Found In Translation – Experiencing the process of machine translation

Found in Translation is an interactive, immersive installation where using their own spoken sentences, visitors viscerally experience the process of machine translation. Visualizations show how the machine learning model clusters words from different languages by semantic similarity, and translations are presented typographically and auditorily across 24 languages.

20/04/2021
NORAA (Machinic Doodles) – A human/machine collaborative drawing

Created by Jessica In, Machinic Doodles is a live, interactive drawing installation that facilitates collaboration between a human and a robot named NORAA – a machine that is learning how to draw. The work explores how we communicate ideas through the strokes of a drawing, and how might a machine also be taught to draw through learning, instead of via explicit instruction

11/12/2018
TraiNNing Cards – Flash cards to train your machines

Latest in the series of critical design projects by Shanghai design and research studio Automato, TraiNNing Cards is a set of 5000 training images, physically printed and handpicked by humans to train any of your machines to recognise first and favorite item in a house: a dog.

01/02/2017
Ethical Machines Podcast

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25/01/2016
School of Machines / Making & Make-Believe

Founded in Berlin, Germany, in 2014, School of MA provides unique, hands-on learning experiences at the intersection of art and technology in Europe. School’s founder Rachel Uwa speaks to the instructors Andrew Friend and Sitraka Rakotoniaina about the recent and future programmes.

18/12/2015
School of Machines, Making & Make-Believe

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20/02/2015
Numby by Pitaru and Paterson – Learning counting in weird and wonky ways

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07/03/2012
Floating Codes – The (spatial) topology of an artificial neural network

‘Floating Codes’ is a site-specific light and sound installation that explores the inner workings and hidden aesthetics of artificial neural networks – the fundamental building blocks of machine learning systems or artificial intelligence. The exhibition space itself becomes a neural network that processes information, its constantly alternating environment (light conditions/day-night cycle) including the presence of the visitors.

05/01/2022
Latentscape – Franz Rosati

Created by Franz Rosati, ‘Latentscape’ depicts exploration of virtual landscapes and territories, supported by music generated by machine learning tools trained on traditional, folk and pop music with no temporal and cultural limitations.

28/10/2021
Project Soli – World’s Tiniest Violin

Created by Design I/O, World’s Tiniest Violin is a ‘speed project’ that uses Google’s Project Soli – Alpha Dev Kit combined with the Wekinator machine learning tool and openFrameworks to detect small movements that look like someone playing a tiny violin and translate that to the volume and playback of a violin solo.

10/06/2016

Created by Refik Anadol in collaboration with Google’s Artists and Machine Intelligence program, ‘Archive Dreaming’ is a 6 meters wide circular installation that employs machine learning algorithms to search and sort relations among 1,700,000 documents.

Created by Seoul based artistic duo Shinseungback Kimyonghun, ‘Animal Classifier’ is an AI trained to divide animals into arbitrary classifications to foreground the imperfections and edge cases in classification systems.

Created by Sebastian Schmieg, ‘Decision Space’ explores how new datasets can enable new experiments in teaching computers how to understand images within a set of meaningful and complex categories.

The following is a documentation of a new course ran by Gene Kogan on Machine Learning for Artists at ITP-NYU in spring 2016.

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A P P A R E L is an augmented reality experimental fashion prototype by the Paris-based anticipatory design studio N O R M A L S. Turning data and network activity into identity and style, the project replaces the details of contemporary couture with jiggly mesh geometry digital overlays.

Created by Lauren Lee McCarthy & Kyle McDonald, Unlearning Language is an interactive installation and performance that uses machine learning to provoke the participants to find new understandings of language, undetectable to algorithms.

Found in Translation is an interactive, immersive installation where using their own spoken sentences, visitors viscerally experience the process of machine translation. Visualizations show how the machine learning model clusters words from different languages by semantic similarity, and translations are presented typographically and auditorily across 24 languages.

‘A Natural History of Networks / SoftMachine’ is an electrochemical algorithmic performance that probes an alternative computational and technological material regime.

Yuri Suzuki and Pentagram in collaboration with Counterpoint have re-imagined the Electronium – Raymond Scott’s instantaneous performance-composition machine.

Created by Jessica In, Machinic Doodles is a live, interactive drawing installation that facilitates collaboration between a human and a robot named NORAA – a machine that is learning how to draw. The work explores how we communicate ideas through the strokes of a drawing, and how might a machine also be taught to draw through learning, instead of via explicit instruction

The chAIr Project is a series of four chairs created using a generative neural network (GAN) trained on a dataset of iconic 20th-century chairs with the goal to “generate a classic”. The results are semi-abstract visual prompts for a human designer who used them as a starting point for actual chair design concepts. 

Latest in the series of experiments and explorations into neural networks by Memo Akten is a pre-trained deep neural network able to make predictions on live camera input – trying to make sense of what it sees, in context of what it’s seen before.

Created by Mike Hogan, Karen Hogan and Orkan Telhan, ‘Microbial Design Studio’ is a countertop biofabrication machine that brings together the capabilities of a biology wetlab into a single inexpensive piece of hardware to design, culture, and test genetically modified organisms.

Latest in the series of critical design projects by Shanghai design and research studio Automato, TraiNNing Cards is a set of 5000 training images, physically printed and handpicked by humans to train any of your machines to recognise first and favorite item in a house: a dog.

CAN interviews Grant D. Taylor, author of the 2014 book “When the Computer Made Art: The Troubled History of Computer Art,” on the past, present and future of digital art.

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Founded in Berlin, Germany, in 2014, School of MA provides unique, hands-on learning experiences at the intersection of art and technology in Europe. School’s founder Rachel Uwa speaks to the instructors Andrew Friend and Sitraka Rakotoniaina about the recent and future programmes.

Created by Martin Hertig at ECAL, Sensible Data is a playful installation consisting of three machines that collect user’s personal data, evaluates mood, age, gender and beauty, to create a ‘passport’ that user can take away but which also randomly sent (without user’s knowledge) to another participant.

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Sorry, this is Members Only content. Please Log-in. Join us today by becoming a Member. Archive: More than 3,500 project profiles, scores of essays, interviews and reviews.Publish: Post your projects, events, announcements.No Ads: No advertisements, miners, banners.Education: Tutorials (beginners and advanced) with code examples, downloads.Jobs Archive: Find employers who have recruited here in the past…

‘Floating Codes’ is a site-specific light and sound installation that explores the inner workings and hidden aesthetics of artificial neural networks – the fundamental building blocks of machine learning systems or artificial intelligence. The exhibition space itself becomes a neural network that processes information, its constantly alternating environment (light conditions/day-night cycle) including the presence of the visitors.

Created by Franz Rosati, ‘Latentscape’ depicts exploration of virtual landscapes and territories, supported by music generated by machine learning tools trained on traditional, folk and pop music with no temporal and cultural limitations.

Latest in the series of video essays by an artist and researcher Alan Warburton, is ‘RGBFAQ’, tracing the trajectory of computer graphics from WW2 to Bell Labs in the 1960s, from the visual effects studios of the 1990s to the GPU-assisted algorithms of the latest machine learning models.

‘Artificial Botany’ by fuse* is an ongoing project which explores the latent expressive capacity of botanical illustrations through the use of machine learning algorithms.

Created by Philipp Schmitt, “Why Would You Want to Picture It” is a sculpture and sound installation engaging with opacity of ‘black box’ machine learning algorithms.

Created by Tore Knudsen, ‘Pour Reception’ is a playful radio that uses machine learning and tangible computing to challenge our cultural understanding of what an interface is and can be. Two glasses of water are turned into a digital material for the user to explore and appropriate.

Created by Selcuk Artut, Variable is an artwork that explores the signification of terms in artists’ statements. The artwork uses machine learning algorithms to thoughtfully problematise the limitations of algorithms and encourage the visitor to reflect on poststructuralism’s ontological questions.

Created by Philipp Schmitt (with Margot Fabre), ‘Computed Curation’ is a photobook created by a computer. Taking the human editor out of the loop, it uses machine learning and computer vision tools to curate a series of photos from an archive of pictures.

Created by Design I/O, World’s Tiniest Violin is a ‘speed project’ that uses Google’s Project Soli – Alpha Dev Kit combined with the Wekinator machine learning tool and openFrameworks to detect small movements that look like someone playing a tiny violin and translate that to the volume and playback of a violin solo.

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