by Dennis Crouch
The Federal Circuit's AI-patent decision this week affirmed a district court's dismissal of the claims as ineligible, holding that "generic" machine learning technology is itself an abstract idea. Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 (Fed. Cir. Apr. 18, 2025).
In its decision, the court acknowledged the growing importance of machine learning, and exerted some care in limiting its holding:
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 under § 101.
At oral arguments, the patenee's attorney Robert Fredrickson (Goodwin) explained that one reason his client did not claim a new algorithm is that it would have raised 101 issues:
This wasn't an invention of a new machine learning technique, because that would fall into another one of this court's section 101 traps, is if the claim is improving the mathematical algorithm or making machine learning better, then we're claiming the natural law, the mathematical algorithm itself.
That question -- scope of protection for new machine learning algorithms -- will be left for another day.