You can't look at the coded guts of a Convolutional Neural Network and tell me which artist was used to train the AI.
Nor can you look at that code and tell me what image it will produce.
The only thing you can do is wait until the black box spits out art in a style and then guess.
FYI artistic style is not covered by copyright. Specific drawings or paintings can be covered by copyright, but not a style.
Since the Neural Network code looks nothing like art, you would have to be a drooling smooth brain to say that the art was not transformed.
As for sources: So what? When you bought that poster did you sign a contract that said you would not use it to train a NN? What law was broken? Who was harmed?
Just to be clear that I understand the point that you are making.
You are saying that transforming a series of images into a very abstract probability weighted neural network matrix that can not be read by humans is, in fact, unaltered, untransformed art?
The process:
A bunch of art ---> Unreadable probability code ---> A new image that is different from the source material
Yet there is no transformation?
Is this a correct interpretation of your argument?
Firstly, you have misread my post, which is surprising because you quoted the relevant passage in your replies.
Go back and read the post again.
My use of the word "profound" is in reference to the tools required to make the internal code of a Neural Network readable to humans.
You seem to think that there is a complete, unaltered copy of an image stored somewhere within the neural network. This just isn't true.
Information is stored inside a neural network as a matrix of weighted probabilities arranged into neurons. Each affects adjacent, connected neurons. The neural network is responding to the image on the pixel level. The response of individual neurons is one of activation intensity, and by themselves they don't do much. Together they are really good at recognizing or creating patterns.
You can't print out the code and look at the images. You can't even reconstruct the images used in training from that code, not with any tools no matter how profoundly they interpret the data. The training data set just isn't there. What you are proposing would be roughly equivalent of looking at slices of a human brain and seeing a story of the person's fifteenth birthday party. Yes, the person with that brain can write stories and accounts of their memorable party. No, you can't see the story by analysis of the brain tissue. The story isn't in the cells.
A weighted neuron probability matrix is not a copy of image, nor does it contain an image in any meaningful sense. Yes, it can produce images in a particular, specific style of art. That isn't the same thing.
Training the Neural Network doesn't even happen the way that you seem think it does. The image isn't fed into the neural network. Instead the neural network produces an image, and then that product is compared to an image from the set of training data. The training framework is playing the "Hotter / Colder" game with the neural network. FIRST the NN creates something. THEN the training framework responds. "Colder. Try again. Colder. Try again. Warmer. Try again. Hot. Getting hot!" This repeats literally thousands or millions of times in an automated process.
Your ignorance of the subject is clearly very profound, and you have devolved to arguing a semantic issue, based on you misreading my post, then declared a technical victory entirely on semantics.
The law does not support your distinction, nor does any competent analysis of Deep Learning Neural Networks.
Whoosh.
You can't look at the coded guts of a Convolutional Neural Network and tell me which artist was used to train the AI.
Nor can you look at that code and tell me what image it will produce.
The only thing you can do is wait until the black box spits out art in a style and then guess.
FYI artistic style is not covered by copyright. Specific drawings or paintings can be covered by copyright, but not a style.
Since the Neural Network code looks nothing like art, you would have to be a drooling smooth brain to say that the art was not transformed.
As for sources: So what? When you bought that poster did you sign a contract that said you would not use it to train a NN? What law was broken? Who was harmed?
You're arguing that I can't prove the exact input the AI used and that it meets the legal definition of transformation.
I'm objecting to the idea that the art is "profoundly" transformed in the artistic sense. We are not talking about the same thing.
Just to be clear that I understand the point that you are making.
You are saying that transforming a series of images into a very abstract probability weighted neural network matrix that can not be read by humans is, in fact, unaltered, untransformed art?
The process:
A bunch of art ---> Unreadable probability code ---> A new image that is different from the source material
Yet there is no transformation?
Is this a correct interpretation of your argument?
No. The art is transformed to some arbitrary degree. But profoundly transformed by most people's understanding of the word profoundly? No.
Firstly, you have misread my post, which is surprising because you quoted the relevant passage in your replies.
Go back and read the post again.
My use of the word "profound" is in reference to the tools required to make the internal code of a Neural Network readable to humans.
You seem to think that there is a complete, unaltered copy of an image stored somewhere within the neural network. This just isn't true.
Information is stored inside a neural network as a matrix of weighted probabilities arranged into neurons. Each affects adjacent, connected neurons. The neural network is responding to the image on the pixel level. The response of individual neurons is one of activation intensity, and by themselves they don't do much. Together they are really good at recognizing or creating patterns.
You can't print out the code and look at the images. You can't even reconstruct the images used in training from that code, not with any tools no matter how profoundly they interpret the data. The training data set just isn't there. What you are proposing would be roughly equivalent of looking at slices of a human brain and seeing a story of the person's fifteenth birthday party. Yes, the person with that brain can write stories and accounts of their memorable party. No, you can't see the story by analysis of the brain tissue. The story isn't in the cells.
A weighted neuron probability matrix is not a copy of image, nor does it contain an image in any meaningful sense. Yes, it can produce images in a particular, specific style of art. That isn't the same thing.
Training the Neural Network doesn't even happen the way that you seem think it does. The image isn't fed into the neural network. Instead the neural network produces an image, and then that product is compared to an image from the set of training data. The training framework is playing the "Hotter / Colder" game with the neural network. FIRST the NN creates something. THEN the training framework responds. "Colder. Try again. Colder. Try again. Warmer. Try again. Hot. Getting hot!" This repeats literally thousands or millions of times in an automated process.
Your ignorance of the subject is clearly very profound, and you have devolved to arguing a semantic issue, based on you misreading my post, then declared a technical victory entirely on semantics.
The law does not support your distinction, nor does any competent analysis of Deep Learning Neural Networks.
Have a nice day.