AP (Hacker News):
A federal judge has approved a $1.5 billion copyright settlement in which artificial intelligence company Anthropic will pay thousands of authors about $3,000 per book after using pirated copies of their works to train its Claude chatbot.
[…]
Bestselling thriller novelist Andrea Bartz first brought the suit with two other authors in 2024. It’s the first major settlement in dozens of AI copyright lawsuits that are still working their way through courts.
Somewhat ironic given recent claims from Anthropic about others training their AI on its work.
Previously:
Jason Koebler (tweet, Reddit):
The AI music generation tool Suno scraped millions of songs and lyrics from YouTube Music, Deezer, and Genius, as well as from the stock music libraries Pond5, Jamendo, Freesound, the International Music Score Library Project, and podcasts via RSS feeds, according to a hacker who breached the company and shared data about Suno’s training libraries with 404 Media. The hacker was also able to access user information for hundreds of thousands of Suno’s customers, as well as Stripe payment information, they said.
[…]
As part of these legal proceedings, Suno previously admitted that it was trained on “essentially all music files of reasonable quality that are accessible on the open internet,” which included a total of “tens of millions of recordings.” Suno has been making the argument that it is allowed to train on copyrighted works as fair use in those cases, one of which has been settled.
Suno has long acknowledged that its AI music generator relied on the scraping of millions of songs available across the internet, but a new hack reveals just how the company pulled from streaming services and websites[…] all while user information remained vulnerable.
[…]
“Our goal has always been to help people create original new music, not replicate someone else’s. That’s why we build our models around what we call ‘Original Creation, By Design,’” the spokesperson said in a statement. “For example, we intentionally do not use artist names as a category of training metadata because we want our models to help people create brand new songs, not music that replicates other artists’ existing work. It’s also why we built Suno with detection filters that block or prevent a user from using specific artist, song, or album names as prompts, and prevent users from uploading lyrics or sound recordings that match existing works.”
Previously:
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