Wang Rui, Liu Shixuan, Fan Changjun, Li Guozheng, Huang Jincai, Liu Zhong, Zhou Gang
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Intelligent Game and Decision Lab, Academy of Military Science, Beijing 100000, China.
Innovation (Camb). 2025 Feb 4;6(7):100834. doi: 10.1016/j.xinn.2025.100834. eCollection 2025 Jul 7.
In recent years, artificial intelligence (AI) has achieved tremendous development, akin to a significant leap, similar to progressing from 1 to 100. However, a significant gap still exists between current machine intelligence and human wisdom: machine intelligence is constrained to post hoc inference based on existing data, lacking the ability for genuine exploratory innovation and possessing no prospective reasoning inherent to human wisdom. Drawing inspiration from human wisdom, this article presents conjectures for overcoming the four dilemmas faced by machine intelligence: neglect of silicon-based cognition, lack of artistry, pitfall of perfectionism, and obsession with uniformity. These conjectures aim to propel machine intelligence toward machine wisdom, achieving a great leap from 1 to i.
近年来，人工智能（AI）取得了巨大发展，宛如一次重大飞跃，类似于从1发展到100。然而，当前的机器智能与人类智慧之间仍存在显著差距：机器智能局限于基于现有数据进行事后推理，缺乏真正的探索性创新能力，也不具备人类智慧所固有的前瞻性推理能力。本文从人类智慧中汲取灵感，提出了克服机器智能面临的四个困境的猜想：对硅基认知的忽视、缺乏艺术性、完美主义的陷阱以及对一致性的痴迷。这些猜想旨在推动机器智能迈向机器智慧，实现从1到i的巨大飞跃。
