By Jurica Dujmovic
As the artificial-intelligence boom accelerates, data-center providers are positioned to reap substantial rewards
Nvidia's (NVDA) partnerships with other tech giants including Amazon.com's (AMZN) AWS, Alphabet's (GOOGL) (GOOG) Google Cloud, Microsoft (MSFT) Azure and Tesla (TSLA) have been instrumental in deploying its cutting-edge AI systems globally.
These collaborations, exemplified by projects like AWS's Ceiba and the integration of Nvidia's H100 GPUs across cloud platforms, have pushed the boundaries of AI capabilities. Yet they also highlight a critical dependency: the need for robust, scalable infrastructure to support AI advancements.
Data-center demand
That makes a lot of sense. As Nvidia's AI chips and systems become more powerful and ubiquitous, the computational demands on data centers and networking infrastructure necessary for their use grow exponentially. Tesla's plan to deploy 85,000 Nvidia H100 GPUs by the end of 2024 is just one example.
Read: Nvidia will look to accomplish this earnings triple play
This AI infrastructure primarily consists of hyperscale data centers - massive, highly sophisticated facilities designed to support the enormous computational needs of AI and other data-intensive technologies. Unlike traditional data centers, hyperscale facilities are built to accommodate tens of thousands of servers and can rapidly scale to meet increasing demand.
These facilities are not just larger versions of traditional data centers; they represent a fundamental shift in data-center architecture and management. They are designed to be modular and scalable, enabling rapid expansion as demand grows. This flexibility is crucial for supporting the unpredictable and often explosive growth of AI workloads.
Hyperscale data centers are strategically located to optimize for factors like energy costs, network latency and natural-disaster risk. They often form the backbone of cloud computing services, providing the raw computational power needed for AI training and inference at scale.
The exponential growth in AI capabilities is directly translating into increased demand for hyperscale facilities. As AI models become more complex and data-intensive, the need for larger, more efficient and more powerful data centers grows correspondingly. This symbiotic relationship between AI advancement and data-center evolution is creating a robust ecosystem that extends far beyond chip makers.
Hyperscale data centers' hypergrowth
Due to systemic changes in supply and demand, the hyperscale-data-center market is on a trajectory of explosive growth, with projections indicating it will grow to $262.09 billion by 2032 from $44.89 billion in 2024 . This represents a compound annual growth rate, or CAGR, of 24.7%, underscoring the sector's immense potential. As the AI boom accelerates, infrastructure providers are positioned to reap substantial rewards.
This shift presents a nuanced opportunity for investors. While Nvidia continues to innovate and grow, the companies that facilitate the deployment and scaling of Nvidia's technologies may offer equally compelling, if not superior, investment prospects.
Ranging from global leaders in digital infrastructure to specialized data-center operators and IT solutions providers, they may not grab headlines like AI chip manufacturers, but these companies are building and maintaining the critical infrastructure that powers AI advancements. From operating vast networks of data centers to providing cutting-edge networking solutions, these businesses are positioning themselves to benefit from the growing demand for robust, scalable AI infrastructure.
Put simply, these companies are supplying the picks and shovels of the AI gold rush. Here are five examples:
1. Equinix: A global leader in digital infrastructure, Equinix (EQIX) operates 260 data centers in 71 major metropolitan areas across the Americas, Asia-Pacific and EMEA (Europe, Middle East, and Africa) regions?.
2. Digital Realty Trust: Digital Realty (DLR) owns and operates more than 300 data centers across six continents. The company provides scalable and optimized network architectures essential for AI and other demanding applications?.
3. Hewlett Packard Enterprise: HPE (HPE) provides comprehensive data-center infrastructure solutions, including servers, storage and networking systems.
4. CoreSite Realty Corp.: CoreSite, a unit of American Tower REIT (AMT), offers secure, high-performance data-center solutions across key North American markets. It supports a wide range of enterprises and cloud providers with its strategically located facilities?.
5. NTT Ltd.: A part of Nippon Telegraph and Telephone Corp. (NTTYY), NTT operates more than 160 data centers across 20 countries. It provides state-of-the-art data-center solutions and services, supporting businesses with advanced digital infrastructure?.
Companies like these are integral to the seamless operation of AI technologies, enabling rapid data processing and storage - essential for AI development.
Furthermore, the strategic placement and sophisticated design of these data centers ensure they can handle increasing AI demands. They're positioned as crucial enablers in the tech ecosystem, offering long-term growth potential. As AI technologies advance, the reliance on robust, scalable infrastructure will only deepen.
In the high-stakes game of AI advancement, these infrastructure providers aren't merely moving pieces - they're architecting the entire playing field.
So, here's the question: When the AI revolution crowns its champions, will your portfolio showcase the flashy players making headlines, or the master craftsmen building the foundation under them?
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-Jurica Dujmovic
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08-31-24 1426ET
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