Guest editor Nora N. Khan and fifteen luminaries question our problematic faith in and deference to AI. Exploring the limits of knowledge, prediction, language, and abstraction in computation, their collected essays and artworks measure the gap between machine learning hypotheticals and the mess of lived experience.
“How might we recognize in the pool of advanced computation, not just a reflection, but the underlying logic of technology, the stories it whispers to us from beyond the surface?”
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Artist Casey Reas explores what it’s like to make pictures with generative adversarial networks (GANs), specifically deep convolutional generative adversarial networks (DCGANs).
Drawing on his vast breadth of scientific and historical knowledge, Smil explains the difference between invention and innovation, and looks not only at inventions that failed to dominate as promised, but also at those that turned disastrous.
This book introduces this new literacy by teaching computer programming within the context of the visual arts. It offers a comprehensive reference and text for Processing (www.processing.org), an open-source programming language that can be used by students, artists, designers, architects, researchers, and anyone who wants to program images, animation, and interactivity.
With Many intelligences, Matteo Loglio lets us peek into the future and imagine a world where pots, cars and toasters will be as intelligent as we are (or maybe even more so). Without forgetting our current task: being the most intelligent beings on the planet also means being responsible for all the others.