Photos' app, this network is about to get a direct pipeline for machine learning imagery to accelerate everything – my main fear would be the potential for this technology to be employed by weaponized drones able to scan a scene (with, eventually, incredibly high resolution cameras and microphones that far surpass human capability) and identify every single object/person in realtime (also at a rate that humans are incapable of).

Of course, there is great utility to be had as well, it just scares me to think about what could be done with this technology, in a mature form, if used for violent purposes.

Re: Inceptionism: Going Deeper into Neural Networks

#52

Post by IanCal »

Lewton wrote: post #50
IanCal wrote: post #15

The one generated after looking at completely random noise on the bottom row, second from the right: http://googleresearch.blogspot.co.uk/2015/06/inceptionism-go... Reminds me very heavily of The Starry Night https://www.google.com/culturalinstitute/asset-viewer/the-st... Lovely imagery. I never had much luck with generative networks. I did some work putting RBMs on a GPU partly because I'd seen Hinton talk showing s…

https://lh3.googleusercontent.com/4jaIlDI1xXGOhxNejib833qA5y... full resolution image

That's great, thank you.

Re: Inceptionism: Going Deeper into Neural Networks

#54

Post by plq »

teraflop wrote: post #33
raldi wrote: post #10

Earlier quoted context omitted.

Link's broken.

Fixed: https://caudallure.files.wordpress.com/2011/09/1217891347094...

OT, but this is originally a "3D" image.

It can be found in the cover art of "10000 Days", an album from American metal band Tool. The original box comes with two magnifying lenses like this:

http://s21.photobucket.com/user/Stonergrunge/media/Mis%20cos...

This (and others in the cover) look stunning through these lenses.

Re: Inceptionism: Going Deeper into Neural Networks

#55

Post by userbinator »

Animats wrote: post #44

This is fascinating. And important. We need better ways to see what neural nets are doing. At least for visual processing, we now have some. This might be usable on music. Train a net to recognize a type of music, then run it backwards to see what comes out. Run on the neural nets that do face popout (face/non face, not face recognition), some generic face should emerge. Run on nets for text recognition, letter forms…

Run on the neural nets that do face popout (face/non face, not face recognition), some generic face should emerge

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

Re: Inceptionism: Going Deeper into Neural Networks

#56

Post by mhax »

moyix wrote: post #2

This appears to be the source of the mysterious image that showed up on Reddit's /r/machinelearning the other day too: https://www.reddit.com/r/MachineLearning/comments/3a1ebc/ima...

That image was so striking and appeared to come out of nowhere. Was it some kind of marketing ploy do you think? I'm glad to have found the source anyway.

Re: Inceptionism: Going Deeper into Neural Networks

#57

Post by anigbrowl »

dnr wrote: post #41

Am I the only one who found those images somewhat disturbing? I wonder if they're triggering something similar to http://www.reddit.com/r/trypophobia

My wife found them somewhat too intense to take in rapidly. If viewing these makes you uncomfortable you should probably steer clear of psychedelic drugs, which tend to induce this sort of imagery for hours on end; as you can imagine this would be mentally tiring at the best of times.

Re: Inceptionism: Going Deeper into Neural Networks

#58

Post by svantana »

davedx wrote: post #38

Worth reading the comments too. One from Vincent Vanhoucke: "This is the most fun we've had in the office in a while. We've even made some of those 'Inceptionistic' art pieces into giant posters. Beyond the eye candy, there is actually something deeply interesting in this line of work: neural networks have a bad reputation for being strange black boxes that that are opaque to inspection. I have never understood those…

That's not really fair though, since any deterministic function can be "back-propagated" using the chain rule (or even automatic differentiation), even though it's not really necessary for simpler models such as GMM and SVM since there are much easier ways of inspecting them. Also, I don't feel single input/output pairs really describe the function itself -- knowing cos(0) = 1 doesn't reveal much about the cosine function, even though it's a local maximum. Maybe one could extend the technique to show transitions (morphing) between classes as video?

Re: Inceptionism: Going Deeper into Neural Networks

#59

Post by DanBC »

philipn wrote: post #29

The reason they look so 'fractal-like' (e.g. trippy!) is because they actually are fractals! In the same way a normal fractal is a recursive application of some drawing function, this is a recursive application of different generation or "recognition -> generation" drawing functions built on top of the CNN. So I believe that, given a random noise image, these networks don't generate the crazy trippy fractal patterns…

> The reason they look so 'fractal-like' (e.g. trippy!) is because they actually are fractals!

Do they exhibit self-similarity at different zoom levels?

Post reply on HN