Attorney:
Sameer Gokhale
December 13, 2022
In the Federal Circuit decision in Amgen Inc. v. Sanofi[1], while invalidating two of Amgen’s antibody patents, the CAFC made the following statement regarding the enablement requirement of 35 U.S.C. §112.<... Read more
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
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
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
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