人工智能可自发形成人类级认知？中国团队最新研究首次证实

Core Insights - A Chinese scientific team has demonstrated that AI, specifically multimodal large language models, can form object concept representation systems similar to human cognition, indicating that AI can achieve human-level understanding [1][3][4] - The research was conducted by the Chinese Academy of Sciences and published in the journal "Nature Machine Intelligence," providing a theoretical framework for developing human-like cognitive structures in AI [1][3] Research Methodology - The study utilized a combination of cognitive neuroscience theories, computational modeling, behavioral experiments, and brain science to create an innovative research paradigm [3][4] - A classic cognitive psychology task was employed, where both AI models and humans were asked to identify the least similar option from a trio of object concepts derived from 1,854 everyday concepts [4] Findings - The research team analyzed 4.7 million behavioral judgment data points to construct a "concept map" for the AI model, revealing 66 "mental dimensions" that were semantically labeled and significantly correlated with neural activity patterns in the human brain [4] - The study found that multimodal large language models exhibited higher consistency with human behavior in decision-making tasks, although humans tended to integrate visual features and semantic information more than the AI models, which relied on semantic labels and abstract concepts [4] - The core finding suggests that AI's "mental dimensions" align closely with human understanding of reality, marking a significant advancement from mere "machine recognition" to "machine understanding" [4]