NCA-GENM Question 38
Select 3A company is developing an AI assistant that can process customer support emails containing text, audio attachments, and images. Which emerging multimodal trends or technologies should the company focus on to ensure the assistant can handle these inputs effectively?
- A
Transformer-based models with cross-modal attention mechanisms
- B
AI models designed exclusively for text processing
- C
Unified multimodal pretraining frameworks
- D
Edge AI devices for real-time processing of multimodal inputs
- E
Generative AI models optimized for single-modality output
Show answer and explanation
Correct answers: A, C, D
Explanation
To handle multimodal inputs effectively, the company should focus on technologies that enable the integration and processing of multiple data types, such as text, audio, and images. Transformer-based models with cross-modal attention mechanisms and unified multimodal pretraining frameworks are essential for achieving this. Edge AI devices are also relevant for real-time processing needs. Single-modality models are not sufficient for such scenarios.
- A. Correct.
Transformer-based models with cross-modal attention mechanisms are increasingly popular for enabling understanding and correlation between text, audio, and image inputs in multimodal applications.
- B. Incorrect.
AI models designed exclusively for text processing are limited to single-modality inputs and do not support multimodal use cases like combining text, audio, and images.
- C. Correct.
Unified multimodal pretraining frameworks help train models on diverse data types simultaneously, which enhances their ability to process and correlate multimodal inputs.
- D. Correct.
Edge AI devices for real-time processing of multimodal inputs are an emerging trend that allows for efficient and low-latency processing, especially in customer-facing applications.
- E. Incorrect.
Generative AI models optimized for single-modality output are not suitable for scenarios requiring the integration of multiple data types, such as text, audio, and images.