AI Investing Glossary
What is a GPU and why do AI companies need them?
A GPU, graphics processing unit, is a chip architecture that performs thousands of calculations in parallel. Originally built for rendering graphics, that parallelism turned out to be ideal for training and running AI models, making GPUs the workhorse hardware of the AI buildout and the largest single line item in AI capital spending.
Why it matters for AI investors
GPU demand is the most direct expression of AI spending, but investing around it spans more than the famous designers: foundries fabricate the chips, memory makers supply the HBM beside them, and networking vendors connect them. The supply chain around the GPU is often where scarcity, and pricing power, actually sits.
Tracked stocks in this layer
The largest names in the Semiconductors category, ranked by market cap:
Market data as of the close on . Prices are end of day, not live.
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Frequently asked questions
Are GPUs the only chips used for AI?
No. Custom accelerators designed by cloud providers, application-specific chips, and specialized inference processors all run AI workloads, and their share is growing. GPUs remain dominant because of their software ecosystem and general-purpose flexibility, but the accelerator market is broader than one architecture and one vendor.
Related terms
See how this fits the whole picture in the Start Here guide, or browse the full glossary.