Jensen Huang, CEO of Nvidia, advocates for re-industrializing technology manufacturing in the U.S., emphasizing its economic and societal benefits.
During a recent interview with CNN’s Fareed Zakaria, Jensen Huang, the CEO of Nvidia, expressed strong support for re-industrializing the United States’ technology manufacturing sector. Based out of Santa Clara, California, Nvidia is a dominant player in the artificial intelligence (AI) chip market. According to Huang, the country should focus on revitalizing its manufacturing sector, which he believes is currently underdeveloped.
Huang highlighted the value of manufacturing skills in contributing to both economic growth and societal stability. “That passion, the skill, the craft of making things; the ability to make things is valuable for economic growth — it’s value for a stable society with people who can create a wonderful life and a wonderful career without having to get a PhD in physics,” Huang explained.
In recent years, the U.S. government has implemented various measures to rejuvenate domestic manufacturing. These have included significant tariffs aimed at invigorating the nation’s declining manufacturing industries, particularly in the automotive and energy sectors, and enhancing technology investments. In April, White House press secretary Karoline Leavitt stated, “President Trump has made it clear America cannot rely on China to manufacture critical technologies such as semiconductors, chips, smartphones, and laptops” following a temporary tariff pause on certain electronics.
Huang emphasized the strategic significance of onshoring manufacturing, suggesting that it would alleviate pressure on Taiwan, home to the world’s largest semiconductor manufacturer, Taiwan Semiconductor Manufacturing Company (TSMC). In March, former President Trump announced that TSMC would invest a minimum of $100 billion in U.S.-based manufacturing.
Huang remarked, “Having a rich ecosystem of industries and manufacturing so that we could, on the one hand, make the United States better but also reduce our dependency — sole dependency — on other countries, is a smart move.”
The growing investment in AI, which has spurred a notable technology boom, has raised discussions about its impact on the labor market. A report from the World Economic Forum in January indicated that 41% of employers plan to downsize their workforce by 2030 due to AI-driven automation.
Nvidia, which briefly achieved a market value of $4 trillion, has developed technologies that support data centers essential for the AI models and cloud services of companies like Microsoft, Amazon, and Google. “Everybody’s jobs will be affected. Some jobs will be lost. Many jobs will be created and what I hope is that the productivity gains that we see in all the industries will lift society,” Huang noted.
Huang also discussed the company’s internal use of AI, emphasizing its importance: “Every software engineer and chip designer at Nvidia uses AI, and I encourage it to the point of mandating it.”
The discussion extended to the ethical concerns surrounding AI, particularly with generative response platforms such as Elon Musk’s Grok and OpenAI’s ChatGPT, which have encountered various controversies. Grok faced criticism after Musk’s xAI altered the chatbot, allowing it to produce more “politically incorrect” responses, including content deemed antisemitic.
xAI released a statement on Saturday attributing Grok’s behavior to outdated code susceptible to user input on X, including extremist content. The code has since been rectified. Huang commented on the incident, describing Grok as “younger” but praised Musk’s advancements within 18 months. “Of course there’s the fine tuning, there’s the guardrailing, and that just takes time to polish,” he stated.
Concerns also arise around AI’s potential for “hallucinations,” where the technology generates incorrect information. Despite these risks, Huang maintains that these fears stem from a lack of understanding of AI’s interconnected systems designed for safety. He asserted that global standards and practices are crucial for maintaining security.
“It will be overwhelmingly positive. Some harm will be done. The world has to jump on top of it when it happens, but it will be overwhelmingly, incredibly powerful,” he remarked.
Huang further explored the role of AI in healthcare, suggesting that AI models could revolutionize drug discovery by learning about proteins and chemicals. This process, more complex than language modeling due to the extensive data involved, could lead to breakthroughs in disease understanding and treatment.
“Not only will we accelerate the discovery of drugs, we’ll improve our understanding of disease. But over time, we’re going to have virtual assistant researchers and scientists to help us essentially cure all disease,” Huang predicted. “I think that day is coming.”
Moreover, real-world applications of AI are expanding. Current generative models, like Google’s Veo 3, can create videos and Huang anticipates the development of robots capable of physical tasks, a process involving vision-language-action models distinct from large-language models.
“The technology exists today. It works today,” Huang asserted, anticipating widespread technological adoption in “three to five years.”
This profound transition underscores Huang’s perspective on enhancing U.S. manufacturing and the transformative potential of AI across various industries, both of which are poised to redefine economic and societal frameworks.