👉 Instructors' computing refers to the process where AI models, often large language models, are fine-tuned or adapted by human experts to better suit specific tasks, domains, or user needs. This involves manually adjusting model parameters through techniques like prompt engineering, where carefully crafted input prompts guide the model's responses, or by directly modifying the model's architecture or training data. Instructors might also use tools to analyze and optimize model outputs, ensuring they align with desired accuracy, ethical standards, or user expectations. This human-in-the-loop approach enhances the model's performance and relevance, making it more effective for specialized applications such as technical writing, medical advice, or creative content generation.
