Not A Categorical Ban- Federal Circuit Narrowed Spectrum of Patent Eligible Machine Learning Claims

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Why it matters

Core event: On April 18, 2025, the U.S. Federal Circuit affirmed the District of Delaware's dismissal of Recentive Analytics, Inc. v. Fox Corp. (No. 23-2437), ruling four patents ineligible under 35 U.S.C. § 101 for merely applying generic machine learning techniques to broadcast scheduling without improvements to the models themselves.[1][4][5][6]

Involved parties: Plaintiff Recentive Analytics, Inc. sued defendant Fox Corp. for infringing patents on machine learning for TV schedules and network maps; Judge Dyk wrote the panel opinion.[1][4][6][8]

Context and timeline: Recentive conceded claims covered pre-computer human tasks; under Alice step one, court found abstract idea of generic ML on new data; step two lacked transformative elements. Decision clarifies no categorical ML ban but requires model improvements, building on Alice/Mayo framework amid rising AI patents.[1][4][5][6][7]

Newsworthy now: Issued Jan 27, 2026 coverage highlights 2026 implications for ML patenting—demands technical innovations over generic applications—amid USPTO guidance and PTAB shifts like Desjardins, affecting AI filings vulnerable to early §101 challenges.[3][4][7][9]

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