Jamie Holcombe, chief information officer of the U.S. Patent and Trademark Office (USPTO), said machine learning helps USPTO speed up the process of assigning patent applications to examiners, FedScoop reported Wednesday.
The agency’s engineers who went to Google to learn more about TensorFlow application programming interfaces and machine learning are applying ML to patent search and classification processes using Python with TensorFlow.
“We immersed them in the culture, and they got Googly,” Holcombe said Wednesday during an ACT-IAC event. “They got certified in TensorFlow, which is the open-source library for a lot of neural network feedback loops.”
USPTO is tapping vendors to help perform patent classifications and compare them against the agency’s algorithms. Holcombe said allowing patent examiners to work with vendors allows the agency to further improve the algorithms.
