You are working on a project that involves developing a named entity recognition (NER) system using spaCy. The system must accurately identify and categorize entities in a large corpus of unstructured text data. Additionally, the data processing pipeline must be optimized for performance and scalability. Which two actions would best enhance the performance and accuracy of the NER system in this scenario? (Select two)
You are deploying a generative AI model on an edge device with limited computational resources. The model must generate responses in near real-time while ensuring data privacy. Which strategy would be the most effective for balancing performance, accuracy, and privacy?
You are developing a chatbot using a generative AI model to assist users with technical troubleshooting. The responses generated by the model are often too verbose, overwhelming the user with unnecessary details. What prompt engineering strategy would you use to make the responses more concise and user-friendly?