Artists meet machine learning
Meet six artists creatively pushing the boundaries of generative ML and natural language processing.
Editor’s note: A version of this article appeared on The Keyword.
From January to May 2020, six international artists collaborated with Google creative technologists to explore machine learning techniques in film, poetry, sound art, and interactive storytelling, as part of an inaugural grant-making collaboration between Google Research and Google Arts & Culture. Today, we are publishing the outcomes of the grants.
EXPLORE THE ARTISTS AND ARTWORKS
Hip Hop Poetry Bot by Alex Fefegha
Can AI rap? Alex explores speech generation trained on rap and hip hop lyrics by Black artists. For the moment it exists as a proof of concept, as building the experiment in full requires a large, public dataset of rap and hip hop lyrics on which an algorithm can be trained, and such a public archive doesn’t currently exist. The project is therefore launching with an invitation from Alex to rap and hip hop artists to become creative collaborators and contribute their lyrics to create a new, public dataset of lyrics by Black artists.
The Nonsense Laboratory by Allison Parrish
Allison invites you to adjust, poke at, mangle, curate and compress words with a series of playful tools in her Nonsense Laboratory. Powered by a bespoke code library and machine learning model developed by Allison Parrish you can mix and respell words, sequence mouth movements to create new words, rewrite a text so that the words feel different in your mouth, or go on a journey through a field of nonsense.
Let Me Dream Again by Anna Ridler
Anna uses machine learning to try to recreate lost films from fragments of early Hollywood and European cinema that still exist. The outcome? An endlessly evolving, algorithmically generated film and soundtrack. The film will continually play, never repeating itself, over a period of one month.
Dhvāni by Budhaditya Chattopadhyay
Budhaditya brings a lifelong interest in the materiality, phenomenology, political-cultural associations, and the sociability of sound to Dhvāni, a responsive sound installation, comprising 51 temple bells and conducted with the help of machine learning. An early iteration of Dhvāni was installed at EXPERIMENTA Arts & Sciences Biennale 2020 in Grenoble, France. Read more about the project.
Neural Swamp by Martine Syms
Martine uses video and performance to examine representations of blackness across generations, geographies, mediums, and traditions. For this residency, Martine developed Neural Swamp, a play staged across five screens, starring five entities who talk and sing alongside and over each other. Two of the five voices are trained on Martine’s voice and generated using machine learning speech models. The project will premiere at The Philadelphia Museum of Art and Fondazione Sandretto Re Rebaudengo in Fall 2021. Read more about the project.
Knots of Code by Paola Torres Núñez del Prado
Paola studies the history of quipus, a pre-Columbian notation system that is based on the tying of knots in ropes, as part of a new research project, Knots of Code. The project’s first work is a Spanish language poetry-album from Paola and AIELSON, an artificial intelligence system that composes and recites poetry inspired by quipus and emulating the voice of the late Peruvian poet J.E. Eielson. Read more about the project.
Artists & Machine Intelligence (AMI) is a program at Google that brings together artists, academics and engineers to realize research and projects with machine intelligence. Questions? Feedback? Tweet us or email: artwithmi@google.com
