The following does not belong TensorFlow2.0 Is characterized by?

Question

Options

• AMulti-core CPU accelerate
• Bdistributed
• Cmulti-language
• DMulti-platform

• A
  84% (49)
• B
  5% (3)
• C
  2% (1)
• D
  9% (5)

Explanation

Option A is the outlier because TensorFlow 2.0's defining hardware acceleration story centers on GPU and TPU support, not multi-core CPU parallelism. While TF2 can use CPU threads, "multi-core CPU acceleration" is not a promoted or distinguishing characteristic of the framework.

The distractors are all genuine TF2 features: Distributed (B) is core to TF2 via tf.distribute for scaling across machines and devices; Multi-language (C) is accurate since TF2 supports Python, JavaScript (TF.js), Java, C++, and more; Multi-platform (D) is true as TF2 runs on cloud, desktop, mobile (TFLite), and the web.

Memory tip: Think "TF2 = GPU/TPU power, not CPU cores." If a question mentions CPU-centric parallelism as a TF2 selling point, that's the wrong answer - TF2's acceleration pitch is always GPU/TPU first.

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