Friday, January 12 marked the date of Flow Machines’ first musical release. Spearheaded by the highly venerated French composer Benoit Carré, the 15-track pop album entitled Hello World —a nod to the text traditionally used to test the functionality of various computer programs—is the collaborative fruit of many artists’ labor, including the Canadian folk artist Kyrie Kristmanson, the Belgian production team The Bionix and the Mercury Prize-nominated artist C. Duncan—as well as the Artificial Intelligence algorithm that ultimately crafted all of the album’s songs.
copyright by www.electronicbeats.net
AI has increasingly become associated with modernity and the age of convenience. While sophisticated Artificial Intelligence has been, until recent years, only a speculative feature of science fiction, it now drives our cars, provides us with medical diagnoses and plays—and conquers—the world’s greatest chess masters. Now, it’s even bleeding over into our creative industries. The research project Flow Machines, an outgrowth of the Sony Computer Science Laboratories in Paris, is one of a handful of emerging enterprises exploring the possibility of using algorithms to create music.
Music to the machine’s hears
Such machine learning-powered software is unique in its ability to produce complex outputs that can serve as decisions, predictions and recommendations that are based on patterns extracted from large data sets. In the case of Flow Machines, a project first conceptualized in 2012 and led by AI researcher François Pachet, a catalog of 13,000 songs was used to train statistical models that represent information about how atomic musical events, like notes and chords, follow in succession across different musical styles. These statistical models are then used to generate new melodic and harmonic sequences in a chosen style, serving as suggestions to musicians using the software during composition.
“The idea is that when an artist uses the system, the first thing he has to do is to decide which songs he wants the machine to be inspired by, whether that’s in the form of scores, lead sheets, or audio stems” Pachet said in an interview at the Flow Machines public launch in Paris. “The machine then analyzes all of these inputs, and the user asks, ‘Please generate a score based on whatever I gave you.’” The ostensible aim of the software, however, is not to replace musicians; it’s to help them generate new and unique ideas by giving them access to harmonies and melodic structures otherwise outside of their usual purview, not unlike a modern reimagining of Brian Eno’s Oblique Strategies.
Next Step in Music History
Carré and Pachet both maintain that Flow Machines is the logical next step in the history of music production. Visitors to the album’s launch party in Paris were greeted by posters depicting milestones in the history of music technology, such as the advent of Pythagorean tuning or the invention of Pro Tools. The effect was clearly intended to underscore the inevitability of AI-produced music. The installation also forced visitors to challenge their traditional perceptions of music-making. “What is a musician?” One sign on the wall asked. “We enter a new realm of music technology, producing music that couldn’t possibly be done before created by people who might not ordinarily think of themselves as musicians,” it answered. […]
read more – copyright by www.electronicbeats.net
Friday, January 12 marked the date of Flow Machines’ first musical release. Spearheaded by the highly venerated French composer Benoit Carré, the 15-track pop album entitled Hello World —a nod to the text traditionally used to test the functionality of various computer programs—is the collaborative fruit of many artists’ labor, including the Canadian folk artist Kyrie Kristmanson, the Belgian production team The Bionix and the Mercury Prize-nominated artist C. Duncan—as well as the Artificial Intelligence algorithm that ultimately crafted all of the album’s songs.
copyright by www.electronicbeats.net
Music to the machine’s hears
Such machine learning-powered software is unique in its ability to produce complex outputs that can serve as decisions, predictions and recommendations that are based on patterns extracted from large data sets. In the case of Flow Machines, a project first conceptualized in 2012 and led by AI researcher François Pachet, a catalog of 13,000 songs was used to train statistical models that represent information about how atomic musical events, like notes and chords, follow in succession across different musical styles. These statistical models are then used to generate new melodic and harmonic sequences in a chosen style, serving as suggestions to musicians using the software during composition.
“The idea is that when an artist uses the system, the first thing he has to do is to decide which songs he wants the machine to be inspired by, whether that’s in the form of scores, lead sheets, or audio stems” Pachet said in an interview at the Flow Machines public launch in Paris. “The machine then analyzes all of these inputs, and the user asks, ‘Please generate a score based on whatever I gave you.’” The ostensible aim of the software, however, is not to replace musicians; it’s to help them generate new and unique ideas by giving them access to harmonies and melodic structures otherwise outside of their usual purview, not unlike a modern reimagining of Brian Eno’s Oblique Strategies.
Next Step in Music History
Carré and Pachet both maintain that Flow Machines is the logical next step in the history of music production. Visitors to the album’s launch party in Paris were greeted by posters depicting milestones in the history of music technology, such as the advent of Pythagorean tuning or the invention of Pro Tools. The effect was clearly intended to underscore the inevitability of AI-produced music. The installation also forced visitors to challenge their traditional perceptions of music-making. “What is a musician?” One sign on the wall asked. “We enter a new realm of music technology, producing music that couldn’t possibly be done before created by people who might not ordinarily think of themselves as musicians,” it answered. […]
read more – copyright by www.electronicbeats.net
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