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USPTO leverages data analytics, AI, and machine learning to increase efficiency and performance

The changes would enhance operations of USPTO and improve the quality of systems and processes.

The United States Patent and Trademark Office (USPTO) is leveraging data analytics and technologies such as AI and machine learning (ML) to increase its performance and improve the quality of systems and processes.

The agency relies on input from hundreds of experienced workers to supplement the technology, captured actively and passively, to train and refine AI-driven models to ensure the technology delivers the expected outcomes. 

The agency has awarded more than 11 million patents since its founding. It employs more than 12,000 people, including attorneys, engineers, analysts, and computer specialists. A constant flow of feedback from its patent examiners on the front lines is also used to improve AI/ML models to fuel the development of new products and support activities in two key areas: patent search and classification.

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Performing a comprehensive patent search is challenging given the explosion in the volume of data and possible sources of the prior art. To meet the challenges, technology teams are rolling out an artificial intelligence component in a new patent search tool to assist examiners in finding the most relevant sources they need as they scrutinize applications. 

This is important because each of the over 600,000 applications received yearly by the USPTO contains approximately 20 pages of figures and text, or roughly 10,000 words describing the claimed innovations. The agency’s IT organization also developed a classification tool that matches the classification symbols identified with an invention from more than 250,000 possible categories.

In both instances, the models were developed and are continually enhanced through input from human experts who facilitate a human touch to determine whether something is genuinely new and then apply law, facts, and expertise to reach a decision.

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Sahil Pawar
Sahil Pawar
I am a graduate with a bachelor's degree in statistics, mathematics, and physics. I have been working as a content writer for almost 3 years and have written for a plethora of domains. Besides, I have a vested interest in fashion and music.


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