A hack revealed in detail how AI music generating app Suno scraped millions of songs, likely including copyrighted ones, from across the web to feed into its AI model, 404 Media reports.
Suno, which is currently embroiled in multiple ongoing copyright lawsuits, has already admitted in response to legal action that it used “essentially all music files of reasonable quality that are accessible on the open internet” to train its music-generating AI.
According to 404, the hack shed light on how that copyrighted music was obtained and funneled into datasets, with Suno pulling music and lyrics from sites including YouTube Music, Genius, and Deezer, in addition to stock music libraries like Jamendo, Freesound, Pond5, and the International Music Score Library Project (IMSLP).
Source code obtained by the hacker also pointed to the staggering scale at which Suno has swallowed up music from across the web. For instance, one file, titled “youtube_music,” contained “2,013,545 music clips,” while another file noted that Suno’s AI datasets held “113,879 hours of youtube_music.” Altogether, the file appears to host hundreds of thousands of hours of music.
The hacker, who goes by the pseudonym ellie.191, also claimed to 404 that they’d also been able to view sensitive Suno user data, including Stripe payment information.
In a statement, Suno told 404 that “as we have stated in public filings and disclosures, Suno’s AI models have been trained on publicly available music files and related metadata accessible on third-party websites on the open Internet.”
The company also insisted that its “goal has always been to help people create original new music, not replicate someone else’s.” That’s despite tests extensively showing how Suno can easily replicate published music, including the work of well-known artists.
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