PatentNext Summary: The Desjardins decision, co-authored by new USPTO Director John Squires, signals a potential shift toward greater patent eligibility for AI and software innovations. By vacating a § 101 rejection and warning that “categorically excluding AI innovations from patent protection in the United States jeopardizes America’s leadership in this critical emerging technology,” the Appeals
PatentNext Summary: The USPTO issued “Reminders” for examiners in Tech Centers 2100/2600/3600 addressing §101 eligibility for software and Artificial Intelligence(AI) / Machine Learning (ML)-related inventions; while not changing the MPEP, the guidance is meant to sharpen examination practice. It clarifies Step 2A, Prong One by limiting “mental process” to what can be practically performed in
PatentNext Summary: Recent rulings from the Northern District of California in Bartz v. Anthropic and Kadrey v. Meta provide the first substantive guidance on how the fair use doctrine applies to AI training, particularly for large language models (LLMs). Both courts found that using lawfully obtained copyrighted books for LLM training can qualify as “highly
PatentNext Summary: In Brightex Bio-Photonics, LLC v. L’Oreal USA, Inc., the U.S. District Court for the Northern District of California invalidated patent claims relating to AI-driven cosmetic recommendations, finding them directed to an abstract idea under 35 U.S.C. § 101. The court held that while the specification referenced artificial intelligence, the claims themselves failed to
PatentNext Summary: In two recent decisions, the Federal Circuit reaffirmed that merely applying artificial intelligence or digital techniques to a specific “field of use” does not satisfy patent eligibility under 35 U.S.C. § 101. In Recentive Analytics v. Fox Corp., claims directed to AI-assisted television scheduling were deemed abstract for lacking inventive implementation. Similarly, in
PatentNext Summary: The Federal Circuit’s decision in Recentive Analytics, Inc. v. Fox Corp. found that applying generic machine learning techniques to a new environment, without a specific technological improvement, is patent-ineligible under 35 U.S.C. § 101. The court emphasized that claims must articulate concrete technological advancements rather than merely applying established methods to different domains.
In a recent PTABWatch article titled “PTAB Provides Some Clarity on Artificial intelligence (AI) Obviousness in IPR decision,” the PTAB’s approach to evaluating obviousness in AI-related patents is examined. The article discusses the case Tesla, Inc. v. Autonomous Devices, LLC, where the PTAB invalidated all challenged claims of U.S. Patent Number 11,055,583, which pertained to
In a decision that underscores the importance of prior art in the context of AI patents, the PTAB recently issued a final decision in Tesla, Inc. v. Autonomous Devices, LLC, IPR2023-01173 (PTAB January 3, 2025), invalidating all challenged claims of U.S. Patent Number 11,055,583 (the “’583 patent”). The case provides some insight into how the
Agentic AI is transforming artificial intelligence by enabling systems to act independently, making decisions and solving problems autonomously across various industries. Its potential rapid development poses unique challenges for intellectual property protection, requiring innovative strategies to ensure these advancements are effectively safeguarded within the evolving IP landscape.
PatentNext Summary: Generative Artificial Intelligence (GenAI) patent application filings continue to rise at the U.S. Patent and Trademark Office (USPTO), with a significant concentration in Tech Center 2100, which focuses on computer architecture and software, particularly AI and simulation technologies. GenAI inventions commonly face Section 103 (obviousness) and Section 101 (subject matter eligibility) rejections, with