Core Viewpoint - The article discusses the contrasting perspectives of AI pioneers Geoffrey Hinton and Hans Moravec on the future of artificial intelligence, likening AI to either a domesticated tiger or a human offspring, with implications for human civilization and evolution [1][3]. Group 1: Perspectives on AI Development - Hinton and Moravec, contemporaries in the AI field, represent different approaches: Hinton focuses on neural networks and learning capabilities, while Moravec emphasizes embodied intelligence and evolutionary processes [3][7]. - Moravec predicts that universal robots will surpass human intelligence between 2030 and 2040, as computational power continues to grow [4][5]. - The evolution of robots is expected to progress from basic learning to human-like reasoning, reflecting a gradual transformation of intelligence [5][6]. Group 2: Moravec's Paradox - Moravec's paradox highlights that human reasoning requires minimal computational resources, while perception and motor skills demand significant resources, challenging common intuitions about AI capabilities [9][12]. - The paradox suggests that the advanced perceptual and motor skills developed over millions of years of evolution are deeply embedded in human genetics, while abstract reasoning is a relatively recent development [8][11]. - This paradox serves as a reminder of the complexities in developing robots that can truly replicate human-like perception and action [13][14]. Group 3: Current State of Robotics - The article critiques the current state of humanoid robots, suggesting that many demonstrations are misleading and do not reflect true capabilities, as they often lack genuine environmental perception [14][15]. - Training robots to perform complex tasks is significantly more challenging than training them for simple, pre-programmed movements, emphasizing the need for advanced perception and interaction with the physical world [15][17]. - The distinction between "blind gymnasts" and robots capable of perception and action illustrates the current limitations in robotics research [15][16]. Group 4: Future Implications - The potential for AI to surpass human intelligence raises questions about the future relationship between humans and intelligent machines, with Moravec suggesting that robots may inherit human civilization [19][20]. - Hinton's views on AI's potential risks have evolved, indicating a belief that AI can be developed to be both intelligent and benevolent, though Moravec expresses skepticism about humanity's ability to control this evolution [18][19].

初中时候，我心智混沌，上课经常不听讲，学习上磕磕碰碰。 有次考物理，最后一道难题是关于浮力的。我完全不记得浮力公式，于是开始徒手推导，用一种感觉模 拟的方式，写出了自己的解答。 发卷的时候，我的答案居然对了，不过分数是零。同桌只写下了公式，后面啥都没做，得了5分。 物理学家费米 说：计算方法只有两种。 "第一种，也是我喜欢采用的，就是拥有一个明确的物理影像； 第二种，则必须具备严密的数学形式结构。" 也许那时我用的方法，就是在大脑中模拟一种初始的物理影像与过程吧。 后来读高中，我稍有改善，不再那么心不在焉，从物理中获得了更多的乐趣。 我尤其喜欢力学，因为只需要极少的公式，就能解决一些很复杂、很天马行空的难题。--照例用的是那 种"感觉"为主的方式。 我会在脑海中模拟物体的受力（以及力的分解），模拟运动，模拟各种要素组合之后的系统作用，然后 再用公式来计算。 爱因斯坦在1945年给数学家雅克·阿达玛写了一封信。阿达玛当时正在研究科学家和数学家的思维过 程。 其中有如下一段： "书写或说出的词语或语言，在我的思考机制中似乎不起任何作用。那些似乎在思想中充当要素的心理 实体，是某些可以'自愿地'被再现和组合的、或多 ...

Core Insights - The article discusses the evolution of AI models using games as a testing ground, highlighting the recent achievement of Google's AI model Gemini 2.5 Pro in independently completing the original Pokémon game, which has reignited interest in AI capabilities [4][30]. Group 1: AI Development and Gaming - AI has been tested through games for nearly a decade, with notable milestones including AlphaGo's victory over human players in Go and DeepMind's success in games like DOTA2 and StarCraft II [2][3]. - The use of games as a benchmark for AI intelligence remains prevalent, as demonstrated by Gemini's recent accomplishment, which was celebrated by Google's CEO and DeepMind's head [4][5]. Group 2: Challenges in AI Learning - The Moravec's paradox suggests that tasks perceived as easy for humans can be significantly more challenging for AI, which is exemplified by Gemini's achievement in Pokémon [6][7]. - The process of AI learning in games like Pokémon is complex, requiring the AI to develop its own understanding and strategies without predefined rules or guidance [16][17]. Group 3: Comparison of AI Models - Anthropic's Claude 3.7 struggled to progress in Pokémon, achieving only three badges after a year of iterations, while Gemini completed the game with approximately 106,000 actions, significantly fewer than Claude's 215,000 actions [11][30]. - The differences in performance between Claude and Gemini are attributed to their respective frameworks, with Gemini's agent harness providing better input processing and decision-making capabilities [34][35]. Group 4: Implications for AI Research - The ability of AI to navigate and complete games like Pokémon indicates its potential for independent learning and problem-solving in real-world scenarios [37][38]. - The choice of Pokémon as a training ground reflects the game's themes of growth, choice, and adventure, paralleling the journey of AI in understanding complex rules and environments [39][40].

来源：新华社 又见证历史了，朋友们！ 4月19日 全球首次"人机共跑"半程马拉松赛事 在2025北京亦庄半程马拉松 暨人形机器人半程马拉松中上演 关于这件事的报道和讨论 想必你今天 已经看过了很多、很多、很多…… 但小编我 还是被安排了再写条稿的任务…… 作为体育小编 机器人的事儿属实有点儿"超纲"了 但还好，咱有DeepSeek啊！ 毕竟 DeepSeek——科技创新"顶流" 人形机器人——又一科技创新"顶流" 让"顶流"锐评"顶流" 不过分吧？ 于是，小编就和DeepSeek聊了聊 但这家伙开场就"吐槽"之魂上身 莫不是看到机器人上"热搜"了 它对赛事过程的想象 也有那么点子"看热闹不嫌事大" 有了点小情绪？↓ 在此 对比赛稍稍有些了解的本小编 还是做一些说明： 导航靠香蕉 纯属DeepSeek自己的想象！ 此次比赛 允许操作员通过遥控器控制机器人 但也有队伍 还是选择了赋予机器人更多自主性 由团队工作人员携带信号发射器 然后让机器人自己根据信号 找到正确的方向奔跑 4月19日，小顽童队选手松延动力N2在比赛中。新华社记者 李贺 摄 充电桥段DeepSeek倒是猜对了 只不过这次机器人们 都是中途直接换电 ...

文章转载自 「 Linguista」 今年的 GTC 大会，英伟达发布了通用机器人模型 GR00T N1，老黄特别提到未来重点关注的趋势是「Physical AI」（物理 AI）。 不仅如此，老黄还把当下机器人领域的核心玩家都喊了过来，针对人形机器人领域当下的技术路径、数据问题以及通用模型和通用机器人等问题进行了深 入探讨，有不少很有价值的观点。 嘉宾阵容很强大，1X、Skild AI、Agility Robotics、Boston Dynamics……堪称具身智能领域的「华山论剑」。 嘉宾介绍： TLDR： Founder Park 正在搭建开发者社群，邀请积极尝试、测试新模型、新技术的开发者、创业者们加入，请扫码详细填写你的产品/项目信息，通过审核 后工作人员会拉你入群～ Bernt Børnich，人形机器人创企 1X 的创始人兼 CEO。1X 致力于构建完全自主的人形机器人。此前曾推出专注于家庭场景的人形机器人 NEO。 Deepak Pathak，具身智能创企 Skild AI 的 CEO 兼联创。Skild AI 致力于打造机器人通用「大脑」。此前曾推出曾推出可扩展的机器人基础模型「Skild B ...

我们这一代人 出生得太晚，没能赶上探索地球的地理大发现时代； 我们出生得又太早，可能无法亲身参与星际旅行，探索其他星系。 但我们却恰逢其时， 躬逢其盛，见证并参与到解决机器人技术难题的伟大历史进程中。相信在不久的将来，所有能够移动的物体都将实现自主化。 责编 | 王启隆 出品丨AI 科技大本营（ID：rgznai100） 今天这篇文章将会回顾英伟达大会重点宣传的一个论坛：《 通用机器人的新时代：人形机器人崛起 》（A New Era of Generalist Robotics: The Rise of Humanoids），英伟达跟紧物理世界 AI 和具身智能的新风向，邀请到美国 四家 顶尖的 人形机器人 公司老板，参与这场对话。 那么问题来了，现在全世界的人形机器人领域都有哪些顶级公司呢？ 相信很多人和小编一样，只认识国内的宇树机器人，对国外现在的机器人战局不太 了解，所以我们先看一张图，了解当前的时局情况： | 特斯拉 | | Google | | NVIDIA | | | | --- | --- | --- | --- | --- | --- | --- | | 美国 | | 美国 | | 美国 | ...