Share on LinkedInShare on LinkedIn

ARTICLE · 07 APRIL 2017

Don't Be Left Flat: Words Matter When Drafting Patent Claims

Lewis Roca
Explore more from Lewis Roca

In Wasica Finance GmbH v. Continental Automotive Systems, Inc., No. 15-2078 (Fed. Cir. 2017), the patentee Wasica Finance discovered, among other things, the importance of using consistent terminology in the patent specification and claims.

United StatesIntellectual Property
Dustin Szakalski
Dustin Szakalski
Author LinkedIn connections

In Wasica Finance GmbH v. Continental Automotive Systems, Inc., No. 15-2078 (Fed. Cir. 2017), the patentee Wasica Finance discovered, among other things, the importance of using consistent terminology in the patent specification and claims.

The patent-in-suit, now expired U.S. Patent No. 5,602,524, is directed to a system for monitoring tire pressure in vehicles. In an appeal from two inter partes review decisions from the Patent Trial and Appeal Board, the United States Court of Appeals for the Federal Circuit affirmed in part that certain claims of the '524 patent are unpatentable as anticipated or obvious.

The '524 patent describes that conventional tire pressure monitors communicate pressure readings through electromagnetic signals, which are susceptible to interference that causes inaccurate pressure readings. The '524 patent attempts to address this deficiency by providing a pressure measuring device and a transmitter in each tire, and a corresponding receiver

We operate a free-to-view policy, asking only that you register in order to read all of our content. Please login or register to view the rest of this article.

Register for freeORLog in

View source

Related Articles

Legal Intelligence Newsletters: sign up for the latest legal and regulatory news on your chosen topics

Read more about

Related Comparative Guides

See more popular content from

Article

UMG v. DistroKid: When AI Becomes A Consumer Protection Issue

Universal Music Group's lawsuit against DistroKid raises a critical question about AI disclosure in consumer markets: when does the use of artificial intelligence become material information that must be disclosed to consumers? The case centers on allegations that DistroKid distributed mass-generated AI music while creating the impression it was created by legitimate human artists, potentially violating existing consumer protection laws even without specific AI disclosure requirements.
United StatesIntellectual Property
Frankfurt Kurnit Klein & Selz PC
Frankfurt Kurnit Klein & Selz PC
Article

U.S. Government Backs Fair Use For AI Training In OpenAI Copyright Litigation

The U.S. government has filed a Statement of Interest of the United States of America under 28 U.S.C. § 517 in the Southern District of New York multidistrict litigation over OpenAI’s use of copyrighted works to train large language models. The filing appears to be the federal government’s first direct intervention in the wave of artificial intelligence (AI) training copyright cases, and it advises the court to treat model training (separate from use of AI to generate outputs) on copyrighted text standing alone as a highly transformative fair use under current law.
United StatesIntellectual Property
Lowenstein Sandler LLP
Lowenstein Sandler LLP
Article

The Ninth Circuit Affirms Dismissal Of DMCA CMI Removal Claim Against AI Code Generator – Output Is A New Work Not A Copy Of Training Data

There was a significant ruling in the Doe v. Github case involving training of AI code generator models on open source. The United States Court of Appeals for The Ninth Circuit affirmed the district court ruling dismissing part of an action brought under the Digital Millennium Copyright Act (“DMCA”) by programmers against GitHub, Inc., and other defendants. The issues centered on whether defendants removed copyright management information (CMI) from content used to train the AI code generator models.
United StatesIntellectual Property
Sheppard
Sheppard
Article

Is This Real? Navigating AI Impersonation Under New And Existing Laws

Is this AI-generated, or is it real? As generative AI tools have become increasingly capable of creating realistic images, videos, and audio, they have also made it easier to impersonate real people without their consent. In response, states are increasingly adopting laws that impose civil and criminal liability for certain AI-generated content that replicates an individual’s identity, likeness, voice, or other personal attributes.
United StatesIntellectual Property
Wiley Rein
Wiley Rein
Article

The Trademark Scam Field Guide: Look-Alike Filing Sites, Fake USPTO Notices, And How To Get Out If You’ve Been Caught

A business decides to file a trademark. Someone on the team searches for a familiar online legal-services brand, clicks the first result, and lands on a site with a similar-sounding name, a polished design, five-star reviews, and a low flat fee. The application gets filed. Months later the business learns the “service” was not who they thought it was, the filing was signed by someone with no authority to sign it, and the USPTO has suspended the application along with hundreds or thousands of others from the same shop.
United StatesIntellectual Property
Harness IP
Harness IP
Article

AI Learning Or AI Copying? Ninth Circuit Weighs In

The Ninth Circuit held that GitHub Copilot's AI-generated code did not violate DMCA's copyright management information (CMI) removal provisions, even when output resembled source code, because the system generated new works through probabilistic patterns rather than retrieving and stripping information from existing copies. This decision establishes a critical distinction between AI systems that learn and generate versus those that retrieve and reproduce, with significant implications for how courts evaluat
United StatesIntellectual Property
Ballard Spahr LLP
Ballard Spahr LLP