NCA-GENM Question 36
Single answerA company is developing a multimodal AI system for autonomous vehicles. The system must process video feeds, LiDAR data, and GPS information to make real-time driving decisions. Which emerging multimodal trend or technology would be most relevant for integrating these diverse data modalities into a unified model?
- A
Transformer-based fusion architectures
- B
Traditional rule-based decision systems
- C
Single-modality neural networks
- D
Generative Adversarial Networks (GANs)
Show answer and explanation
Correct answer: A
Explanation
Transformer-based fusion architectures represent a key emerging trend in multimodal AI. They enable the integration of data from various sources, such as video, LiDAR, and GPS, into a unified model for complex tasks like autonomous vehicle navigation. This makes them the most suitable choice for the described scenario.
- A. Correct.
Transformer-based fusion architectures are designed to integrate multiple data modalities, making them a relevant emerging technology for applications requiring unified processing of diverse input types like video, LiDAR, and GPS data.
- B. Incorrect.
Traditional rule-based decision systems are not flexible or scalable enough for modern multimodal AI tasks, especially those requiring real-time integration of advanced sensor data.
- C. Incorrect.
Single-modality neural networks are designed to handle data from only one type of input, and thus are not suitable for tasks requiring multimodal integration.
- D. Incorrect.
Generative Adversarial Networks (GANs) are primarily used for generating new data (e.g., images) and are not inherently designed for fusing multiple data modalities in real-time decision-making systems.