A Federal Circuit panel concludes that patents merely applying generic machine learning to new datasets lack eligibility under the Alice framework, requiring a transformative inventive aspect beyond routine computing.

Key points

• Federal Circuit holds Recentive’s ML Training and Network Map patents ineligible under Alice Steps 1 and 2.
• Claims reference generic ML models trained on historical event, venue, and weather datasets without technical detail.
• Patents lack inventive concept as they recite conventional computing components and broad machine learning limitations.
• Court emphasizes that efficiency gains alone cannot convert an abstract idea into patent-eligible subject matter.
• Affirms district court’s denial of amendment as any changes would remain technologically conventional.