When discussing patentable inventions with data scientists, I often hear them dismiss their inventions under arguments such as these: “We’re using the same tools as everyone else,” “Augmenting data for the training set is well known,” “A similar thing has been done for car-bumper design” (said by the designer of a churro-making machine), “Configuring the neural-network hyperparameters is trivial,” and worst of all, “It’s obvious.” Data scientists often believe that their accomplishments are not patentable, but in-depth exploration of their work often uncovers patentable ideas. I am referring to data scientists that use machine-learning (ML) tools to uncover intrinsic relationships within a large corpus of data. Other data scientists design and improve these ML tools, and their work may also result in patentable ideas, which is a topic for discussing another day.
- Other Barks & Bites for Friday, February 23: Intel and Microsoft Announce Landmark Chip and IP Deal; Court Overturns $1 Billion Copyright Infringement Ruling Against Cox; and Reddit and Google Set to Announce AI Content Licensing Agreement
- Members of Congress Blast Biden on March-In Proposal and Pandemic Accord
- Rader’s Ruminations: The Most Striking (and Embarrassing) Legal Mistake in Modern Patent Law
- Supreme Court Denies Five IP Petitions on Issues from IPR Joinder to Contributory Trademark Infringement
- ‘Where Are the Designers on This?’: Some Post-Argument Thoughts on LKQ v. GM