Nvidia’s recent earnings report focused attention on the long-term viability of AI capital expenditures (CapEx), particularly in light of delays in the production of Nvidia’s highly anticipated Blackwell GPU. However, JPMorgan analyst Harlan Sur remains optimistic about Nvidia’s AI strategy, stating that even slight delays in Blackwell production will not deter cloud service providers from investing in AI and driving further research and development.
Sur emphasizes the strong demand for Blackwell, suggesting that supply could be outstripped at least until mid-2025. He cites Nvidia’s revenue guidance, which projects an 8% quarter-over-quarter increase, driven by continued customer spending on AI and accelerated computing initiatives. This positive outlook persists despite the Blackwell production delays, which Sur attributes to a two-month pushback, but considers a minor setback.
Nvidia’s Hopper GPU platform is proving to be a crucial driver of revenue, with the potential to generate several billion dollars in the coming quarters. This underscores the company’s commitment to staying ahead of the curve in the AI landscape.
Gokul Hariharan, co-head of Asia Pacific TMT Research at JPMorgan, reinforces the notion that Nvidia is still in the early stages of an accelerated computing and Gen AI investment cycle. He anticipates strong growth for customers next year, but acknowledges the market’s uncertainty, with some investors hesitant about the broader trajectory of AI adoption due to the competitive and rapidly evolving nature of the industry.
Despite these uncertainties, Nvidia’s pivotal role in driving the semiconductor sector forward is undeniable. Sur highlights that Nvidia’s growth serves as a bellwether for the entire industry, necessitating the development of various chip types, including compute, network, storage, and memory. This widespread demand benefits a wide range of semiconductor companies across the tech value chain.
Looking ahead, Nvidia’s ability to capitalize on its AI capabilities remains a primary focus. Sur highlights the potential for significant profits, revenue growth, and increased profitability as generative AI adoption accelerates. However, he cautions that the adoption phase is still in its early stages, presenting both opportunities and risks.
Ultimately, Nvidia faces a delicate balancing act between the promising future of AI and the practical challenges of scaling production and managing geopolitical risks. As Sur aptly concludes, the AI race is far from over, but Nvidia’s ability to create entirely new markets remains its strongest asset in this high-stakes game.
