Group 1 - The core viewpoint of the articles highlights that MiroMind, an AI company founded by philanthropist Chen Tianqiao, has achieved top rankings in the FutureX evaluation, surpassing many international competitors and closed-source commercial models [1][2] - MiroMind's MiroFlow framework, powered by GPT-5, is designed specifically for prediction and decision-making, utilizing a memory-driven mechanism that distinguishes it from traditional text-output generative models [1] - The framework successfully predicted specific outcomes in sports rankings and cryptocurrency price movements, showcasing its capabilities in handling price volatility and risk management [1] Group 2 - MiroFlow achieved an impressive score of 82.4% on the GAIA-Validation benchmark and led in several other tests, indicating its competitive edge in the AI landscape [2] - FutureX, developed by ByteDance's SEED team in collaboration with Stanford University and Fudan University, is the first dynamic real-time LLM agent future prediction benchmark, focusing on questions with clear outcomes in the near future [2] - The benchmark evaluates AI's ability to predict various future events, including stock price movements, sports outcomes, political election results, and strategic directions of technology companies [2]

机器之心报道 机器之心编辑部 科技的走向、股市的涨跌、比赛的胜负、选举的结果…… 在 AI 时代，未来还会像过去那样不可知吗？ 全球首个动态实时 LLM 智能体未来预测基准 FutureX 推 出， 被马斯克称为衡量智能的最佳标准。 9 月 18 日，全球创新企业家、慈善家陈天桥旗下的 MiroMind 团队在这一 AI 未来大考中，连续第二周蝉联冠军。与专注文本输出的生成式模型不同，MiroMind 采用记忆驱动机制，专为预测与决策设计，旨在打造全球最好的预测大模型。 科幻电影早已为我们描绘过可能性：《少数派报告》AI 预测犯罪，让「未发生的事件」变得可防可控；《Her》智能系统能够预测人类行为和选择。今天，这些幻 想正逐步照进现实。 长期以来，AI 评估大多停留在答案已知的静态问题上，如同学生反复练习往年高考试卷。然而，真正有价值的能力是对未知未来的准确预测。投资和规划将不再 依赖盲目试错，可以提前洞察趋势，把握机遇，有效规避风险，真正掌握主动权。毕竟，谁不曾幻想过回到过去，提前买入 Nvidia 或 Tesla 呢？ 正如伊隆・马斯克所说：「预测未来的能力是衡量智能的最佳标准。」让 AI 具备像人类一样 ...

Core Insights - MiroMind aims to build a self-aware digital agent ecosystem, focusing on the continuous evolution of Artificial General Intelligence (AGI) through community collaboration and open-source principles [2][4]. Group 1: Open Source Ecosystem - MiroMind has developed a comprehensive open-source ecosystem that includes the Agent framework (MiroFlow), models (MiroThinker), data (MiroVerse), and training infrastructure (MiroTrain/MiroRL), all of which are open for learning, reuse, and further development [1][8]. - The MiroFlow framework achieved a state-of-the-art (SOTA) score of 82.4 on the GAIA validation set, surpassing existing commercial model APIs [1][12]. - MiroThinker, the core model, reached a SOTA performance of 60.2% on the GAIA-Text-103 dataset, nearing the performance level of OpenAI's Deep Research [1][15]. Group 2: Community Collaboration - MiroMind fosters a developer-centric environment that encourages community participation through data requests, feature customization, and technical challenges, with feedback directly influencing project development [2][22]. - The project organizes various community activities such as competitions, leaderboards, and hackathons to enhance developer engagement and contribution [22]. Group 3: Key Personnel - The project is led by Chen Tianqiao, a renowned entrepreneur known for his strategic vision and significant contributions to brain science and AI [4]. - Dai Jifeng, a key figure in the project, is a professor at Tsinghua University with extensive experience in computer vision and deep learning, having published over 80 papers with significant citations [5][6].