
What happened
Sony and Universal Music Group filed yet another suit against Suno, saying its v6 model is trained on user outputs from earlier models that were themselves trained on unlicensed music ripped from YouTube and other sources.
Why it matters
Sony and UMG did not sign a licensing agreement with Suno, so the lawsuit tests whether training a new model on an older model's outputs removes the copyright problem or simply repeats it.
What to watch
The outcome hinges on whether Suno can show v6 truly started from scratch; the complaint says that unless it did, its models will continue to be built on unauthorized data.
WHO IT HITSThis lawsuit lands directly on AI music startups that build new models on top of earlier ones, and on the labels deciding whether to license their catalogs to them.
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Sony and Universal Music Group have already sued Suno before, and this latest filing shows the labels are not satisfied that the company's newer model solves the problem. Their central argument is that v6 does not stand on its own: it was trained on user outputs from earlier Suno models, and those earlier models were trained on unlicensed music taken from YouTube and other sources.
The complaint calls this 'model laundering,' arguing that training a 'new' model on the outputs of an infringing model does not eliminate the infringement. Sony also alleges that Suno used distillation to train v6, meaning it was trained to replicate the results of its previous, 'teacher' models, which were created using infringing data. For their part, Sony and UMG are notable holdouts who did not sign a licensing agreement with Suno. When v6 launched, Suno's Jack Brody told The Verge it was 'trained from the ground up, with a new set of data,' including 'user data,' but did not offer details beyond that. Suno later confirmed to Engadget that data includes 'creations' from users, but would not elaborate further when reached for comment.
The labels' argument amounts to a claim that unless Suno truly starts from scratch, its models will continue to be built on stolen data. For AI music startups and the labels weighing licensing deals, the case may turn on whether a model can ever be considered clean if it learns from an earlier model's outputs.
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