Jensen Huang, co-founder and CEO of Nvidia, a leading technology company in graphics processing units (GPUs) and artificial intelligence (AI), has become a central figure in the fast-paced development of AI technologies. With a career spanning decades and a personal fortune since 1999, Huang has voiced strong support for the rapid advancement of AI, often clashing with other wealthy tech leaders and scientists who advocate for more caution and regulation. In a recent interview with New York Times columnist Ezra Klein, Huang discussed his perspectives on AI’s role in education, its impact on global AI strategies, and the ethical debates surrounding its development. Huang noted that AI tools could help students work more efficiently but may also lower test scores by nearly 20%, particularly in basic math skills like multiplication tables and square roots. He argued that such skills might become less important as students transition into the workforce, where other competencies may be more valuable. However, he shared a personal anecdote about not knowing his own home address, which he found alarming when he needed it for a credit card verification. This highlighted his concern about the potential loss of certain practical skills in a world increasingly reliant on AI. In discussing China’s AI development, Huang praised its ability to produce a large number of scientists, mathematicians, and engineers through its educational system. He likened China's approach to "manufacturing smart kids in volume," expressing admiration for its use of open-model communities and its commitment to building an AI-driven future. Huang did not criticize China’s strategy, instead showing respect for its progress and ambition in the field. Huang criticized what he called "alarmism" and "doomerism" from some of his U.S. counterparts, including Geoffrey Hinton, a Nobel Prize-winning scientist who warned of a 10% chance that AI could end human civilization. Huang dismissed Hinton’s warning as "irresponsible," arguing that the source of the statement does not automatically make it scientifically valid. On the topic of energy consumption, Huang acknowledged that AI supercomputers are "super energy efficient" but still use a significant amount of power. He called for transparency in energy use and encouraged the development of sustainable energy sources, though he admitted that fossil fuels may be necessary in the near term due to current limitations in energy production. Huang emphasized the need for patience and perseverance in building a sustainable future with AI, comparing its development to surgery, where initial discomfort is necessary for long-term benefits. He stressed that AI systems should not be released if they act out of alignment with human values, but he did not provide specific details on the measures or concerns related to current AI testing and deployment practices. His comments reflect a broader debate about the balance between innovation and responsibility in the AI era.