We're essentially peeking inside a very rudimentary form of consciousness: a consciousness that is very fragile, very dependent, very underdeveloped, and full of "genetic errors". Once you have a functioning deep learning neural network, you have the assembly language of consciousness. Then you start playing with it (as this paper did), you create a hello world program, you solve the factorial function recursively, and so on. Somewhere in that universe of possible programs, is hidden a program (or a set of programs) that will be able to perform the thinking process a lot more accurately.
Inceptionism: Going Deeper into Neural Networks
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Re: Inceptionism: Going Deeper into Neural Networks
#72This 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...
I get creeps from fractals, but now my whole body is itching. Humans are weird.
Re: Inceptionism: Going Deeper into Neural Networks
#73This is one of the most astounding things I've ever seen. Some of these images look positively like art. And not just art, but good art.
Re: Inceptionism: Going Deeper into Neural Networks
#74Am 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
Re: Inceptionism: Going Deeper into Neural Networks
#75While 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…
Computers can already understand our emotions in writing, voice and from the expression on our faces, they can also estimate pose and understand your movements. They can label thousands of kinds of objects. And they're just starting.
They can also build neural nets 10x smaller by compressing a larger neural net while maintaining most of accuracy. That means once a problem such as vision or speech has been solved with a huge net, it can be transferred in a smaller, more efficient net.
Re: Inceptionism: Going Deeper into Neural Networks
#76The 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…
Re: Inceptionism: Going Deeper into Neural Networks
#77Worth 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…
Re: Inceptionism: Going Deeper into Neural Networks
#78Tweak image urls for bigger images: Ibis: http://3.bp.blogspot.com/-4Uj3hPFupok/VYIT6s_c9OI/AAAAAAAAAl... Seurat: http://4.bp.blogspot.com/-PK_bEYY91cw/VYIVBYw63uI/AAAAAAAAAl... Clouds: http://4.bp.blogspot.com/-FPDgxlc-WPU/VYIV1bK50HI/AAAAAAAAAl... Buildings: http://1.bp.blogspot.com/-XZ0i0zXOhQk/VYIXdyIL9kI/AAAAAAAAAm... I'd love to experiment with this and video. I predict a nerdy music video soon, and a pop video…
Re: Inceptionism: Going Deeper into Neural Networks
#79Re: Inceptionism: Going Deeper into Neural Networks
#80EDIT: in clarification, to pick out abstract features of an image, it must obviously be trained on many images. I'm curious about how it picked out seemingly unique characteristics of the painting, and what images it was trained on to get there.