盛大集团和天桥脑科学研究院创始人，全球知名创新企业家、慈善家陈天桥在会上宣布：投入10亿美元 算力，支持全球科学家的创新人工智能研究。他表示："人类的进化从未停止，只是方式改变了。我们 的工具——现在包括AI——是进化的外部器官。" 陈天桥认为，AI的终极价值是发现。发现式智能可以主动构建关于世界的可检验理论模型、提出可被 证伪的假说，并在与世界的交互与自我反思中持续修正其理解框架的智能，这是真正意义的通用人工智 能。它能提出问题而非只回答问题，能理解规律而非仅预测结果，超越了模仿，具备创造和发现这些智 慧的本质能力 ，让AGI的意义不再是"取代人类"而是"进化人类"。 他指出，打造发现式智能需要建设五个能力，分别是神经动力结构、长期记忆、因果推理机制 、世界 模型、元认知与内在动机系统，它们共同形成一个有生命力、面向发现的智能闭环。为帮助全球科学家 推进发现式智能研究，陈天桥宣布了基准测试、结构性算力、PI孵化器等多项特别针对青年科学家的支 持。"Scale是巨人的道路，Structure是年轻人的机会"，陈天桥表示，"真正改变智能的下一个算法不会 出现在数据中心——它会出现在笔记本电脑上。" 盛大集团和天 ...

Core Insights - The first "AI-Driven Scientific Symposium" was held in San Francisco, featuring Nobel laureates and industry leaders discussing how AI can drive scientific discovery [1][2] - Chen Tianqiao announced a $1 billion investment in computational power to support global scientists in "discovery-driven intelligence" research [1] - The symposium highlighted the importance of AI's role in constructing verifiable world models and enhancing human capabilities rather than replacing them [1] Group 1: AI in Scientific Research - Chen Tianqiao emphasized the need for "discovery-driven intelligence" to possess five key capabilities: neural dynamic structure, long-term memory, causal reasoning mechanisms, world models, and metacognitive systems [1] - Omar Yaghi showcased AI's application in materials science, demonstrating a portable device that extracts water from the atmosphere in low humidity conditions using ChatGPT for molecular optimization [1][2] - David Baker presented the RFDiffusion3 model, which enables reverse design of proteins, providing new pathways for research on diseases like Alzheimer's [2] Group 2: AI and Genetic Research - Jennifer Doudna discussed the integration of AI with CRISPR technology, highlighting its potential to enhance understanding of unknown gene functions and advance personalized gene therapy [2] - The symposium concluded with the "AI-Driven Science Prize," recognizing young scientists for their cutting-edge research, indicating a shift towards AI-driven paradigms across multiple disciplines [3] Group 3: Societal Implications of AI - John Hennessy reflected on the rapid adoption of AI, stressing the need for humans to retain key decision-making authority and ensure transparency in AI-generated content [2] - He warned about the potential depletion of global data for AI training in the coming years, noting that improvements in computational energy efficiency have not kept pace with growth [2]