Nvidia CEO Jensen Huang’s comments about the extraordinary demand for AI chips sent the company’s stock soaring nearly 8% in Wednesday’s trading session. Huang described the chip demand as “intense” and “so great” that it is “really emotional for people.”
Huang emphasized that AI is not just about a chip but an entire infrastructure. He highlighted the crucial role Nvidia plays in supporting numerous stakeholders in the evolving AI ecosystem.
The positive investor sentiment extended to Nvidia’s suppliers and other semiconductor-related firms in Asia. Contract chip manufacturer TSMC rose by as much as 5%, while Foxconn gained over 4%. Huang praised TSMC as “the world’s best,” attributing much of Nvidia’s success to the supplier.
Japanese semiconductor stocks also experienced a significant boost.
Nvidia’s surge amid AI demand
Semiconductor testing equipment supplier Advantest surged over 9%, while Tokyo Electron and Screen Holdings climbed 4.6% and 3%, respectively.
Technology conglomerate SoftBank, which holds a stake in chip designer Arm, jumped over 7%. In South Korea, Samsung Electronics and SK Hynix, the world’s two largest memory chip makers, soared by 2% and 7.5%, respectively. Huang reiterated that the rise of artificial intelligence encompasses more than just semiconductors.
He highlighted the significance of cloud service providers and developers in the evolving AI ecosystem. Huang expressed confidence in Nvidia’s ability to adapt amidst geopolitical uncertainties, stating, “In the event anything were to happen, we should be able to pick up and fab it somewhere else.”
Nvidia shares have skyrocketed 136% so far this year, buoyed by sustained investor enthusiasm. The rise in Nvidia’s stock underscores the heated competition among chip manufacturers as they vie for dominance in the burgeoning AI market.
Cameron is a highly regarded contributor in the rapidly evolving fields of artificial intelligence (AI) and machine learning. His articles delve into the theoretical underpinnings of AI, the practical applications of machine learning across industries, ethical considerations of autonomous systems, and the societal impacts of these disruptive technologies.
