New Worlds

Inside an abstract place, within a virtual reality, across a latent space, the territory of the New New New World (NNNW) stretches out. Its history peaks centuries ahead of the New World as found by the XV century colonial Europe, and it does so after the Contemporary World as well. The worlding of it, the worldbuilding of it, seems to require a post-post-colonial politics as it is not only to be discovered but, just as the New World to some extent, to be also generated. Such politics, implying both an abducted and an abductive cognition, both a praxis of unlearning and one of designation and objectification, both an inside and an outside view, define an in-between kind of mediator, or as it were, a post-contemporary Malitzin.

Originally, the NNNW only existed within the memory of the AI model that, at the moment of its release, knew better than every other AI what the human world looked like: the BigGAN. To acquire such knowledge, BigGAN was trained on ImageNet –for years, the largest dataset for AI training, assembled to “map the entire world of objects”, according to its creators– which made it capable of generating accurate images of the more-than-20 thousand ImageNet object classes, comprehending around 14 million tagged images. Born from a “large scale GAN training for high fidelity natural image synthesis” (Andrew Brock + Jeff Donahue + Karen Simonyan, 2019), it is capable of “artificial” image synthesis –more precisely, synthesis of artificial objects. Within its Latent Space, a series of new new new objects –or Xenobjects, as I call them– all of them differentiable from ImageNet’s object classes in which it was trained, potentially exists. Even after having landed on the NNNW and having developed a basic cosmography of it already, I wonder if “we are still far from understanding the hidden world of the [BigGAN’s] latent space” (Zaid Alyafeaid, 2019).

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(Research in progress)