Strafford will be offering a webinar entitled "Patent Drafting for Machine Learning: Structural Claim Limitations, Avoiding §101 or §112 Rejections" on February 13, 2018 from 1:00 to 2:30 pm (EST). Gregory Rabin of Schwegman Lundberg & Woessner and Michael D. Stein of Baker & Hostetler will provide guidance to patent practitioners on overcoming the challenges when seeking patent protection for machine learning inventions, and also discuss what can be done to anticipate and minimize the risks of § 101 or § 112 rejections. The webinar will review the following issues:
• What hurdles must patent counsel overcome to demonstrate inventorship?
• How can patent counsel meet the requirements under § 101 and § 112 in machine learning patent applications?
• What steps should patent counsel take to minimize the likelihood of § 101 or § 112 rejections?
The registration fee for the webcast is $297. Those interested in registering for the webinar, can do so here.