For Google’s new text-based music generative AI, the contrast between input and interpretation creates opportunity for discovery.
From ChatGPT writing code for software engineers to Bing’s search engine sliding in place of your bi-weekly Hinge binge, we’ve become obsessed with the capacity for artificial intelligence to replace us.
MusicLM takes on this challenge by generating audio clips from descriptions like “a calming violin melody backed by a distorted guitar riff,” even accounting for less tangible inputs like “hypnotic and trance-like.” It approaches this thorny question of music categorization with a refreshing sense of self awareness. Rather than focusing on lofty notions of style, MusicLM grounds itself in more tangible attributes of music with tags such as “snappy”, or “amateurish.
In a way — by fostering an exchange that welcomes moments lost in translation — MusicLM’s language-based structure positions the model as a sounding board: as you prompt the model with a vague idea, the generation of approximates help you figure out what you actually want to make.With their experience producing Chain Tripping — a Grammy-nominated album entirely made with MusicVAE — the band YACHT chimes in on MusicLM’s future in music production.
Nonetheless, both YACHT and the MusicLM team agrees that MusicLM — as it currently is — holds promise. “Either way there’s going to be a whole new slew of artists fine-tuning this tool to their needs,” Rob contends.
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