Exploring the bounds of computational creativity from "summary" of The Creativity Code by Marcus Du Sautoy
The boundaries of computational creativity are constantly being pushed and tested by researchers and programmers in the field of artificial intelligence. This involves developing algorithms and systems that can generate creative outputs such as music, art, or literature. These systems are designed to mimic human creativity by using machine learning and deep learning techniques to produce original and innovative work. By exploring the limits of what machines are capable of creating, we gain a deeper understanding of both human creativity and artificial intelligence. One way researchers are exploring the bounds of computational creativity is through the use of generative adversarial networks (GANs). GANs are a type of AI system that consists of two neural networks – a generator and a discriminator – that work together to produce new and unique outputs. The generator creates new data, such as images or music, while the discriminator evaluates the quality of the generated output. Through this process of iteration and feedback, GANs are able to produce...
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