Machine learning is increasingly important and is at work in many things used today, from internet searches to navigating traffic. Inventions in the field of machine learning pose challenges for patent practitioners seeking patent protection. However, what is patent eligible in the context of software inventions is not always clear.
Machine learning inventions should be eligible for protection, at least in the United States, but for patent-eligibility purposes, such designs must be described and claimed correctly and given the current state of the law. Counsel may also face challenges when seeking to comply with the enablement requirement under Sect. 112. Structural claim limitations can be used to strengthen patents for machine learning inventions and will benefit applicants by producing valid and enforceable patents.
Counsel should also understand the EPO’s approach to assessing the patentability of machine learning inventions. Counsel needs to be well versed in both the U.S. and EU approach to make the most of the patent protection available.
In this presentation, we will examine the challenges under Sections 101 and 112 and what patent counsel can do to overcome those challenges. More specifically, we will review these and other relevant issues:
- How can patent counsel meet the requirements under Sect. 101 and 112 in machine learning patent applications?
- What steps should patent counsel take to minimize the likelihood of Sect. 101 or 112 rejections?
- How does the EPO treat patent applications for machine learning technologies differently than the USPTO?
We will reserve time for a lively discussion and Q&A session.
MICHAEL STEIN has broad and deep experience working with technology companies and advising clients in the field of intellectual property protection and enforcement. He focuses his practice on patent portfolio development and counseling and client counseling in respect to industry standard-setting activities and open source software. Notably, Michael is well-versed in the regulations and nuances of complex U.S. and international patent laws. He is presently concentrating on developing strategies for protecting inventions in the fields of artificial intelligence, machine learning, and blockchain.
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