"The U.S. Supreme Court today declined to grant a petition filed by Recentive Analytics, Inc. asking the Court to weigh in on whether the U.S. Court of Appeals for the Federal Circuit's (CAFC's) approach to patent eligibility for machine learning claims is improper. The petition was filed in October following an April 2025 decision by the CAFC that addressed an issue of first impression in the patent eligibility context; the opinion held that "claims that do no more than apply established methods of machine learning to a new data environment" are not patent eligible."
"Recentive originally sued Fox Corp., Fox Broadcasting Company, LLC, and Fox Sports Productions, LLC for infringement of four U.S. Patent, Nos. 10,911,811; 10,958,957; 11,386,367; and 11,537,960. The patents are directed to solving problems in the entertainment industry and television broadcasting with respect to optimizing the scheduling of live events and "network maps," which "determine the programs or content displayed by a broadcaster's channels within certain geographic markets at particular times." The district court ultimately granted Fox's motion to dismiss the suit for failure to state a claim on the ground the patents were ineligible under Section 101."
"The court said the claims of the patents failed at Alice step one as they were "directed to the abstract ideas of producing network maps and event schedules, respectively, using known generic mathematical techniques," and at step two the claims failed to show an "inventive concept" as "the machine learning limitations were no more than 'broad, functionally described, well-known techniques'" and claimed "only generic and conventional computing devices." On appeal, the CAFC agreed that 'the patents are directed to the abstract idea of using a generic machine learning technique in a particular environment, with no inventive concept'."
Recentive Analytics sued Fox entities asserting four patents that apply machine-learning techniques to optimize live-event scheduling and broadcaster network maps. The district court dismissed the complaint under Section 101, finding the claims directed to abstract ideas using generic mathematical techniques and lacking an inventive concept because the machine-learning limitations were broad, well-known techniques implemented on generic computers. The CAFC held that claims that merely apply established machine-learning methods to a new data environment are not patent eligible. The U.S. Supreme Court declined to review Recentive's petition challenging the CAFC decision.
Read at IPWatchdog.com | Patents & Intellectual Property Law
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