GPU

GPU refers to graphics processing units, the chip category TPU? GPU? What’s the difference between these two chips used for AI? describes as central to the AI boom. In the Marketplace Tech episode, Christopher Miller contrasts Nvidia GPUs with Google [[TPU|TPUs]]: GPUs remain more general-purpose and broadly useful, while TPUs are more specialized for certain AI workloads.

The wiki already discusses GPUs indirectly through Nvidia, MaaS Infrastructure, AI Compute Continuity, High Bandwidth Memory, and Data Center Thermal Management. This page makes the accelerator category explicit so future AI infrastructure sources can distinguish general-purpose accelerator flexibility from workload-specific chip design.

Connections

• Nvidia - dominant GPU supplier in the episode’s AI market frame.
• TPU - Google specialized-chip comparison.
• AI Chip Specialization - broader tradeoff between flexibility and efficiency.
• MaaS Infrastructure, AI Inference Cost Structure, and AI Compute Continuity - serving and reliability contexts where GPU availability matters.
• AI Hardware Supply Chain Pressure and High Bandwidth Memory - adjacent component pressure from GPU-heavy AI systems.