香港大学马毅：智能的核心在于“自我验证与自我纠错”的能力

Core Insights - The evolution of intelligence is categorized into four stages: genetic intelligence represented by DNA, individual developmental intelligence formed by brains and perception systems, collective intelligence achieved through language, and finally, true artificial intelligence. The current AI models, represented by large models, are still in the primitive "genetic intelligence" stage, relying heavily on vast parameters and pre-training data, which leads to high resource consumption and inefficiency [1] Group 1 - The essence of life evolution is the activation of intelligent mechanisms, and current AI models lack individual memory and self-awareness [1] - The core of intelligence lies in the ability of "self-verification and self-correction," which allows for critical examination of existing knowledge to identify and rectify errors. Current large models serve merely as static knowledge repositories and cannot comprehend their content, resulting in logical confusion and "hallucination" issues [1] - Despite possessing vast amounts of "knowledge," current AI models do not exhibit true "intelligence" [1] Group 2 - Looking ahead, it is essential to study intelligence as a rigorous scientific and mathematical subject, focusing on building systems with individual memory and closed-loop autonomy capabilities [1] - The advancement of machine intelligence towards true "autonomous intelligence" should be promoted within an explainable theoretical framework [1]