Every AI model runs on specialized chips — primarily GPUs originally designed for video games. Understanding this layer helps you make sense of the industry's trajectory, bottlenecks, and economics.
Why GPUs? AI requires massive parallel computation — thousands of operations simultaneously. GPUs were built for exactly this. NVIDIA's CUDA platform became the standard for AI computation, which is why NVIDIA has become one of the most valuable companies on earth.
The supply bottleneck. Demand for AI chips has outstripped supply for the past two years. This bottleneck affects how quickly AI capabilities can scale and is a real constraint on the industry.
The competition heating up. NVIDIA dominates, but AMD is closing the gap, Google has its own TPU chips, Amazon has Trainium and Inferentia. More competition means faster innovation and eventually lower costs — which flows through to cheaper AI services for end users.
Why SMBs should care. You'll never buy an AI chip. But the chip supply chain directly affects the cost and availability of your AI services. When supply is constrained, prices stay elevated. As supply expands — which is happening now — prices drop and capabilities increase. The infrastructure buildout today is what makes AI affordable for your business tomorrow.