When deploying agent frameworks like CRADLE in real-world applications, several limitations and ethical concerns need consideration:
Limitations:
Performance Issues: The effectiveness of LMM-based models like GPT-4V may vary based on the complexity of tasks or environments.
Spatial Perception Challenges: Recognizing fine-grained details or spatial relationships accurately might be challenging for current models.
Icon Understanding: Difficulty in interpreting domain-specific icons or symbols within interfaces could limit agent performance.
Ethical Concerns:
Privacy: Multimodal agents interacting with sensitive data raise privacy concerns if not handled securely.
Bias: Models trained on certain datasets may exhibit biases that influence decision-making processes.
Autonomy & Accountability: Autonomous agents must have clear accountability structures to address errors or unintended consequences.
Addressing these limitations while ensuring ethical deployment practices will be essential when integrating such advanced agent frameworks into real-world applications.