Abstract:Technological innovation serves as the core engine for reshaping the international competitive landscape and driving high-quality economic and social development. At its essence, innovation-driven growth is talent-driven, making the establishment of regional ecosystems for talent innovation and entrepreneurship a pivotal strategy for local governments to enhance their innovative competitiveness. This study first reviews and analyzes relevant domestic and international research and concepts, then develops a research framework based on prior findings, identifies case studies and data sources, and constructs a model for regional science and technology talent innovation ecosystems. Focusing on artificial intelligence in China and the United States—with particular attention to Hangzhou and Silicon Valley''s ecosystems—the study conducts comparative analyses across ecological element characteristics, factor synergy networks, and overall ecosystem performance. It further deciphers the innovative paradigms of the "Hangzhou Model" and "Silicon Valley Model," examining their shared strengths, core differences, and underlying causes. These insights provide actionable recommendations for building regional sci-tech talent innovation ecosystems in China, supporting the achievement of advanced technological self-reliance and strength.