USPTO turns to artificial intelligence and machine learning for patent classification and trademark fraud

“Strategic modernization moves and the deliberate development of a robust teleworking infrastructure prior to the COVID-19 pandemic palpably paid off for the United States Patent and Trademark Office when the global health crisis hit, according to the agency’s Chief Information Officer Jamie Holcombe…”

“Presently, the agency is also embarking on six unique AI-centered programs, and the ‘greatest results’ they’ve seen so far relate to the classification of patents, the CIO said, noting that the team is ‘relearning the algorithms to do a supervised neural network feedback loop.’ In doing so, USPTO has gained ‘very precise classifications’ to use going forward in a dedicated effort to ‘drive the workflow to become quicker and better—more accurate and faster’, Holcombe noted. The agency is also turning to AI and machine learning tools to create a neural network in its trademarks’ fraud detection, with image search and classification…”

“Another priority within the agency is to offer the public ‘new valuable services’ that enable stakeholders the ability to seamlessly make use of—and draw new insights from—the agency’s vast amounts of data. Among other new initiatives, in May, USPTO launched Patents 4 Partnerships, a searchable repository for all applications available for licencing. Launched within 10 days, the hope is that the platform connects individuals and entities that have technologies they aim to license with those that can help commercialize the tech.”

“’That’s something that we’re trying to do in the future and get done more and more is provide more data services to the public,’ Holcombe explained…” Read the full article here.

Source: How USPTO Avoided the Strains of Pandemic-Forced Mass Telework – By Brandi Vincent, July 16, 2020. Nextgov.


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