陈天桥详解“大脑之镜” 首发世界级开源长期记忆系统

Core Insights - The concept of "memory" is viewed as a critical competitive advantage for future AI applications, marking a transition from tools to intelligent agents and from passive responses to proactive evolution [1][3] - EverMind, a team under Chen Tianqiao's Shanda Group, has launched EverMemOS, a world-class open-source long-term memory system aimed at becoming the data infrastructure for future intelligent agents [1][3] - Chen Tianqiao emphasizes the importance of "discovery-based intelligence," advocating for a research paradigm that endows AI with a persistent, coherent, and evolvable "soul" [1][3] AI Memory Systems - Current AI applications, including Claude and ChatGPT, have integrated long-term memory as a strategic feature, reflecting a broader trend in the industry [3] - EverMemOS is inspired by human memory mechanisms, mimicking the encoding, indexing, and long-term storage processes of the human brain [3][4] - The EverMind team aims to tackle one of the most profound challenges in AI: enabling machines to possess memory, which is seen as a gateway to higher levels of general intelligence [3][4] Discovery-Based Intelligence - Chen Tianqiao argues that true "discovery" in AI should involve posing questions and understanding principles rather than merely predicting outcomes [4] - He outlines two pathways to achieving "discovery-based intelligence": the "scale pathway," which focuses on the size of models and data, and the "structure pathway," which emphasizes dynamic and continuous cognitive processes [4][5] - The "scale pathway" has led to significant applications in AI, such as protein prediction and compound generation, but is viewed as limited in its ability to foster true understanding [5] Research and Development Initiatives - The Tianqiao Brain Science Research Institute plans to invest over $1 billion in dedicated computing clusters to support young scientists in exploring structural intelligence [6] - The institute has established a PI incubator, allowing young researchers to have independent budgets and lead their own experiments without waiting for graduation [6] - Chen Tianqiao stresses the need for interdisciplinary collaboration among neuroscience, information theory, physics, and cognitive psychology to drive innovation in AI [5][6]