AMECA
“Multiply the power of artificial Intelligence with an artificial body. Ameca is the physical presence that brings your code to life. The most advanced lifelike humanoid you can use to develop and show off your greatest machine learning interactions. This robot is the digital interface to the real world.” Engineered Arts
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“A U.K. robotics firm called Engineered Arts just debuted the first videos of its new humanoid robot, which is able to make hyper-realistic facial expressions. It’s a pretty stunning achievement in the world of robotics; it just also happens to be absolutely terrifying.
Named Ameca, the robot’s face features eyes, cheeks, a mouth, and forehead that contort and change shape to show off emotions ranging from awe to surprise to happiness. One of the new videos of Ameca shows it waking up and seemingly coming to grips with its own existence for the first time ever.” Neel V.Patel

No Longer Write – Mochiji
Powered by artificial intelligence’s Generative Adversarial Networks (GANs), the collected works from ancient Chinese Calligraphers, including Wang Xizhi, Dong Qichang, Rao Jie, Su Shi, Huang Tingjian, Wang Yangming, as input data for deep learning. Strokes, scripts and style of the masters are blended and visualized in “Mochiji”, a Chinese literature work paying tribute to Wang Xizhi. Wang is famous for his hard work in the pursuit of Chinese calligraphy. He kept practicing calligraphy near the pond and eventually turned the pond for brush washing into an ink pond (Mochi). The artwork provides a platform for participants to write and record their handwriting. After a participant finished writing the randomly assigned script from “Mochiji”, the input process is completed and the deep learning process will begin. The newly collected scripts will be displayed on the screen like floating ink on the pond, and slowly merge with other collected data to present a newly learnt script. The ink pond imitates process of machine learning, which observes, compares and filters inputs through layers of image and text, to form a modern edition of “Mochiji”.
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不再写 – Mochiji
以人工智能的生成对抗网络（GANs）为动力，将王羲之、董其昌、饶捷、苏轼、黄廷健、王阳明等中国古代书法家的作品作为深度学习的输入数据。向王羲之致敬的中国文学作品《麻糬》，将大师的笔触、文字、风格融为一体，形象化。王先生以对中国书法的刻苦钻研而著称。他一直在池塘边练习书法，最终把洗笔池变成了墨池（麻糬）。艺术作品为参与者提供了一个书写和记录他们笔迹的平台。参与者完成“Mochiji”中随机分配的脚本后，输入过程完成，深度学习过程将开始。新收集到的脚本会像池塘上的浮墨一样显示在屏幕上，并与其他收集到的数据慢慢融合，呈现出新学到的脚本。墨池模仿机器学习的过程，通过图像和文本的层层观察、比较和过滤输入，形成现代版的“年糕”。

The normalizing machine
The Normalizing Machine is an interactive installation presented as an experimental research in machine-learning. It aims to identify and analyze the image of social normalcy. Each participant is asked to point out who looks most normal from a line up of previously recorded participants. The machine analyzes the participant decisions and adds them to its’ aggregated algorithmic image of normalcy.

Dali Lives
Using an artificial intelligence (AI)-based face-swap technique, known as “deepfake” in the technical community, the new “Dalí Lives” experience employs machine learning to put a likeness of Dalí’s face on a target actor, resulting in an uncanny resurrection of the moustacheod master. When the experience opens, visitors will for the first time be able to interact with an engaging life-like Salvador Dalí on a series of screens throughout the Dalí Museum.

Living Archive

The Living Archive is an experiment between Studio Wayne McGregor and Google Arts and Culture – a tool for choreography powered by machine learning which generates original movement inspired by Wayne’s 25-year archive.

n-Polytope: Behaviors in Light and Sound after Iannis Xenakis
N_Polytope: Behaviors in Light and Sound After Iannis Xenakis is a spectacular light and sound performance-installation combining cutting edge lighting, lasers, sound, sensing and machine learning software inspired by composer Iannis Xenakis’s radical 1960s- 1970s works named Polytopes (from the Greek ‘poly’, many and ‘topos’, space). As large scale, immersive architectural environments that made the indeterminate and chaotic patterns and behaviour of natural phenomena experiential through the temporal dynamics of light and the spatial dynamics of sound, the Polytopes still to this day are relatively unknown but were far ahead of their time. N_Polytope is based on the attempt to both re-imagine Xenakis’ work with probabilistic/stochastic systems with new techniques as well as to explore how these techniques can exemplify our own historical moment of extreme instability.

Machine Hallucination
Refik Anadol’s most recent synesthetic reality experiments deeply engage with these centuries-old questions and attempt at revealing new connections between visual narrative, archival instinct and collective consciousness. The project focuses on latent cinematic experiences derived from representations of urban memories as they are re-imagined by machine intelligence. For Artechouse’s New York location, Anadol presents a data universe of New York City in 1025 latent dimensions that he creates by deploying machine learning algorithms on over 100 million photographic memories of New York City found publicly in social networks. Machine Hallucination thus generates a novel form of synesthetic storytelling through its multilayered manipulation of a vast visual archive beyond the conventional limits of the camera and the existing cinematographic techniques. The resulting artwork is a 30-minute experimental cinema, presented in 16K resolution, that visualizes the story of New York through the city’s collective memories that constitute its deeply-hidden consciousness.

Discrete Figures
‘Discrete Figures’ unites the performing arts and mathematics in a dramatic exploration of the relationship between the human body and computer generated movement (simulated bodies) born from mathematical analysis. As an additional layer of complexity, the performance piece utilizes drones, A.I., and machine learning in the quest for a new palette of movement to foster undiscovered modes of expressive dance that transcend the limits of conventional human subjectivity and emotional expression.