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Nvidia's Chips Riding High as Big Tech's AI Spending Spree Continues

On Monday, analyst Reitzes reiterated his Buy rating on Nvidia (NVDA) shares, bumping up his target for the stock price to $1,125, from $1,000. 

Reitzes' stance emphasizes the substantial and expanding capital expenditure budgets at tech giants like Tesla (TSLA), Microsoft (MSFT), Meta Platforms (META), (AMZN), and Alphabet (GOOG), which bode well for suppliers of AI infrastructure.

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"There's a gold rush," Reitzes wrote. "The big clouds are the foundation of demand for Nvidia’s GPUs, and they are all spending ~20% more on chips than we thought over the next few years."

According to Reitzes, cloud providers are aggressively pursuing the development of artificial general intelligence, which refers to sentient software capable of performing tasks beyond human capability. To fuel this ambition, he noted their substantial spending with hopes of commensurate monetization in the future.

The rationale behind this expenditure is clear, as Reitzes elaborated: "Microsoft needs the best AI for tools like Copilot. Google also needs to get AI right for Search or risk everything…Meta also needs the best AI tools for ads – and to create the best AI assistants/tools for its users – so it can monetize them. Amazon needs to invest like Microsoft to not only reinvent their cloud but also catalyze its retail and ads businesses."

Reitzes adjusted his revenue and profit forecasts for Nvidia for the current fiscal year, 2025, as well as for 2026 and 2027.

The AI Arms Race: What It Means for Nvidia and Investors
The demand for artificial intelligence (AI) applications is reaching new heights, driven by the technology needs of four major tech companies. Tesla, Meta Platforms, Microsoft, and Alphabet have all reported robust demand for AI, spelling good news for Nvidia, a key supplier of GPUs for training large language models powering next-gen AI applications.

Tesla, for instance, plans to increase its utilization of Nvidia chips by a whopping 140%. The company's forthcoming robotaxi, dependent on Tesla's full self-driving (FSD) capabilities, demands intensive AI training. Elon Musk, Tesla's CEO, disclosed that the company doubled its training compute power in the first quarter alone. Furthermore, Tesla's cluster of 35,000 Nvidia H100 GPUs is expected to swell to approximately 85,000 by year-end, solely for AI training purposes.

Similarly, Meta Platforms is ramping up its spending on AI infrastructure to bolster its AI capabilities, aiming to become a leader in the field. CEO Mark Zuckerberg envisions Meta as the foremost AI company globally and is allocating significant capital to achieve that goal. As part of its strategy, Meta is increasing its expenditure on Nvidia chips while simultaneously developing custom silicon for AI training.

Microsoft, a frontrunner in providing cloud services for AI applications, is also witnessing a surge in demand outpacing available capacity. To address this, Microsoft plans to ramp up spending in fiscal 2024 and 2025 to meet growing demand. The company is investing in both adding capacity and developing its own AI models using OpenAI's GPT architecture.

Alphabet, Google's parent company, is another major player significantly investing in AI infrastructure. In the first quarter alone, Alphabet allocated $12 billion to capital expenditures, nearly double the amount from the previous year. These investments primarily focus on expanding Google Cloud and enhancing AI capabilities, including integrating AI into search functionalities.

Implications for Nvidia and Investors
The implications for Nvidia are profound. Amidst the AI arms race, demand for AI compute continues to outstrip supply, driving up Nvidia's pricing power. With its gross margin soaring from 56.9% to 72.7% between fiscal 2023 and fiscal 2024, Nvidia stands to benefit significantly from the heightened demand for AI infrastructure. Despite the strong momentum, however, Nvidia faces challenges as tech giants increasingly develop and deploy proprietary chip designs for AI workloads, potentially eroding Nvidia's market share.

While Nvidia's position atop the AI hierarchy remains formidable, its vulnerability to competition underscores the need for sustained innovation and adaptability. As Nvidia navigates the evolving landscape of AI, investors anticipate continued growth, albeit against a backdrop of intensifying competition and technological disruption.

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