Conceptos Básicos
The author argues that current artificial intelligence lacks a sense of self, proposing a Brain-inspired and Self-based Artificial Intelligence (BriSe AI) paradigm to address this gap by emphasizing the crucial role of the Self in shaping future AI models.
Resumen
The content delves into the limitations of current artificial intelligence in understanding and perceiving the world from a subjective perspective. It introduces the BriSe AI paradigm, highlighting the importance of self-awareness in developing advanced AI models. The hierarchical framework of Self is detailed, showcasing how different levels contribute to enhancing cognitive abilities. Various learning strategies are discussed, such as unsupervised learning, supervised learning, reinforcement learning, and more, all aimed at achieving human-level cognition through self-organized coordination.
Estadísticas
The Baxter robot achieved an accuracy rate of 94% in a multi-sensory classification task involving 40 distinct objects.
The brain simulation model showed distinct spatial distribution during anesthesia-induced loss of consciousness.
The NeuEvo framework integrates local synaptic dynamics with global network optimization for evolutionary learning.
Citas
"The hierarchical framework of Self highlights self-based environment perception, bodily modeling, autonomous interaction with the environment, social collaboration with others." - BriSe AI Paradigm
"Intelligent agents can distinguish themselves from others and understand others’ mental states based on self-experiences." - Social Self
"Empathy for others’ negative emotions becomes an intrinsic drive for altruism." - Affective Empathy