YACHT closes out Algorithmic Art Assembly with a live performance following their latest album CHAIN TRIPPING.
CHAIN TRIPPING is the band's seventh album and third with DFA Records. Recorded between the band's home in Los Angeles and Marfa, TX, the ten-song collection marks a shift in the group's relationship with technology and their art. Rather than trying to comment on existing platforms from within their own filter bubble, the band stripped their process down and rebuilt it using a technology entirely new to them--Artificial Intelligence, and more specifically, machine learning. The result is an album that merges invention and intimacy, "challenging" technology from code to content.
In order to compose CHAIN TRIPPING, YACHT needed to invent their own AI songwriting process. It was a journey of nearly three years. They first tried to discover any existing YACHT formulas by collaborating with engineers and creative technologists to explore their own back catalogue of 82 songs using machine learning tools.
"We listened to raw audio samples of a neural network trying to sing in Claire's voice," says Bechtolt. "We reduced our entire compositional output to MIDI data. We flattened our lyrics into text files, into words among millions that would be fed to a weird custom algorithm. We talked to pioneers of algorithmic composition, and to startup founders who promised us they could reproduce our sound in two hours or less."
Eventually they created their own working method, an uncharacteristically low-tech approach to a high-tech possibility, painstakingly stitching meaningful fragments of plausible nonsense together from extensive, seemingly endless fields of machine-generated music and lyrics, themselves emerging from models created with the help of generous experts in neural networks, deep learning, and AI. Armed with these custom and custom-tweaked machine learning models, YACHT was able to generate massive volumes of lyrical and melodic information--much of which was "hiding in-between" melodies in their our own back catalogue--which they then approached as source material, using a process more influenced by analog cut-up writing techniques than anything explicitly technological.
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CHAIN TRIPPING is the band's seventh album and third with DFA Records. Recorded between the band's home in Los Angeles and Marfa, TX, the ten-song collection marks a shift in the group's relationship with technology and their art. Rather than trying to comment on existing platforms from within their own filter bubble, the band stripped their process down and rebuilt it using a technology entirely new to them--Artificial Intelligence, and more specifically, machine learning. The result is an album that merges invention and intimacy, "challenging" technology from code to content.
In order to compose CHAIN TRIPPING, YACHT needed to invent their own AI songwriting process. It was a journey of nearly three years. They first tried to discover any existing YACHT formulas by collaborating with engineers and creative technologists to explore their own back catalogue of 82 songs using machine learning tools.
"We listened to raw audio samples of a neural network trying to sing in Claire's voice," says Bechtolt. "We reduced our entire compositional output to MIDI data. We flattened our lyrics into text files, into words among millions that would be fed to a weird custom algorithm. We talked to pioneers of algorithmic composition, and to startup founders who promised us they could reproduce our sound in two hours or less."
Eventually they created their own working method, an uncharacteristically low-tech approach to a high-tech possibility, painstakingly stitching meaningful fragments of plausible nonsense together from extensive, seemingly endless fields of machine-generated music and lyrics, themselves emerging from models created with the help of generous experts in neural networks, deep learning, and AI. Armed with these custom and custom-tweaked machine learning models, YACHT was able to generate massive volumes of lyrical and melodic information--much of which was "hiding in-between" melodies in their our own back catalogue--which they then approached as source material, using a process more influenced by analog cut-up writing techniques than anything explicitly technological.
YACHT closes out Algorithmic Art Assembly with a live performance following their latest album CHAIN TRIPPING.
CHAIN TRIPPING is the band's seventh album and third with DFA Records. Recorded between the band's home in Los Angeles and Marfa, TX, the ten-song collection marks a shift in the group's relationship with technology and their art. Rather than trying to comment on existing platforms from within their own filter bubble, the band stripped their process down and rebuilt it using a technology entirely new to them--Artificial Intelligence, and more specifically, machine learning. The result is an album that merges invention and intimacy, "challenging" technology from code to content.
In order to compose CHAIN TRIPPING, YACHT needed to invent their own AI songwriting process. It was a journey of nearly three years. They first tried to discover any existing YACHT formulas by collaborating with engineers and creative technologists to explore their own back catalogue of 82 songs using machine learning tools.
"We listened to raw audio samples of a neural network trying to sing in Claire's voice," says Bechtolt. "We reduced our entire compositional output to MIDI data. We flattened our lyrics into text files, into words among millions that would be fed to a weird custom algorithm. We talked to pioneers of algorithmic composition, and to startup founders who promised us they could reproduce our sound in two hours or less."
Eventually they created their own working method, an uncharacteristically low-tech approach to a high-tech possibility, painstakingly stitching meaningful fragments of plausible nonsense together from extensive, seemingly endless fields of machine-generated music and lyrics, themselves emerging from models created with the help of generous experts in neural networks, deep learning, and AI. Armed with these custom and custom-tweaked machine learning models, YACHT was able to generate massive volumes of lyrical and melodic information--much of which was "hiding in-between" melodies in their our own back catalogue--which they then approached as source material, using a process more influenced by analog cut-up writing techniques than anything explicitly technological.
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CHAIN TRIPPING is the band's seventh album and third with DFA Records. Recorded between the band's home in Los Angeles and Marfa, TX, the ten-song collection marks a shift in the group's relationship with technology and their art. Rather than trying to comment on existing platforms from within their own filter bubble, the band stripped their process down and rebuilt it using a technology entirely new to them--Artificial Intelligence, and more specifically, machine learning. The result is an album that merges invention and intimacy, "challenging" technology from code to content.
In order to compose CHAIN TRIPPING, YACHT needed to invent their own AI songwriting process. It was a journey of nearly three years. They first tried to discover any existing YACHT formulas by collaborating with engineers and creative technologists to explore their own back catalogue of 82 songs using machine learning tools.
"We listened to raw audio samples of a neural network trying to sing in Claire's voice," says Bechtolt. "We reduced our entire compositional output to MIDI data. We flattened our lyrics into text files, into words among millions that would be fed to a weird custom algorithm. We talked to pioneers of algorithmic composition, and to startup founders who promised us they could reproduce our sound in two hours or less."
Eventually they created their own working method, an uncharacteristically low-tech approach to a high-tech possibility, painstakingly stitching meaningful fragments of plausible nonsense together from extensive, seemingly endless fields of machine-generated music and lyrics, themselves emerging from models created with the help of generous experts in neural networks, deep learning, and AI. Armed with these custom and custom-tweaked machine learning models, YACHT was able to generate massive volumes of lyrical and melodic information--much of which was "hiding in-between" melodies in their our own back catalogue--which they then approached as source material, using a process more influenced by analog cut-up writing techniques than anything explicitly technological.
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