Federal Circuit Agrees with the USPTO: an AI System Cannot be an Inventor

Attorney: Kurt M. Berger, Ph.D.
August 16, 2022

The Federal Circuit recently affirmed a decision in the Eastern District of Virginia holding that the Patent Act unambiguously requires an inventor to be a natural person.<... Read more

The Ongoing Patent Dispute Over Innovative ML-Based Pattern Recognition

Attorney: Yuki Onoe
April 18, 2022

Support Vector Machine-Recursive Feature Elimination (SVM-RFE) is a technology which can be used to find relevant patterns in a large data set such as the data generated in the sequencing of genomes and produce smaller subsets. In Health Discovery Corp. v. Intel Corp.[1], the patent owner HDC, in its complaint for infringement, discussed the innovative aspects of the technology:<... Read more

AI and Written Description: When Does an AI Patent Claim Cross the Line?

Attorney: Sameer Gokhale
June 28, 2021

Following Ed Garlepp’s great discussion on AI disclosure issues[1][2], I want to describe a related problem with AI and issues arising under the written description requirement that I often bring up when presenting on this topic. I started raising this topic following an episode of HBO’s Silicon Valley.  One of the characters who lives in the incubator depicted in the show, Jian Yang, pitches an app to venture capitalists called “See Food” which is described as a “Shazam for food.” The user takes a picture of food, and then the app returns an identification of the food.    Eventually Jian Yang does come up with an app that can identify food. The problem: it can only identify “hot dog” and “not hot dog.”  When asked why he only created an app that only recognizes one type of food, Jian Yang explains that identifying more foods will require scraping significantly more images of food from the Internet to use as training data for a computational model.<... Read more

Disclosing AI Inventions - Part II: Describing and Enabling AI Inventions

Attorney: Edwin D. Garlepp
April 30, 2021

In Part I of this series on Disclosing AI Inventions, we discussed the basics of machine learning and the unique disclosure challenges presented by the “black box” nature of trained machine learning models. Nevertheless, current U.S. patent laws are generally viewed as sufficient to ensure adequate disclosure of machine learning inventions to the public, and it will be left to the courts to shape the details of disclosure requirements through interpretation of existing patent laws.  In this Part II, we discuss techniques for disclosing machine learning inventions in compliance with the written description and enablement requirements of 35 U.S.C. 112(a).<... Read more

Tracking AI Prosecution Trends at the U.S. Patent Office

March 5, 2021

written by Alec Royka 

Following last week’s post on this blog (AI Patent Trends in the U.S. Patent Office: Is the U.S. Losing Its Lead?), we look deeper into the filing data of AI applications to better understand how the USPTO’s treatment of inventions in this field have evolved over time. AI applications are increasing rapidly, but what happens when these applications get into substantive prosecution? Patent practitioners who understand this information can better help their clients avoid some of the pitfalls present, potentially resulting in higher allowance rates and less office actions to disposition. The data presented throughout this post was compiled using Juristat and focuses on the USPTO’s Art Units which handle the greatest number of AI filings (2122, 2129, 2121, 2124, 2123, 2128, 2127), further filtered by USPC 706, which relates to “Data Processing – Artificial Intelligence.”<... Read more