Nvidia’s Robust Growth: Riding The AI Wave
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Summary:
- Nvidia Corporation has experienced a 70% increase in value YTD, driven by AI advancements and its unique approach to sustainability and workload acceleration.
- The widespread adoption of generative AI and digitalization supports our bullish thesis on Nvidia’s robust and visible growth prospects.
- Despite elevated valuations, maintaining a long position in Nvidia could prove fruitful as AI gains prominence and investors establish positions in the company, although competition risks should not be overlooked.
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At the beginning of the year, we published an optimistic piece suggesting that ChatGPT would serve as a driving force for Nvidia Corporation (NASDAQ:NVDA) expansion. We are delighted to report that, in line with our predictions, NVDA stock has seen roughly a 50% increase in value since then. In response to numerous recent developments and a substantial shift in the stock’s valuation, many readers have asked for an update. We are eager to deliver this update in the present article, as well as a comprehensive account of Nvidia’s distinct story, which bolsters our bullish stance that Nvidia possesses one of the most robust and visible growth outlooks of any company we have encountered.
NVIDIA’s Unique Advantage
For the first time in history, general-purpose computing (CPUs) can no longer provide the necessary throughput without a corresponding increase in cost or power. In our view, this inability to reduce power consumption or cost-effectively presents a significant challenge for the world to sustain increasing workloads while maintaining the sustainability of computing.
Sustainability has emerged as one of the most critical factors in computing today. It is essential to accelerate all possible workloads to reclaim power and invest it back into growth. The first step is to minimize power wastage and accelerate as many tasks as possible while prioritizing sustainability. Examples of workloads demonstrate that, in many cases, applications can be accelerated by from 40x to 100x while simultaneously reducing power consumption by an order of magnitude and decreasing costs by a factor of 20.
However, implementing this approach is not simple. Accelerated computing presents a full-stack challenge, and Nvidia’s accelerated computing encompasses the entire stack, from architecture and system to system software, acceleration libraries, and the applications on top. We believe that Nvidia’s data center-scale computing architecture is uniquely positioned to address this challenge.
One of the key benefits of accelerated computing is its ability to scale up and out, providing million-x acceleration factors to various application domains, including the crucial area of artificial intelligence. Nvidia’s accelerated computing platform is multidomain, enabling it to process multiple types of applications, from particle physics and fluid dynamics to robotics, artificial intelligence (“AI”), computer graphics, image processing, and video processing. By accelerating all these domains, NVIDIA can reduce power consumption and costs significantly.
The openness, reach, and acceleration capabilities of NVIDIA’s platform have created a virtuous cycle of accelerated computing, marking the arrival of accelerated computing and artificial intelligence. Based on our research, we believe that NVIDIA’s comprehensive approach to tackling the challenges of sustainability and workload acceleration places it among the companies with the strongest and most visible growth prospects in the industry.
Dawn of Artificial Intelligence
Over the past decade, foundational work has led to significant breakthroughs in computer vision and perception, resulting in industrial revolutions within autonomous vehicles, robotics, and similar fields. This was just the tip of the iceberg. The emergence of generative AI has propelled artificial intelligence beyond mere perception and into the realm of information generation. This new capability allows AI to not only understand the world but also make recommendations and create valuable content. We believe that generative AI has initiated an inflection point in artificial intelligence, driving its widespread adoption globally and causing a step-function increase in the volume of inference deployed across the world’s clouds and data centers.
We believe that a key driver of the demand for Nvidia platforms is generative AI. The Hopper launch, featuring a transformer engine specifically designed for large language models and foundation models, generated considerable excitement. The transformer engine has proven immensely successful, with Hopper being adopted by nearly every cloud service provider and available through OEMs. The surge in Hopper demand compared to previous generations signifies an inflection point for AI, as it transitions from research to deployment across global industries. Importantly, this shift also represents a considerable step-function increase in the inference of AI models.
Generative AI has caused a step-function increase in the volume of inference workloads. This development is crucial as inference workloads emerging from data centers demand acceleration and multimodal capabilities, handling a variety of workload types. For instance, AI may need to apply inference to video, images, or text, each with their distinct characteristics. In a cloud data center, we believe it would be ideal to have specialized accelerators for each modality or diverse generative AI workload, which should drive demand for Nvidia’s semiconductors.
Based on our research, we believe that the developments in generative AI and digitalization, along with the successful adoption of Hopper, support our bullish thesis that Nvidia holds one of the strongest and most visible growth prospects in the market.
Financials & Valuation
Nvidia’s financial performance in fiscal year 23 (ending January) reveals a significant slowdown in the company’s growth rate. The challenging comparisons in video games and data centers from previous years, coupled with the decline of the cryptocurrency market, have caused sales for FY23 to increase by a mere 0.1%, in stark contrast to the 61.4% increase experienced in the previous year. The main culprit behind this stagnation is a projected 30% year-over-year decline in the gaming segment, which has been the most affected by cryptocurrency.
Nvidia’s operating margins have contracted, as the company’s operating expenses increased at a faster pace than its revenue growth. This has resulted in a 14% decrease in operating margins to 33.3% in FY23, which in turn has led to a projected 26% drop in earnings per share for the same period.
Due to a slowing economic climate and uncertainty surrounding end market demand, consensus projections for FY24 remain cautious. Sales growth is estimated to be 10.8%, revised upwards from the 8.3% consensus estimate when we wrote our January Nvidia article, and earnings per share are expected to recover to $4.49, revised upwards from $4.39 in January. However, this is still only about the same as the FY22 EPS of $4.44, despite massive demand coming from AI. We believe there is potential for Nvidia to surpass these upwardly revised but still conservative estimates, given the escalating competition among tech giants in the field of AI and the reliance on Nvidia’s GPUs for processing AI workloads.
In January 2023, Nvidia experienced a significant rally of 43%, and skepticism surrounded the sustainability of its valuation. However, Nvidia is now up 92% year-to-date, with market recognition of the opportunity presented by ChatGPT and the broader shift towards riskier assets likely playing a major role. During the same period, Tesla, Inc. (TSLA) experienced a rally of 78% and Bitcoin (BTC-USD) saw a rally of 70%. We believe that a large portion of NVIDIA’s rally is driven by the repricing of risk assets due to moderating interest rate hike concerns, and that NVIDIA’s excess return relative to these risk assets has been modest. In our view, NVIDIA’s fundamental growth prospects have significantly improved, while those of other risk assets have not.
Based on our analysis, Nvidia is currently trading at 58 times its forward 12-month earnings per share (EPS). This valuation is towards the upper end of its 10-year range, with an all-time high of 65.5 times reached in November 2021 during the peak of the tech bubble. In comparison, when we pitched the stock in January, it was trading at a more attractive 45.5 times forward EPS, which made the investment case much clearer than it is today.
Despite the elevated valuation, we will maintain our long position in Nvidia without adding to it at these levels. We believe that many investors are underexposed to Nvidia and, by extension, underexposed to the greatest technological trend of the century – artificial intelligence (AI). As AI continues to gain prominence, we expect these investors will be compelled to establish positions in Nvidia, which in turn should drive demand for the stock, especially as earnings estimates are revised higher, which would reduce the earnings multiple.
Risks
While we maintain a positive outlook on Nvidia’s prospects as a major player in the AI space, we acknowledge that investing always carries some degree of risk.
One concern we have is the potential for increased competition as AI becomes more critical and Nvidia’s profits continue to grow. Specifically, we are apprehensive about competition from China, a country with vast technical resources, a significant semiconductor market, and a political motivation to establish a domestic supply in response to US government technology restrictions.
For instance, Chinese GPU developer Moore Threads has recently raised $215.4 million in Series B funding to support its ongoing research and development of multi-functional GPUs. This funding signifies investors’ confidence in the potential of Chinese GPU development, fueled by the country’s demand for AI/ML accelerators and graphics processors for gaming. Since its inception in late 2020, Moore Threads has launched two graphics processors compatible with its MUSA computing platform: Sudi and Chunxiao, along with multiple add-in-boards built around that base design. These multi-functional GPUs target various industries, including gaming, cloud computing, AI/ML, FP32 high-performance computing, and virtual desktop infrastructure, allowing Moore Threads to attract investors from diverse backgrounds.
Another potential source of competition is the development of AI chips by tech giants themselves. Google, for example, has announced a processor specifically designed for enhanced imaging and machine learning capabilities. The company has highlighted the chip’s ability to efficiently perform tasks such as real-time language translation for captions, offline text-to-speech, image processing, and other machine learning-based functions like live translation and captions. This development suggests that tech giants may increasingly opt to create their own AI solutions, potentially encroaching on Nvidia’s market share.
Conclusion
Despite Nvidia Corporation’s elevated valuation, we will maintain our long position without adding to it at these levels. We believe that many investors are underexposed to Nvidia and, consequently, the greatest technological trend of the century – artificial intelligence. As AI gains prominence, we expect investors to establish positions in Nvidia, driving demand for the stock and potentially reducing the earnings multiple as estimates are revised higher. However, we must also consider the risks of increased competition from countries like China and tech giants developing their own AI chips, which could pose challenges for Nvidia’s market share.
Analyst’s Disclosure: I/we have a beneficial long position in the shares of NVDA either through stock ownership, options, or other derivatives. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
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