AI Chips are divided into business applications and can be divided into?

Question

Options

• Atraining
• BGPU
• CModel building
• Dreasoning

• A
  78% (35)
• B
  16% (7)
• C
  7% (3)

Explanation

AI chips, when divided by business application, fall into two distinct use-case categories: training and reasoning (inference). Training chips are optimized for the computationally intensive process of building AI models from data, while reasoning chips (also called inference chips) are optimized for deploying those trained models to generate outputs and make decisions in real-world applications.

Option B (GPU) is incorrect because GPU refers to a type of hardware architecture, not a business application category. GPUs can be used in both training and inference, so it does not define a functional use-case split. Option C (Model building) is incorrect because it describes the same activity as training and is not a separate business application category on its own.

Memory tip: Think of the AI product lifecycle in two stages - "build it" (training) and "use it" (reasoning). Chips are designed and sold to serve one of these two business purposes, which is the core distinction the question is testing.

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