Jensen Huang: AI Drives GDP and Profits, Demand for Computing Power in Taiwan Surges

NVIDIA CEO Jensen Huang highlighted the rise of Agentic AI at GTC Taipei, noting its transformative impact on productivity. He stated that AI tokens have become profitable revenue units, leading to a surge in demand for computing power in Taiwan and globally.
techNQ 55/100出典:PR Times

📋 Article Processing Timeline

  • 📰 Published: June 1, 2026 at 13:39
  • 🔍 Collected: June 1, 2026 at 13:54 (15 min after Published)
  • 🤖 AI Analyzed: June 1, 2026 at 13:57 (2 min after Collected)
Central News Agency, Taipei, June 1. NVIDIA CEO Jensen Huang delivered a keynote at GTC Taipei today, emphasizing the rise of Agentic AI and its transformative impact on productivity, computing models, and the AI ecosystem, as well as Taiwan's critical role. He stated that AI has become a driver of profits and GDP. Huang noted that as AI utility increases, tokens have become 'profitable units of revenue,' prompting AI companies to invest more resources, generate more tokens, and build more AI factories, leading to a surge in demand for computing power in Taiwan and globally. Huang pointed out that Agentic AI has matured and is delivering significant productivity gains. Citing the rapid growth of commits on GitHub, he explained how AI has increased software developer productivity by nearly three times, emphasizing that AI does not replace jobs but increases the demand for software engineers. Huang said Agentic AI is a new computing model consisting of LLMs, coordination frameworks, and memory systems that can understand intent, observe, reason, plan, and execute actions. He also mentioned NVIDIA's end-to-end AI system, Vera Rubin, describing it as a complete solution integrating GPUs, CPUs, storage, and DPUs. Huang concluded that NVIDIA has evolved from a GPU company to a system company and now an infrastructure provider, praising Taiwan's ecosystem.

FAQ

Why is Taiwan important for the AI industry?

It possesses the world's best supply chain and ecosystem, making it essential for building AI infrastructure like NVIDIA's.