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Using AI to Reduce Transactional Costs of Patent Validity and Infringement Determinations

Using AI to Reduce Transactional Costs of Patent Validity and Infringement Determinations

Gau Bodepudi and Eesha Kumar of IP EDGE write about initative to incorporate AI methods by Carnegie Mellon from their Patent Examination Initiative.

For example, Carnegie Mellon’s Center for AI and Patent Analysis is developing AI algorithms that combine the capabilities of AI, machine learning, and natural language processing (NLP) to examine patent applications. The Center’s Patent Examination Initiative is directed to enabling patent examiners to “deliver high quality and timely examination,” by “deliver[ing] the most pertinent information and analysis for robust examination.”

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