A. Doubling the neural network layers
B. Adjusting the model parameters to improve accuracy
C. Upgrading the hardware of the AI clusters
D. Encrypting the data for security reasons
A. Classify documents into different types
B. Extract text from documents
C. Extract tables from documents
D. Generate transcript from documents
A. Prompt Engineering modifies training data, while Fine-tuning alters the model's structure.
B. Both involve retraining the model, but Prompt Engineering does it more often.
C. Prompt Engineering adjusts the model's parameters, while Fine-tuning crafts input prompts.
D. Prompt Engineering creates input prompts, while Fine-tuning retrains the model on specific data.
A. Text summarization
B. Audio recording
C. Speech recognition
D. Text to speech
