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Inceptionism: Going Deeper into Neural Networks

googleresearch.blogspot.com

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Re: Inceptionism: Going Deeper into Neural Networks

#151

Post by nitrogen »

tzs wrote: post #147

Understanding what is going on in a neural network (or any other kind of machine learning mechanism) when it makes a decision can be important in real world applications. For example, suppose you are a bank and you have used built a neural network to decide if credit applications should be approved. The lending laws in the US require that if you reject someone you tell them why. Your neural network just gives a yes/n…

I have an idea for a company related to this concept, but for hiring and job training.

Re: Inceptionism: Going Deeper into Neural Networks

#152

Post by bearzoo »

They are doing nothing but starting with random noise, and then learning a representation of an image that will maximize the probability in the output layer (by suggesting to the network that this noise should have actually been recognized as a banana or what have you) and back propagating changes into the input layer. Essentially, this has been happening since 2003 in the natural language processing world where we learn 'distributed representations' of words by starting with random representations of words, and learning them by context by back propagating changes into the input layer. Very cool though.

Re: Inceptionism: Going Deeper into Neural Networks

#153

Post by nitrogen »

plq wrote: post #54
teraflop wrote: post #33

Earlier quoted context omitted.

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.

You can see the 3D effect of this subset of the image here: https://imgur.com/04yBHN4

Re: Inceptionism: Going Deeper into Neural Networks

#155

Post by Houshalter »

svantana wrote: post #58
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 fun…

Here's it applied to each frame of a video https://plus.google.com/photos/+MikeJurney/albums/6161722239...

Re: Inceptionism: Going Deeper into Neural Networks

#156

Post by Houshalter »

pjonesdotca wrote: post #123
rndn wrote: post #77

Earlier quoted context omitted.

Perhaps the argument should be steelmanned in that we should generally avoid using algorithms which are so complex that they aren't glass boxes. I doubt the idea to "simply follow gradients" can prove neural networks to be glass boxes because the output of that is still too complex. And we are clearly onto something here. If we can generate artificially hallucinated pictures today, it is not unreasonable to assume th…

Great more "ZOMG I'm skirred of AI" FUD. Stop being so afraid of the future.

There are plenty of reasons to be concerned about AI. Stop dismissing arguments because you don't like their conclusions. There is no law of the universe that the future can't suck.

Re: Inceptionism: Going Deeper into Neural Networks

#157

Post by Houshalter »

fr0styMatt2 wrote: post #149
userbinator wrote: post #74

Earlier quoted context omitted.

I'm only mildly trypophobic but those images did have a minor effect - and I have a possible hypothesis for why it happens: what these images and trypophobia-triggering ones all have in common is a huge number of edges of various shapes and sizes, and it's this "edge overload" stimulating many more neurons than usual that's causing the disturbance. I find that the repetitive, but not-quite-the-same patterns like (org…

I've always wondered about this! Back when I was a teenager I remember playing around with one of the Kai's Power Tools to generate fractal-like images (I forget exactly which one it was, but it had a bunch of presets that would generate cell-like textures). Thing was, I found them MASSIVELY anxiety-provoking and have never been able to figure out why. They'd literally make me panicky. These images are doing the same…

I found an image which stimulates the edge detectors in people's brains, far more than a natural image. It tends to cause people to feel weird and not want to look at it, in a way they can't quite describe. And making the image flash and rotate rapidly made it far worse.

The image: https://i.imgur.com/Zihujue.gif

And it flashing: http://makeagif.com/i/hHzAiq

Re: Inceptionism: Going Deeper into Neural Networks

#158

Post by [deleted] »

fizixer wrote: post #112
romaniv wrote: post #98

Earlier quoted context omitted.

We're essentially peeking inside a very rudimentary form of consciousness Blatant sensationalism. There is absolutely nothing here that would suggest consciousness. If you have a mask for matching images, you can reverse that mask and imprint it as an image. What we're seeing here is a more complicated version of the same process. Heck, look more closely. Some of those "building" images have obvious chunks of pedestr…

> Blatant sensationalism. There is absolutely nothing here that would suggest consciousness. Putting biological consciousness on a pedestal might be blatant sensationalism itself. By consciousness, I specifically mean the behavioral capacity of general intelligence, nothing more. If by consciousness you mean subjective character of experience then yes, there are serious issues with resolving the mind-body problem. Bu…

[deleted]

Re: Inceptionism: Going Deeper into Neural Networks

#159

Post by tdaltonc »

drcode wrote: post #116
mhax wrote: post #56

Earlier quoted context omitted.

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.

If I was part of the Google marketing machine and a developer wanted to make that nightmare image public, I'd veto them in a Mountain View minute.

Ya the PR team would have probably gone with this one:

https://photos.google.com/share/AF1QipPX0SCl7OzWilt9LnuQliat...

Re: Inceptionism: Going Deeper into Neural Networks

#160

Post by romaniv »

fizixer wrote: post #112
romaniv wrote: post #98

Earlier quoted context omitted.

We're essentially peeking inside a very rudimentary form of consciousness Blatant sensationalism. There is absolutely nothing here that would suggest consciousness. If you have a mask for matching images, you can reverse that mask and imprint it as an image. What we're seeing here is a more complicated version of the same process. Heck, look more closely. Some of those "building" images have obvious chunks of pedestr…

> Blatant sensationalism. There is absolutely nothing here that would suggest consciousness. Putting biological consciousness on a pedestal might be blatant sensationalism itself. By consciousness, I specifically mean the behavioral capacity of general intelligence, nothing more. If by consciousness you mean subjective character of experience then yes, there are serious issues with resolving the mind-body problem. Bu…

You did not address a single specific points I made.

I specifically mean the behavioral capacity of general intelligence

Any image-matching algorithm can be used to generate images. A simple color-matcher can be used to create very impressive things if plugged into a genetic algorithm, but no one claims it's conscious or intelligent. None of what you wrote here points out some fundamental differences between this and other image-generating techniques used before. You're simply trivializing what it means to be conscious or intelligent to the point that word is no longer useful.

I will consider an AI to be "generic" when it is able to apply training from one domain to an entirely different domain without any manual "mapping" from humans. For example, being able to decently play checkers after learning chess and being given a description of checker's rules. Applying training in image domain to image domain with tons of manual tweaking might be interesting and useful, but it's hardly qualifies as "mind-blowing".

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