For most people, the experience of artificial intelligence begins and ends with daily interactions—using ChatGPT to create a fitness plan, asking Claude to help write application code, or having Alphabet’s Google Gemini turn a spreadsheet into a chart. However, behind these convenient tools lies a complex ecosystem of hardware and cloud infrastructure that ensures the stable operation of AI tools. As companies continue to invest in AI development, firms engaged in building AI infrastructure are seeing growing demand, making them noteworthy investment targets.
Nvidia maintains its lead in the AI processor market with its GPU hardware and CUDA software ecosystem; TSMC, as the world’s most critical chip manufacturer, holds an irreplaceable position in manufacturing capability; Amazon, relying on its AWS cloud platform and Bedrock development tools, occupies a core position in the cloud infrastructure sector.
Nvidia has made significant contributions to the explosive development of AI tools over the past few years. Although the company has not launched generative AI applications or large language models, its hardware provides the computational “brain” power for training and deploying many mainstream AI models. Nvidia’s graphics processing units (GPUs) were originally designed to enhance video game graphics, but their parallel processing capabilities also make them well-suited for rapidly handling complex AI workloads.
Over the past several years, Nvidia has achieved a near-monopoly in the data center AI chip market, a position clearly reflected in its financial results. With this near-monopoly on general-purpose AI processors, Nvidia has been able to charge premium prices, thereby boosting its profit margins and profitability. In its most recently reported quarter ending January 25, Nvidia’s net profit increased 94% year-over-year to $43 billion; over the past three years, this metric has grown by a cumulative 594%.
While companies like Nvidia design the AI chips needed for data centers, TSMC is responsible for actually manufacturing most of these products. As the world’s leading chip manufacturer, TSMC plays a critical role in the AI ecosystem. Chip manufacturing is a costly and highly specialized task that few companies can perform. Currently, no competitor can match TSMC’s manufacturing capabilities, which is why so many well-known tech companies rely on it to produce their high-end chip designs.
With hundreds of billions of dollars expected to be invested in data centers and other AI infrastructure (such as cooling systems) over the next year alone, TSMC will be a major beneficiary. In its recent earnings call, TSMC stated that it expects long-term demand for its AI accelerators to grow at a compound annual rate of around 55%. Without TSMC’s manufacturing prowess, the quality of AI chips would suffer, which in turn would reduce the reliability of AI tools.
Amazon’s role in the AI space is built on its cloud platform, AWS. AWS is the world’s largest cloud infrastructure provider, offering the necessary computing power for developing and deploying AI software. Without such platforms, only a handful of large technology companies would have the resources to venture into the AI field.
Amazon’s Bedrock is evolving into an integrated AI development platform that allows users to access different AI models, customize their own models, and deploy applications. As OpenAI’s exclusive partnership with Microsoft comes to an end, AWS has been able to incorporate ChatGPT, one of the most widely used models on the market, into its service offerings.
Amazon plans to invest $200 billion this year in building data centers and improving AI infrastructure. As these projects gradually come online, the company is expected to take on more customers and reduce its backlog of orders, thereby beginning to see higher returns on its AI investments.
