Machine Hallucinations – ISS Dreams transforms a vast data set of 1.2 million images captured from the International Space Stations (ISS), along with additional satellite images of Earth’s topology, into a dynamic data painting. Each version of the machine’s dream sequences is derived from a different generative adversarial network (GAN) latent walk, exploring artificial intelligence’s capacity to reach its own subconscious and offering an avant- garde form of cartographic aesthetics.

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About RAS : Machine Hallucinations

Machine Hallucinations is an ongoing project of data aesthetics based on collective visual memories of space, nature, and urban environments. Since the inception of the project in 2016 (Google AMI Residency), our studio has been utilizing machine intelligence as a collaborator to human consciousness, specifically DCGAN, PGAN and StyleGAN algorithms trained on these vast datasets to unfold unrecognized layers of our external realities. We collect data from digital archives and publicly available resources and process them with machine learning classification models such as CNN’s, Variational Autoencoders and deep ranking, to filter out people, noise and irrelevant data points. The sorted image datasets are then clustered into thematic categories to better understand the semantic context of the data universe.

This expanding data universe not only represents the interpolation of data as synthesis, but also becomes a latent cosmos in which hallucinative potential is the main currency of artistic creativity. In order to capture these hallucinations from a multi-dimensional space, we use NVIDIA’s StyleGAN, StyleGAN2 and StyleGAN2 ADA which generates a model for the machine to process the archive and the model is trained on subsets of the sorted images, creating embeddings in 1024 dimensions.

As a masterfully curated multi-channel experience, Machine Hallucinations brings a self-regenerating element of surprise to the audience and offers a new form of sensational autonomy via cybernetic serendipity.

“In 2016, during my artist residency at Google’s Artists and Machine Intelligence (AMI) program, I coined the terms ‘AI Data Painting’and ‘AI Data Sculpture’ as a way to encapsulate a groundbreaking exploration into the creative capacities of artificial intelligence. This concept was born from a profound curiosity: if a machine can learn, can it also dream? Can it hallucinate? These questions propelled my artistic inquiry, leading to the development of visual works that transcend traditional art forms. By harnessing vast datasets and AI algorithms, I sought to visualize the dreams of machines, creating ethereal landscapes that blur the line between the digital and the physical. AI Data Painting thus represents not just a new technique, but a philosophical pondering on the evolving relationship between human creativity and machine intelligence, inviting viewers to contemplate the potential for AI to not only mimic reality but to imagine beyond it.”