Brazilian copyright law

Oscars Draw Line: No AI Actors, Human Scripts Only Amid Industry Debate

The Academy of Motion Picture Arts and Sciences has introduced new rules that will prevent AI-generated performers from being eligible for Oscars, emphasizing that acting performances and screenplays must be human-authored. These updated guidelines also overhaul the international feature category, allowing films to qualify through major festival wins in addition to national submissions, and permit actors to receive multiple nominations within the same category for different roles. These significant changes, designed to address growing industry concerns and clarify creative authorship, will first apply to the 99th Academy Awards in March 2027.

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Trump Fires Copyright Chief After AI Fair Use Report

Register of Copyrights Shira Perlmutter was reportedly fired from her position following the release of a report on the fair use of copyrighted data for AI training. The report concluded that while some AI uses, like research, might qualify as fair use, commercial applications that compete with existing markets likely do not. This firing has been criticized as an “unprecedented power grab” possibly linked to the report’s unfavorable implications for AI companies. Simultaneously, Librarian of Congress Carla Hayden was also dismissed, although the White House cited unrelated reasons.

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Brazilian Samba Composer Sues Adele for Plagiarism: A Case of Musical Coincidence or Copyright Infringement?

Adele and Greg Kurstin face a plagiarism lawsuit in Brazil alleging their song “Million Years Ago” infringes on Toninho Geraes’s “Mulheres.” A judge initially ordered the song’s worldwide removal, a decision that has since been challenged. A subsequent conciliation hearing failed to reach an agreement, with the defendants’ absence and conflicting expert opinions on melodic similarity contributing to the impasse. The case highlights ambiguities in Brazilian copyright law and the potential ramifications of setting a precedent for removing songs based on perceived similarities.

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