Practice Integration Of Ai Models With Hardware (10.4.2) - Advanced Topics and Emerging Trends in AI Circuit Design

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8 questions

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Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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2 questions · about 1 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is model pruning?
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Think about simplifying the model for efficiency.
Question 2.
Name one benefit of model compression.
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Consider the size of the model.
3Question 3.
What is the main purpose of model pruning?
- To reduce model complexity
- To increase training time
- To improve data collection
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Think about what pruning does to a plant.
4Question 4.
True or false: Quantization can lead to increased precision in model weights.
- True
- False
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Consider what quantization does.
Question 5.
Evaluate the effects of model compression on real-time data processing in an autonomous vehicle.
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Link speed with efficient computation.
Question 6.
Formulate a strategy for deploying quantized models in a smart home device without losing too much accuracy.
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Consider which parts of the model can afford less precision.

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