Patent Drafting for Machine Learning: Claim Strategy, Patent Eligibility, and Disclosure Requirements for the U.S. and Europe
Partner, Richard Kennedy is a panelist in a live 90-minute premium CLE video webinar with interactive Q&A on Tuesday 2 March, 2021.
This CLE webinar will assist patent practitioners in drafting high quality patent applications for machine learning inventions. The panel will discuss different claim styles and framings which may be appropriate for different machine learning inventions, how to anticipate and minimize the risks of Sect. 101 or 112 rejections, and best practices for success before the European Patent Office (EPO).
- Understanding the components of a machine learning invention
- Claim strategies for machine learning inventions, style, and framing
- Current state of subject matter eligibility for machine learning in the U.S. and Europe
- Disclosure requirements in the U.S. and Europe
- Drafting techniques for satisfying patent eligibility and disclosure requirements
The panel will review these and other relevant issues:
- What is the appropriate way to claim machine learning inventions?
- How can patent counsel meet the requirements under Sect. 101 and 112 in machine learning patent applications?
- How does the EPO treat patent applications for machine learning technologies differently than the USPTO?
- What steps should patent counsel take to satisfy patent eligibility and disclosure requirements?
For more information and to register to attend, please click here.
Richard is a European and Chartered Patent Attorney and a partner at Venner Shipley LLP. He has significant expertise in artificial intelligence and deep learning based technologies, and is the lead for the firm’s AI practice group. Clients describe him as having “very strong technical skills on complex machine learning subject matter” and being “highly in tune with ongoing policy developments, such as proposed (since adopted) changes at the European Patent Office regarding examination of artificial intelligence subject matter”.