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The Federal Circuit’s en banc decision in Williamson v. Citrix Online, LLC, 792 F.3d 1339 (Fed. Cir. 2015), expanded the potential application of 35 U.S.C. §112, ¶6, making it more likely that functional claim language will be construed as a means-plus-function limitation even in the absence of the word “means.” Patent claims that recite functions in connection with nonce words like “module,” “mechanism,” “element,” “device,” or even “processor” are now more likely to be deemed means-plus-function limitations. Whether a claim term is or is not subject to §112, ¶6 may be dispositive in some patent cases. For example, the specification must disclose a structure or algorithm for performing the means-plus-function limitation, and if no such structure is disclosed, the claim will be held invalid as indefinite. Recent cases applying Williamson have reached different results, with some decisions finding claims subject to §112, ¶6 and invalid for lack of structure and other decisions finding software claim terms to recite structural limitations not subject to §112, ¶6. While most of the decisions to date have been in the computer-related arts, interesting parallels exist in the life sciences and pharmaceutical fields. Below, we discuss recent decisions applying Williamson and provide practical insights and strategies for patent owners and accused infringers to consider when addressing the expanded application of §112, ¶6.
By Sarah Benowich
Romag Fasteners, Inc. v. Fossil, Inc.
The Supreme Court, settling a circuit split, held that, although highly important, willfulness is not a prerequisite for a trademark infringement plaintiff to obtain a profits award.
By Anthony J. Dreyer
On May 14, 2020, the U.S. Supreme Court resolved a circuit split, finding that any preclusion of litigation defenses must comply with traditional res judicata principles, and ruling that Lucky Brand was not precluded from asserting its defenses in its long-standing trademark litigation against Marcel Fashions Group
By Shaleen J. Patel and Sushmitha Rajeevan
Machine learning allows certain AI to create entirely new content based upon the materials it used to learn. In the process of creating new content, AI may create copies of copyrighted works in memory storage as a byproduct of its overall output sequence. This article explores authorship and ownership of such AI-generated content, and to what extent, if any, can copyrights be infringed upon when AI reproduces copyrighted works for machine learning.
By Rudy Kim and Chris Han
Holding that the parties’ executed agreement mooted the issues in the case, the Federal Circuit recently reversed a district court’s decision to grant summary judgment of non-infringement despite the parties’ agreement. The decision builds upon prior Federal Circuit case law giving effect to settlement agreements.