What are the two key components of a multi-modal model?

• A. A language encoder and an image decoder
• B. A word generator and an image classifier
• C. A language encoder and an image encoder
• D. An audio learner and a visual learner

Answer: (C)

A multi-modal model is designed to process and integrate information from different types of data, such as text, images, and audio. The two key components of a multi-modal model are a language encoder and an image encoder.

The language encoder is responsible for converting text into numerical representations, allowing the model to understand and process natural language data. This is essential for tasks that involve language, such as generating descriptive captions for images or answering questions based on text.

The image encoder, on the other hand, processes visual data and translates images into formats that the model can analyze. This enables the model to recognize and extract relevant features from images, which is crucial for tasks such as object detection, image classification, and generating visual content.

By utilizing both a language encoder and an image encoder, a multi-modal model can effectively learn from and make sense of the relationships between different types of inputs, enabling it to perform complex tasks that require an understanding of both text and images simultaneously.