Press Release
Source: Law.com, Law360
Press Release
Press Contacts: Erik Cummins, Matt Hyams, Taina Rosa, Olivia Thomas
04.25.25
A team of Pillsbury litigators led by Silicon Valley partner Ranjini Acharya recently secured an appellate ruling upholding a defense win for Fox Corp., in a precedential machine learning decision by the Federal Circuit. The win was featured in Law.com’s Litigator of the Week column on April 25.
In its decision, the court found that four patents held by Recentive Analytics covering machine learning-backed methods for dynamic updating of television schedules were not eligible for patent protection. The court said in its ruling: “Machine learning is a burgeoning and increasingly important field and may lead to patent-eligible improvements in technology. Today, we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible.”
The case of first impression explored key patent eligibility issues under the U.S. Supreme Court’s Alice decision, which held in 2014 that abstract ideas are not patentable. This case was the first time the Federal Circuit had ruled on patent eligibility for machine learning, which is a subset of AI.
In response to the decision, Pillsbury stated: “This precedent setting decision affirms our longstanding contention that technological improvements created merely by the ordinary use of generic machine learning (or AI) are not patent eligible. We believe this decision has far-reaching implications, as courts and companies grapple with the best way to commercialize and use new AI technologies across a wide range of fields.”
The Pillsbury team included Acharya, who argued the case, along with Michael E. Zeliger, Evan Finkel and Michael S. Horikawa.
The case is Recentive Analytics Inc. v. Fox Corp. et al., 23-2437, in the U.S. Court of Appeals for the Federal Circuit.
To read more about the decision, see here.