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Hype Cycle: Machine Learning

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Hype Cycle: Machine Learning
When will machines achieve human agility?
Hype Cycle ­is a series of futurist films exploring human-machine collaboration through performance and emerging technologies.

Machine Learning is the second set of films in the Hype Cycle series. It builds on the studio’s 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 from Universal Everything 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.

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
Hype Cycle: Machine Learning
Published:

Hype Cycle: Machine Learning

A futurist film asking: when will machines achieve human agility?

Published: