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Thompson Hine LLP, a full-service business law firm with approximately 400 lawyers in 11 offices, was ranked number 1 in the category “Most innovative North American law firms: New working models” by The Financial Times and was 1 of 7 firms shortlisted for The American Lawyer’s inaugural Legal Services Innovation Award. The firm has been recognized by the National Law Journal as a Legal Technology Trailblazer and featured by Bloomberg for its innovative service delivery models, which drive accuracy and predictability. The firm’s commitment to innovation is embodied in Thompson Hine SmartPaTHTM – a smarter way to work – predictable, efficient and aligned with client goals. For more information, please visit ThompsonHine.com and ThompsonHine.com/SmartPaTH.

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On October 9, U.S. Patent and Trademark Office (USPTO) Director John Squires submitted written testimony to the Senate Judiciary Subcommittee on Intellectual Property in which he emphasized that a strong and predictable system during patent examination is important to U.S. competitiveness and national security. Director Squires warned that USPTO uncertainty in making patent eligibility determinations may risk undermining American leadership in emerging technologies, such as artificial intelligence and machine learning.

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The director’s written testimony highlighted the USPTO’s recent Ex parte Desjardins decision as an example in which genuine technical improvements were recognized to satisfy patent eligibility standards.

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In <a href="https://www.uspto.gov/sites/default/files/documents/202400567-arp-rehearing-decision-20250926.pdf" target="_blank" rel="noreferrer noopener">Ex parte Desjardins, Appeal 2024-000567</a>, an Appeals Review Panel headed by Director Squires vacated a new ground of rejection under 35 U.S.C. § 101 that the Patent Trial and Appeal Board had entered in its decision against claims in a patent application relating to training a machine learning model in a way that preserved prior knowledge while learning new tasks. The Appeals Review Panel was convened by Director Squires sua sponte to review the decision.

The Appeals Review Panel concluded that the claims reflect an improvement in computer functionality and technology and, therefore, are not directed to an abstract idea. In that regard, the Appeals Review Panel found that the claims improve the functioning of the machine learning model itself when trained on sequential tasks.

The Appeals Review Panel credited benefits, namely reduced storage, reduced system complexity, and preservation of performance on earlier tasks during subsequent training, as technological improvements that were articulated by the specification of the patent application. Importantly, claim elements tied these benefits to a continual learning strategy that addresses a technical problem and provides a solution representing a practical improvement in how computers function.

The reversal of the new ground of rejection signals that Director Squires is interested in expanding the patent eligibility of artificial intelligence and machine learning claims, as well as a subtle but meaningful shift at the USPTO regarding the examination of these claims. This is encouraging news for innovators in artificial intelligence and machine learning technologies.

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This advisory bulletin may be reproduced, in whole or in part, with the prior permission of Thompson Hine LLP and acknowledgment of its source and copyright. This publication is intended to inform clients about legal matters of current interest. It is not intended as legal advice. Readers should not act upon the information contained in it without professional counsel.

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https://admin.thompsonhine.com/wp-content/uploads/2025/10/Intellectual-Property-Update-USPTO-Director-Squires-Defends-Expansive-Patent-Eligibility.pdf

USPTO Director Squires Defends Expansive Patent Eligibility

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