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This paper proposes a unified theoretical and practical framework for constructing AI agents that are dynamically embodied and capable of multimodal perception, reasoning, and action. The framework integrates principles from embodied cognition, adaptive learning, and multimodal data fusion to enable agents that can flexibly interact with complex environments.
Exploring how AI systems can develop spatial awareness and contextual understanding within digital environments, moving beyond traditional processing models toward true embodied intelligence.
This paper presents a comprehensive analysis of how integrated information theory and causal structure inform the possibility of artificial consciousness.
An abstract overview of the current state of cognitive science, the limitations of human understanding, and the potential for AI to help us understand the human brain.
This paper provides a comprehensive analysis of the current state of understanding of Large Language Models (LLMs).