Which of the following is NOT a common form of data input for AI models?

Which of the following is NOT a common form of data input for AI models?

• A. Images and videos.
• B. Text from books and articles.
• C. Biometric sensors data.
• D. Manual annotations from human users.

Answer: (D)

The option indicating that manual annotations from human users are NOT a common form of data input for AI models is misleading. In fact, manual annotations are a crucial aspect of many AI training processes, particularly in supervised learning scenarios. Manual annotations involve labeling data, which is essential for teaching AI models to recognize patterns or make predictions based on specific inputs. For instance, in image recognition tasks, an AI model requires annotated images to learn the features of different categories, such as distinguishing between cats and dogs. This process essentially provides the model with the correct answers during training, enabling it to generalize and perform well on unseen data. The other forms of data input mentioned, such as images and videos, text from books and articles, and biometric sensor data, are indeed common sources of input for AI models. Images and videos are extensively used in computer vision tasks, while text data is critical for natural language processing models. Biometric sensor data plays an important role in applications like security and health monitoring, further demonstrating the variety of data sources utilized in AI.

The option indicating that manual annotations from human users are NOT a common form of data input for AI models is misleading. In fact, manual annotations are a crucial aspect of many AI training processes, particularly in supervised learning scenarios.

Manual annotations involve labeling data, which is essential for teaching AI models to recognize patterns or make predictions based on specific inputs. For instance, in image recognition tasks, an AI model requires annotated images to learn the features of different categories, such as distinguishing between cats and dogs. This process essentially provides the model with the correct answers during training, enabling it to generalize and perform well on unseen data.

The other forms of data input mentioned, such as images and videos, text from books and articles, and biometric sensor data, are indeed common sources of input for AI models. Images and videos are extensively used in computer vision tasks, while text data is critical for natural language processing models. Biometric sensor data plays an important role in applications like security and health monitoring, further demonstrating the variety of data sources utilized in AI.