AI0-001 AI Infrastructure and Technologies Practice Question
Which hardware accelerator is specifically designed by Google for training and inference of machine learning models, particularly their TensorFlow framework?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
TPU
TPU (Tensor Processing Unit) is Google's custom ASIC designed to accelerate ML workloads, especially with TensorFlow.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
NPU
Why it's wrong here
NPU stands for Neural Processing Unit, a broad category; not specific to Google.
- ✗
FPGA
Why it's wrong here
FPGAs are reconfigurable, not designed specifically by Google for ML.
- ✗
GPU
Why it's wrong here
GPUs are general-purpose accelerators, not Google-specific.
- ✓
TPU
Why this is correct
TPU is Google's custom chip for ML, optimized for TensorFlow.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.