126. What is the difference between GPT and BERT?
a) GPT is designed for text generation, while BERT is designed for text classification.
b) GPT is a Transformer-based architecture, while BERT is an RNN-based architecture.
c) GPT is trained on unsupervised learning tasks, while BERT is trained on supervised learning tasks.
d) GPT is designed for language modeling, while BERT is designed for bidirectional encoding of text.
127. Which of the following is a limitation of GPT models?
a) They require a lot of computing power to train.
b) They are not able to generate text that is coherent and understandable.
c) They are limited to a specific language or domain.
d) They are not able to learn from feedback or corrections.
128. Which of the following is NOT an application of GPT models?
a) Chatbots
b) Text classification
c) Image recognition
d) Language translation
129. Which of the following is a potential ethical concern associated with using GPT models?
a) GPT models may perpetuate bias or discrimination.
b) GPT models may replace human jobs.
c) GPT models may be used to spread misinformation or propaganda.
d) All of the above.
130. What is the difference between GPT-2 and GPT-3?
a) GPT-3 has a larger number of parameters than GPT-2.
b) GPT-2 is better at generating coherent and grammatically correct text than GPT-3.
c) GPT-3 is designed for text classification, while GPT-2 is designed for text generation.
d) There is no difference between GPT-2 and GPT-3.
