March 26, 2025 - 09:46
Scaling artificial intelligence (AI) has been a primary focus in recent years, yet this approach may not suffice for achieving true intelligence. Insights from neuroscience suggest that the missing elements in AI development include embodied cognition, active inference, and a sense of agency. These concepts highlight the importance of physical interaction with the environment and the ability to adapt based on experiences.
Embodied cognition posits that intelligence is not merely a computational process but is deeply rooted in our bodily experiences and interactions with the world. This perspective challenges the traditional view of AI as a purely predictive tool, urging researchers to explore how machines can develop a more nuanced understanding of their surroundings.
Active inference, another critical concept, emphasizes the role of self-directed learning and adaptation in intelligence. By incorporating these principles, AI systems could potentially evolve beyond simple prediction models, allowing for more sophisticated decision-making processes. This shift could pave the way for AI that not only processes information but also engages with the world in a more meaningful and intelligent manner.
