Post-Midterm Review Direction in Focus
U.S. midterm election results are shaping tech industry policy, while NVIDIA founder Jensen Huang's departure has drawn global attention. Wan Hai Chairman Po-Ting Chen said today (13th) that the incident itself may have little direct impact on the AI industry, but the subsequent strength of U.S. scrutiny of the tech sector and the stance of newly elected Democratic governors are worth watching. He believes the structure of the global shipping industry has changed since the pandemic, with the shipping market moving toward orderly competition.
International Competition Returns to National Interests
Chen believes international AI competition has always existed, and countries will ultimately return to national interest considerations. This incident merely brought some competitive relationships to the surface, and countries or relevant parties may use it to increase their own bargaining leverage. As for whether national security needs will further affect the global trade order, he said it will be necessary to watch subsequent U.S. policy and review direction. Compared with individual incidents, the subsequent impact of the U.S. midterm results on the tech industry deserves more attention.
Taiwan Supply Chain May Be Indirectly Affected
Chen observed that Taiwan's tech industry focuses on hardware manufacturing, or "selling shovels," with an industry structure different from AI software and platform operators, so it may not immediately feel a clear impact in the short term, but subsequent U.S. reviews may take different directions and could still have some impact on Taiwan's supply chain. He stressed that both the benefits and drawbacks of AI should be fully evaluated. AI can improve efficiency and accelerate computing, but data center expansion also brings electricity, water and land demand, with related environmental costs gradually emerging.
Calls for Smart AI Use for the Good of the Earth
Chen appealed "for the good of the Earth," saying AI should not only pursue a computing-power race but should focus on smart use of AI. He gave as an example that when users make requests, they should first clearly state the content type and purpose, such as needing a narrative, story-driven, emotional or historical article, so AI can grasp the need and avoid repeated generation and revision that wastes time and computing resources. He advocated sorting and diverting requests at the application entry point to reduce ineffective computing, and directing AI resources toward applications with substantive benefits such as medicine and basic medicine, DNA research, energy management, office and building air-conditioning configuration, precision transportation and retail replenishment, while entertainment-oriented AI use can be moderately reduced.