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Weighing the Benefits: How Much Weight Will Your Survey Have in Court?
As consumer surveys become increasingly common forms of evidence in matters involving copyright, patent or trademark infringement, so too do Daubert challenges that attempt to disqualify that evidence. However, getting admitted into court is no guarantee of success — you are not over the entire Daubert hurdle just yet. The next step is ensuring that your survey is convincing the fact finders that your survey's results are dependable and useful.
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IP News
Federal Circuit: Faulty Claim Construction Does Not End Patentability Determination Federal Circuit: Notice to Market Bio Product Not Negated By New Applications
Features

What You Need to Know About the USPTO's Proposed Rule Changes to PTAB Trials
On May 27, 2020 the U.S. Patent and Trademark Office (USPTO) proposed rule changes to govern inter partes review (IPR), post-grant review (PGR), and covered business method (CBM) review proceedings at the PTAB. This article provides a summary of each proposed rule change and its potential impact on PTAB practice.
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Statute of Limitations In Copyright Ownership Disputes: Questions from the Everly Brothers Case
Don and Phil Everly's flawless harmonies that resulted in a string of hits in the 1950s and '60s regrettably ended in acrimony. The Sixth Circuit recently issued a decision in a dispute between Phil's heirs and Don over copyright ownership of the No. 1 hit "Cathy's Clown," in which concurring Judge Eric E. Murphy raised important questions about when the statute of limitations should begin to run in copyright cases and whether courts have been correctly applying the law.
Features

Survey Says: Tips on Getting Over the Daubert Hurdle
Surveys can provide useful evidence in litigation if they are conducted by a qualified expert employing reliable methods that survive a Daubert challenge. In the first of a series of articles drawing on our review of over 300 U.S. court rulings in cases involving surveys, including over 150 Daubert motions, we provide some suggestions for getting survey evidence admitted for consideration in court.
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Recent Court Views on "Making Available" Controversy In Copyright Infringement
Federal courts have long disagreed over whether the unauthorized "making available" of a plaintiff's works to the public is sufficient to constitute copyright infringement under the U.S. Copyright Act. Two June District Court decisions demonstrated the differences between the views of the Fourth and Ninth Circuits.
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IP News
Federal Circuit Finds Preamble Not Limiting and Claims Reciting Means-Plus-Function Limitations Without Disclosure of Corresponding Structures Cannot Be Determined Unpatentable as Indefinite in an IPR Proceeding Federal Circuit Finds That District Court Correctly Applied the Disclosure-Dedication Doctrine In Granting a Motion for Judgment of Non-Infringement on the Pleadings
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Eliminating Willfulness as a Prerequisite to Recovering an Infringer's Damages in Dilution Cases
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.
Features

U.S. Supreme Court Rejects 'Defense Preclusion' in Trademark Suit
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
Features

Artificial Intelligence and Copyright: Ownership and Fair Use
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.
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