The hottest Copyright Issues Substack posts right now

Youtube has blocked the show again due to copyright claims, which the creator feels are unfair.
The show can be watched on Twitter, with live chats available for viewers.
There are also discussions about various topics, including legal issues and events during Pride Month.

Big music companies are likely to license their music to AI firms. This means that AI companies will pay for access to use real music to create new songs.
When artists sign with a music label, their music might be used to train AI without them knowing. If they want to opt out, they may have to be very influential in the industry.
People generally dislike AI-generated music, viewing it as low quality. Even so, it could become common in places like elevators or waiting rooms, which reflects concerns about its impact on genuine artistry.

Some people are late bloomers, meaning they achieve success later in life. It's often just a part of their personality, not because they are held back.
The estate of Sherlock Holmes has faced criticism for aggressively protecting copyright, even after losing court cases. Many believe this approach is unfair and counters the spirit of the original author's intent.
There are different types of luck, such as finding opportunities through being active or being open to new ideas. Creating opportunities can lead to unexpected successes.

It's a Wonderful Life is partly in the public domain, meaning anyone can make their own versions without asking for permission. But some parts of the story are still under copyright, which complicates things.
Different versions of the movie have emerged, like the Abridged and RiffTrax editions. These versions take out certain scenes and music to avoid copyright issues, which can lead to very different viewing experiences.
The film's copyright history has led to confusion and debate over what can be shown without permission. This situation highlights how public domain status can both help and hurt a movie's legacy.

Learning involves forgetting some details to form general ideas. This means that to truly learn, we often need to overlook specific differences.
Large Language Models (LLMs) can memorize details from the data they are trained on, which raises concerns about copyright issues and how much they reproduce existing content.
Finding a way to make LLMs forget specific details from training data, while still keeping their language abilities, is challenging and may require new techniques.

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