As the leader in GPU manufacturing, Nvidia has cemented its position as a ‘pick and shovel’ play in the AI chip gold rush. The company’s stock price has skyrocketed by 900% since the release of ChatGPT, with its GPU revenue experiencing an annual growth rate of 67% over the last three years. However, concerns have been raised about the demand for AI infrastructure driven mainly by Big Tech companies. We will examine the likelihood of this scenario and how it forms the foundation of the Nvidia bear thesis.
The Rise of AI Infrastructure Demand
To understand the potential for future GPU revenue, we need to delve into the underlying technology driving this revenue growth. For over half a century, the semiconductor industry’s growth was determined by Moore’s law. However, with the advent of advanced technologies and increasing computing power needs, Moore’s law is no longer relevant. The transistor count on microchips can now be increased at an exponential rate, far surpassing the two-year doubling requirement.
The driving force behind this accelerated growth is the ever-increasing need for greater computing power. This necessity was highlighted by Meta Platforms CEO Mark Zuckerberg when his company released the Llama 3 model in April 2024. The next version of the model, Llama 4, is set to launch early this year and will require a staggering 10 times more computation power than its predecessor.
Tech Companies’ Pursuit of Computing Power
The major tech companies in the US are investing heavily in increasing their computing capacity to cater to this growing demand. They recognize that developing advanced AI technology before their competitors can provide a significant advantage, making it a critical factor in their business strategies. Meta’s investment of $8.5 billion in the second quarter of last year is a testament to this, with spending 33% higher than the same period in the prior year.
This trend is likely to continue as tech companies strive to stay ahead of the competition. Nvidia, with its 90% market share in GPU manufacturing, will remain the primary provider of computing power for these companies. The need for increased capacity is not only driven by the requirement for more advanced AI technology but also by the fear of losing ground to competitors who invest heavily in this area.
Hedge Funds’ Confidence in Nvidia
Nvidia’s dominance in the AI chip market has been recognized by hedge funds, with 193 portfolios holding NVDA at the end of the third quarter. This represents a significant increase from the previous quarter, when 179 hedge fund portfolios held NVDA. While our research suggests that some AI stocks hold greater promise for delivering higher returns within a shorter timeframe, Nvidia remains an attractive investment opportunity.
The Cheapest AI Stock
For those looking for an AI stock with similar potential to Nvidia but trading at less than five times its earnings, we recommend checking out our report on the cheapest AI stock. This stock has shown significant growth in recent years and is poised to continue delivering high returns in the future.
Conclusion
Nvidia’s leadership in GPU manufacturing and its position as a key player in the AI chip market make it an attractive investment opportunity for those looking to capitalize on the growing demand for AI infrastructure. While concerns about the sustainability of this growth have been raised, our research suggests that the need for increased computing power will continue to drive demand for Nvidia’s products.
Further Reading
- $30 Trillion Opportunity: 15 Best Humanoid Robot Stocks to Buy According to Morgan Stanley
- Jim Cramer Says NVIDIA ‘Has Become A Wasteland’
Note: This article was originally published at Insider Monkey.
