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Patenting Machine Learning Inventions for Companies Outside the Software Industry

Original air date: 11/14/19

The use and development of artificial intelligence and machine learning technology is spreading from niche Silicon Valley software companies to almost all innovative businesses, including those outside the traditional software field. Stitch Fix CEO Katrina Lake recently said: “In 10 years, every ‘relevant’ company will be a tech company.” As such, a strategy for inventing and using machine learning technology, and for generating IP based on the resulting inventions, is essential to non-software companies.

This presentation focuses on assisting private patent practitioners, as well as in-house attorneys, in understanding the machine learning technology space, developing processes for identifying patentable inventions in the machine learning field, and patenting such inventions. The presentation defines machine learning, addresses strategies for drafting and prosecuting patent applications in the US, and discusses advantages and disadvantages that non software technology companies may have in obtaining patents in this space.

Presented by:

Gregory Rabin of Schwegman, Lundberg & Woessner
Aliza Carrano of Finnegan, Henderson, Farabow, Garrett & Dunner, LLP