An aria sung by an algorithm, a lyrical exploration of fire's varied moods and landscapes as interpreted by a DCGAN model. The interplay of data and pixels, drawn from a vast library of images, gives rise to a visual harmony that speaks to the transformative power of fire and AI alike. These pieces, with their 64-pixel genesis, are a digital ode to the primal and the ephemeral, resonating with the deep-rooted human fascination with flame.
Channeling the fire myths of the world, Prometheus, the Phoenix, the gods of the sun and flame. A story of technology brought to humans; to myths of destruction and rebirth. To be immortal; to be a god; it is always a paradox of fire and technology. The morality of the fire is always in question but we desire it and fear it. And yet it has changed us, we have learned so much since we first touched fire. We used it to destroy the wood, smelt the metal and build the chip. And now we teach and show the fire what we know; what we create and our reflection is there telling us our faults. The GAN is but a single neuron in a blazing star; a greater fire is coming.
One of 200 unique pieces of art in Painting With Fire: A History in GANs. Exploring the history of generative adversarial networks GAN as represented by fire. https://bardionson.com/painting-with-fire
DCGAN - Radford, Alec; Metz, Luke; Chintala, Soumith . "Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks"
GAN - Goodfellow, Ian; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). Generative Adversarial Nets (PDF). Proceedings of the International Conference on Neural Information Processing Systems (NIPS 2014). pp. 2672–2680.|2014|https://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf
