You have stated that AI will improve. Improvement implies being able to classify something as better than something else. You have then stated that art is subjective and therefore a given piece cannot be classified as better than another. This is a logical contradiction.
I then questioned your standards for “good”. By what criteria are you measuring the pieces in order to determine which one is “better” and thus be able to determine if the AI’s input is improving or not? I then tried to, as simply and as timely as I could, give a basic explanation of how the Learning process actually works. Admittedly I did not do a good job. Explanations of this could take up to two or three hours, depending on how much you already know.
Then comes some philosophizing about what makes a piece “good”. First, questioning your focus on the pieces of output being good. Then, inquiring what is the harm of a “bad” image? In the context of “Why not draw yourself? Too afraid of making something that is not «perfect»”? Then I asked why is it that you refuse, on your analisys of the “goodness” of an image, to go beyond “I like it.”/“I do not like it.”, “It looks professional”/“It looks amateurish”. Such statements are not meaningful critiques of a piece, they are reports of the feelings of the observer. The subjectivity of art we all speak of. However, it is indeed possible to create a more objective critique of a piece which goes beyond our tastes. To critique a piece, one must try to look at what one believes the piece is trying to accomplish, then evaluate whether or not the piece is succeeding at it. If it is, why? If it isn’t, why not?
Then, as an addendum, I stated that these functions we call AI have diminishing returns. This is a consequence of the whole loss function thing which is at the heart of the Machine Learning process.
The some deceitful definitions. The words “Neuron” and “Learning” under the context of Machine Learning do not have the same meaning as they do colloquially. This is something which causes many to be fooled and marketing agencies abuse to market “AI”. Neuron does not mean “simulation of biological neuron”, it means “Number from 0 to 1”. That means that a Neural Network is actually just a network of numbers between 0 and 1, like 0.2031. Likewise, learning in Machine Learning is not the same has biological learning. Learning here is just a short hand for Minimizing the value of the Loss Function”.
I could add that even the name AI is deceitful, has it has been used as a marketing buss word since it’s creation. Arguably, one could say it was created to be one. It causes people to judge the Function, not for what it is, as any reasonable actor would, but for what it isn’t. Instead judged by what, maybe, it might become, if only we [AI companies] get more funding. This is nothing new. The same thing happened in the first AI craze in the 19’s. Eventually people realized the promised improvements were not coming and the hype and funding subsided. Now the cycle repeats: They found something which can superficially be considered “intelligent” and are now doing it again.
You have stated that AI will improve. Improvement implies being able to classify something as better than something else. You have then stated that art is subjective and therefore a given piece cannot be classified as better than another. This is a logical contradiction.
I then questioned your standards for “good”. By what criteria are you measuring the pieces in order to determine which one is “better” and thus be able to determine if the AI’s input is improving or not? I then tried to, as simply and as timely as I could, give a basic explanation of how the Learning process actually works. Admittedly I did not do a good job. Explanations of this could take up to two or three hours, depending on how much you already know.
Then comes some philosophizing about what makes a piece “good”. First, questioning your focus on the pieces of output being good. Then, inquiring what is the harm of a “bad” image? In the context of “Why not draw yourself? Too afraid of making something that is not «perfect»”? Then I asked why is it that you refuse, on your analisys of the “goodness” of an image, to go beyond “I like it.”/“I do not like it.”, “It looks professional”/“It looks amateurish”. Such statements are not meaningful critiques of a piece, they are reports of the feelings of the observer. The subjectivity of art we all speak of. However, it is indeed possible to create a more objective critique of a piece which goes beyond our tastes. To critique a piece, one must try to look at what one believes the piece is trying to accomplish, then evaluate whether or not the piece is succeeding at it. If it is, why? If it isn’t, why not?
Then, as an addendum, I stated that these functions we call AI have diminishing returns. This is a consequence of the whole loss function thing which is at the heart of the Machine Learning process.
The some deceitful definitions. The words “Neuron” and “Learning” under the context of Machine Learning do not have the same meaning as they do colloquially. This is something which causes many to be fooled and marketing agencies abuse to market “AI”. Neuron does not mean “simulation of biological neuron”, it means “Number from 0 to 1”. That means that a Neural Network is actually just a network of numbers between 0 and 1, like 0.2031. Likewise, learning in Machine Learning is not the same has biological learning. Learning here is just a short hand for Minimizing the value of the Loss Function”.
I could add that even the name AI is deceitful, has it has been used as a marketing buss word since it’s creation. Arguably, one could say it was created to be one. It causes people to judge the Function, not for what it is, as any reasonable actor would, but for what it isn’t. Instead judged by what, maybe, it might become, if only we [AI companies] get more funding. This is nothing new. The same thing happened in the first AI craze in the 19’s. Eventually people realized the promised improvements were not coming and the hype and funding subsided. Now the cycle repeats: They found something which can superficially be considered “intelligent” and are now doing it again.