You Thought It Wasn't Possible (Podcast)

The Board dismissed this petition for cancellation of Roman Atwood's registration for the mark SMILE MORE for various goods (stickers, backpacks, shirts) and for retail store service featuring clothing, denying petitioner's claim that the term fails to function as a mark.

Universal Music Group's lawsuit against DistroKid raises a critical question about AI disclosure in consumer markets: when does the use of artificial intelligence become material information that must be disclosed to consumers? The case centers on allegations that DistroKid distributed mass-generated AI music while creating the impression it was created by legitimate human artists, potentially violating existing consumer protection laws even without specific AI disclosure requirements.

On Oct. 7, 2026, at 18:00 UTC, the Internet Corporation for Assigned Names and Numbers (ICANN) will publish every new generic top-level domain (gTLD) application proceeding in the 2026 new gTLD Round, including who applied...

The U.S. Copyright Office recently released a report on the human authorship requirement for materials to qualify for copyright protection.

The U.S. government has filed a Statement of Interest of the United States of America under 28 U.S.C. § 517 in the Southern District of New York multidistrict litigation over OpenAI’s use of copyrighted works to train large language models. The filing appears to be the federal government’s first direct intervention in the wave of artificial intelligence (AI) training copyright cases, and it advises the court to treat model training (separate from use of AI to generate outputs) on copyrighted text standing alone as a highly transformative fair use under current law.

Is this AI-generated, or is it real? As generative AI tools have become increasingly capable of creating realistic images, videos, and audio, they have also made it easier to impersonate real people without their consent. In response, states are increasingly adopting laws that impose civil and criminal liability for certain AI-generated content that replicates an individual’s identity, likeness, voice, or other personal attributes.

A business decides to file a trademark. Someone on the team searches for a familiar online legal-services brand, clicks the first result, and lands on a site with a similar-sounding name, a polished design, five-star reviews, and a low flat fee. The application gets filed. Months later the business learns the “service” was not who they thought it was, the filing was signed by someone with no authority to sign it, and the USPTO has suspended the application along with hundreds or thousands of others from the same shop.

There was a significant ruling in the Doe v. Github case involving training of AI code generator models on open source. The United States Court of Appeals for The Ninth Circuit affirmed the district court ruling dismissing part of an action brought under the Digital Millennium Copyright Act (“DMCA”) by programmers against GitHub, Inc., and other defendants. The issues centered on whether defendants removed copyright management information (CMI) from content used to train the AI code generator models.

In recent video game news, gaming giant Nintendo filed and settled a lawsuit against the developers of the popular Nintendo Switch emulator, Yuzu.

The Ninth Circuit held that GitHub Copilot's AI-generated code did not violate DMCA's copyright management information (CMI) removal provisions, even when output resembled source code, because the system generated new works through probabilistic patterns rather than retrieving and stripping information from existing copies. This decision establishes a critical distinction between AI systems that learn and generate versus those that retrieve and reproduce, with significant implications for how courts evaluat