Algorithm imagines train ride
Set to the pulsing, ethereal sounds of Steve Reich’s minimalist score Music for 18 Musicians (1974-6), this video by the French computer programmer Damien Henry is a clever visual demonstration of machine learning – a term coined by the US computer scientist Arthur Samuel (1901-1990) to describe an algorithm that gives computers the ‘ability to learn without being explicitly programmed’.
— Damien Henry (@dh7net) 7 mei 2017
Using several videos recorded from windows during train rides, Henry trained an algorithm to predict what the next frame of a train ride should look like. Then, starting with a single frame chosen by Henry, the algorithm generated, to the best of its ability, scenes from an hour-long train ride, improving itself roughly every 20 seconds. The resulting video demonstrates machine learning in action through a dreamy, impressionistic take on the experience of observing flowing, fleeting landscapes passing by. Though machine-learning algorithms are used more practically in applications where adaptability is greatly advantageous, such as anti-virus software and driverless cars, there’s an undeniable charm to seeing a computer engage in a version of one of our more ephemeral but corporeal experiences – the train ride.