56. Which of the following is true about the size of GPT models?
A) They are relatively small and can be trained on a single GPU
B) They are typically larger than other models and require specialized hardware for training
C) They are the same size as other models and do not require specialized hardware
D) Their size varies depending on the specific application they are being used for
57. Which of the following is a potential benefit of GPT models for businesses?
A) They can generate large amounts of text data for free
B) They can automate many tasks that would otherwise require human labor
C) They can reduce the amount of training data required for machine learning models
D) They do not require any specialized hardware to run
58. Which of the following is true about the training process of GPT models?
A) It involves training the model on a specific task
B) It involves fine-tuning the model on a large corpus of text data
C) It involves evaluating the performance of the model on a validation set
D) It involves generating new text based on specific prompts
59. Which of the following is an example of a limitation of GPT models for natural language processing tasks?
A) They require large amounts of training data
B) They cannot generate text in multiple languages
C) They have a limited understanding of complex sentence structures
D) They are highly interpretable and their outputs can be easily verified
60. What is the primary disadvantage of GPT models over traditional rule-based approaches for natural language processing tasks?
A) They require specialized hardware to run
B) They have a limited vocabulary
C) They are not as accurate as rule-based approaches
D) They are less interpretable and their outputs cannot be easily verified
