πŸ‘€ Machine Learning

HD video
2018
Stereo sound

Machine Learning is the second set of films in our Hype Cycle series. It builds on our past experiments with motion studies, and asks: when will machines achieve human agility?

Set in a spacious, well-worn dance studio, a dancer teaches a series of robots how to move. As the robots’ abilities develop from shaky mimicry to composed mastery, a physical dialogue emerges between man and machine – mimicking, balancing, challenging, competing, outmanoeuvring.

Can the robot keep up with the dancer? At what point does the robot outperform the dancer? Would a robot ever perform just for pleasure? Does giving a machine a name give it a soul?

These human-machine interactions are inspired by the Hype Cycle trend graphs produced by Gartner Research, a valiant attempt to predict future expectations and disillusionments as new technologies come to market.

Available for licensing, screenings and exhibitions

Editions

Edition of 6 with 2 artist proofs

Exhibitions

Can humans teach machines to move? These four animated films use research into motion capture for a collaboration with dancer and choreographer Dwayne-Antony Simms. The duet between machine and dancer is a conversation of balance, mimicry and challenge. Here choreography reflects expressive human emotion but is also a tool to source accurate, useful data to makes beautiful moving forms. Simms’ improvisation with his initially invisible opponents – which change from smart materials to drone swarms - was transformed into a futurist, expressionistic and surprisingly natural pas de deux. Dance lets the humanity emerge from the abstract.

Credits

Creative Director: Matt Pyke
Animation: Joe Street
Sound Designer: Simon Pyke (Freefarm)
Senior Producer: Greg Povey
Motion Capture: Β­Audio Motion
Dancer/Choreographer: Dwayne-Antony Simms