Neural Networks - Emulating Human Creativity
Upon finding the article Algorithmic Composition and Reductionist Analysis: Can a Machine Compose? I immediately got excited. The author gives a great overview of algorithmic composition and details his own endeavors into the field.
In particular, the author touches on the concept of heuristic algorithms - including both genetic algorithms and neural networks - that slowly approach a desired solution by having a human evaluator determine the fitness of the system. I found the following quote astounding:
"A researcher trained a neural network to recognize makes of car from a photograph, and he decided to look inside the network at the individual neurons, rather than regarding it as a "black box" that somehow worked for some incomprehensible reason. He found that certain areas of the network were specializing into recognizing certain features of the car, and, by introducing a level of random "noise" into the network, got the network to design its own cars."
And finally, the author's take on algorithmic composition and creativity:
"I have always felt very uneasy about throwing any musical ideas away, as it would amount to destroying something that I think is unique. But, if computer composition took over to a degree, would the 'preservation people' be content with the idea that the music exists, somewhere, within the set of possibilities? May I delete Clara Empricost's symphony with impunity, once it has generated it? Should I preserve the algorithm and the random number seeds somewhere? An interesting set of problems."