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.
Recent Posts
- IP Innovators – From Patent Office to Managing Partner: Chris Agrawal’s Journey
- In Sonos v. Google, the Federal Circuit Has a Chance to Fix Its Prosecution Laches Doctrine
- Perspectives on the PTAB’s 70% All Claims Invalidation Rate
- Moratorium on State AI Regulation Scrapped in Senate Version of Trump’s ‘Big Beautiful Bill’
- Increasing Volume of Patent Deals Could Signal Bounce in Patent Marketplace | IPWatchdog Unleashed