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.
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Recent Posts
- StarrAI Night: AI Art and the Necessary Changes in the Copyright Law
- Other Barks & Bites for Friday, February 3: Trump Sues for Copyright Infringement, Google Wins Transfer from TX to CA, and Nike Takes Lululemon to Court for Patent Infringement
- Revolution Rope Inventor Tells Justices She Deserves Her Day in Article III Court
- The USPTO Claims it Wants to Ensure ‘Robust and Reliable’ Patents – But Its Questions Imply Another Assault on Patent Owners
- USPTO Issues Final Rule to Eliminate CLE Certification Program