Machine Learning
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
Exhibitions
- Lifeforms - 180 Studios, London, 2022
- AI : More Than Human, Barbican, London, 2019
- Between Us, Stiftung Kunsthalle Mainz, Germany, 2019
- Fluid Bodies, Borusan Contemporary, Istanbul, 2018
- San Francisco Dance Film Festival, 2018
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: Audio Motion
Dancer/Choreographer: Dwayne-Antony Simms