Question 1

What is the key difference between AI and traditional programming?

Options :

A : AI can solve problems without explicit programming

B : AI relies on deterministic algorithms

C : AI requires more computing power than traditional programming

D : AI is more accurate than traditional programming

Answer: A

Question 2

Which of the following best describes the importance of domain adaptation in sentiment analysis for specific business contexts?

Options :

A : Domain adaptation reduces the need for sentiment lexicons

B : Domain adaptation ensures models are more computationally efficient

C : Domain adaptation allows models to transfer knowledge from general to specific domains

D : Domain adaptation increases the number of sentiment categories

Answer: C

Question 3

Why is it important to use pre-trained models like GPT-3 or BERT in business applications involving complex text generation tasks, and how do they enhance performance?

Options :

A : Pre-trained models provide state-of-the-art performance by leveraging vast amounts of prior knowledge

B : Pre-trained models reduce the need for extensive hyperparameter tuning

C : Pre-trained models eliminate the need for labeled training data

D : Pre-trained models simplify the model architecture by reducing the number of layers needed

Answer: A

Question 4

Which of the following is a key ethical concern in artificial intelligence?

Options :

A : The high computational cost of training models.

B : Maximizing the accuracy of AI models.

C : Developing AI systems faster than competitors.

D : Ensuring that AI systems are interpretable and transparent.

Answer: D

Question 5

Which technique is most effective in reducing the computational cost of a CNN deployed in a business application without significantly compromising accuracy?

Options :

A : Increasing the depth of the CNN

B : Switching to a sigmoid activation function

C : Applying model pruning

D : Using a larger batch size during training

Answer: C

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