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International Competitive Landscape for Generative Artificial Intelligence Technology Based on Patent Metrics

  • Shuijing Hu,
  • Ying Li

摘要

This study delves into the competitive dynamics of the generative artificial intelligence technology sector by examining patent metrics. Patent data spanning from 2004 to 2023, pertinent to generative AI, were sourced from leading global patent repositories. We devised a patent valuation framework anchored in three facets: technological innovation, legal considerations, and market potential. Through juxtaposing patent submission volumes and patent caliber across diverse corporations and nations, we gauged the vigor of their R&D endeavors in the generative artificial intelligence domain. Initial findings suggest a fluid and swiftly transforming competitive milieu in the generative artificial intelligence technology sector. While established tech behemoths command a significant patent portfolio in this domain, nascent startups and academic entities are steadily carving a niche for themselves. Furthermore, the research underscores a marked uptick in patent submissions related to generative artificial intelligence technology in recent times, signaling a heightened momentum in R&D pursuits.