NVIDIA AIIO Pre-test

Why do GPUs offer a significant advantage over CPUs in accelerating AI workloads,

• GPUs are easier to cool, allowing them to run at maximum performance continuously

• GPUs have a higher clock speed than CPUs

• GPUs can process multiple data streams simultaneously, making them ideal for matrix operations in AI

• GPUs consume less power, making them more efficient for AI workloads

Which of the following factors has most significantly contributed to the recent rapid improvements and widespread adoption of AI?

• The invention of new AI programming languages

• The global standardization of AI ethics guidelines

• Increased computational power, especially with the advent of modern GPUs and specialized AI hardware

• The rise of social media, increasing the need for AI

Which of the following features of GPUs is most crucial for accelerating AI workloads, specifically in the context of deep learning?

• Large amount of onboard cache memory

• Lower power consumption compared to CPUs

• High clock speed

• Ability to execute parallel operations across thousands of cores

Which of the following best describes the primary benefit of using GPUs over CPUs for AI workloads?

• GPUs are designed to handle parallel processing tasks efficiently

• GPUs provide better accuracy in AI model predictions

• GPUs consume less power than CPUs for AI tasks

• GPUs have higher memory capacity than CPUs

You are comparing two regression models, Model X and Model Y, that predict stock prices. Model X has an R-squared (proportion of explained variance) of 0.75, while Model Y has an R-squared of 0.85.

Which model should you prefer based on the R-squared metric, and what does this metric indicate about the model's performance?

• Model X is better because a lower R-squared indicates more flexibility

• Neither model is better because R-squared is not a reliable metric

• Model Y is better because it has a higher R-squared value, indicating it explains more variance in the data

• Model X is better because it might generalize better despite a lower R-squared