Welcome to Mans International “Be Your Own Boss” Program

Have you dreamed of being your own boss?

Mans International “Be Your Own Boss” Program is designed to help people from all walks of life around the world who are committed to changing their way of thinking, improving their abilities, and achieving financial freedom and time freedom.

Before You Start

First of all, I’m sorry to tell you that it takes a long time to realize financial freedom and time freedom. If for whatever reason, you have obtained a large amount of wealth,  it doesn’t mean that you achieved financial freedom automatically. Because you may not have the ability and psychological capacity to manage large amounts of wealth, the money will be consumed at a rate you can’t imagine. 

You might say, can I just ask a financial professional to help me take care of my wealth? The question I asked was do you have the ability to select an outstanding and suitable professional?

If you feel that you ALREADY have independent thinking and various skills, then you do not need to participate in this program! All the best!

Our Values

If you DON’T agree with our values, please do not disturb!

Check Mans International “Be Your Own Boss” program values:

Value #1 – Honesty Watch the video

Value #2 – No complaints Watch the video

Value #3 – Courage Watch the video

Value #4 – Never give up Watch the video

To be continued.

How To Join Mans International “Be Your Own Boss” Program

This program is an INVITE ONLY program.

Please read our “how to join” information page carefully.

If you meet the requirements, congratulations, you will embark on a new journey to financial freedom and time freedom under our continuous guidance.

Not Ready Yet

If you are not ready yet, don’t worry. Every week, we create content and open it to the public.

Weekly Newsletter 2021.07.23

You can either send an email to info@mansinternational.com and we will send you the latest content regularly.

Before You Go

Every year we make plans. Every day we receive tons of information and learn a lot of knowledge, but why most people still can’t make choices that are beneficial to themselves in the long run, achieve their goals, and become a better version of themselves? 

Think about these questions when you have time.

Resource page – Mans International Be Your Own Boss program

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© Mans International, 2021. No part of www.mansinternational.org may be reproduced in whole or in part in any manner without the permission of Mans International.

AI 时光解语:用技术解码遗憾,与过去温柔和解

在你到目前为止的人生里有没有什么遗憾?如果AI 可以帮你重新回到过去,再经历一遍,发现一些你没有注意的细节,帮你打开心结,你愿意吗?

故事 — Eulogy 悼念

先来讲个故事。故事的男主人公退休了,一个人过着悠闲的生活。有一天,他接到了来自一个神秘公司的电话。该公司是受他曾深爱过的前女友的家人的委托,希望他能帮忙回忆一些关于她的往事。他的前女友刚刚去世了。他犹豫了一下,但还是答应了。

不久,他收到一个盒子,叫做“回忆套件”。里面有一个小小的装置,就像一个纽扣。当他把它贴在太阳穴附近,启动后,一个温柔的女声响起——那是一个人工智能向导,专门帮助他唤起关于她的记忆。

可问题是……男主竟然什么都记不起来了。她的音容笑貌,全都模糊不清。

AI 温柔地建议他找找看有没有老照片或视频。他下楼在满是灰尘的地下室,翻箱倒柜找出了几张旧照片。但奇怪的是,每一张照片里,她的脸都被剪掉了。他震惊地意识到,他竟然连她长什么样子都不记得了。那些曾经温暖又鲜活的回忆,如今变得冰冷而沉默。

他回忆起他们最初相识时,她其实已经订婚了。可他们还是坠入了爱河,一起旅行,一起拍了很多照片——而后来,他却把照片里她的脸全剪掉了。

他还记得某个生日的夜晚,身为乐团大提琴手的她因巡演未能相伴。即便如此,她仍在晚间拨通电话送上祝福,可那时他犯了很多男人都会犯的错误,电话被和他在一起的女同事接了。结果,他们在电话里大吵一架。之后,前女友回来收拾好行李,离开了他。

其实之后男主曾经准备好戒指,还特意到前女友乐团所在地,订了一家豪华餐厅,想向前女友求婚。可惜天意弄人,一切为时已晚。

多年后,在 AI 的引导下,他发现当年她离开时在房间留下了一张纸条——但他当时完全错过了。纸条上,她坦白自己也曾短暂地背叛过那段感情,并发现自己怀孕了,没有任何爱,只是迷失了。她请求他的原谅,并写下了见面的地点。可他从没看到那纸条,于是这段感情,就在误会和沉默中,永远失去了。

这桩心事成为他生命里的隐痛,终其一生都未能释怀。

直到最后,AI 告诉他一个秘密:她不是普通的AI,而是他前女友女儿的数字化身。

在故事的最后,男主参加了前女友的葬礼。他看到一个女孩在礼堂演奏大提琴曲,琴声缓缓流淌,像是从回忆深处飘来的歌。

就在那一刻,他终于想起了她的脸,她的笑容。

泪水静静滑落,不只是为逝去的爱情,也是为那份仍然存在的温柔和记忆。因为爱,并没有真正消失,它藏在音乐里,也藏在他终于记起的那一张熟悉的脸里。他终于释然了。这是《黑镜》第七季里的一个故事叫做 Eulogy 悼念。

挥之不去的阴影:遗忘并非总是释怀

人性是复杂的,有时候,我们在很多年前一个不经意的决定,或者一时冲动做的事情,可能会让我们后悔一辈子。

生活里好多事情,我们以为早就翻篇、彻底放下了,可其实它们就像一颗种子,在我们心里长成了结。不知不觉中,这个心结会影响我们现在的生活,甚至改变我们做的每一个选择。

往事的回响:人工智能邀你直面逝去时光

在你的人生里,一定也藏着些难以释怀的遗憾吧!无论是错过的机会,还是没能说出口的话,都可能在某个瞬间突然涌上心头。如果现在有 AI 能帮你 “回到过去”,重新回顾那些重要时刻,你愿意尝试吗?

也许最后你不会得到什么实际的改变,但说不定在这个过程中,你能把憋在心里的情绪痛痛快快地宣泄出来;又或者,你能因此有勇气直面曾经的遗憾,真正地和过去和解。你心里的那个遗憾是什么?想不想借助 AI 给自己一个重新审视的机会呢?欢迎留言。

视频版

The Power of What Was Left Behind: How AI Can Help Us Find Peace with Our Past

Have you ever carried a regret — something you wish you’d said, done, or understood differently?

If AI could take you back to those moments, helping you relive them, notice what you once missed, and perhaps find peace ,would you want to try it?

The Story — Eulogy

Once upon a time, there was a man who had just retired. He lived a quiet, peaceful life, enjoying his days in solitude.

One seemingly ordinary afternoon, his phone rang. The caller ID displayed an unfamiliar number, but something compelled him to answer.

A calm, professional voice greeted him. It was from a mysterious company, calling on behalf of the family of someone he hadn’t heard from in years — his former lover. She had just passed away. Her family, hoping to preserve the fragments of her past, asked if he would be willing to help piece together the memories they once shared.

He hesitated. The past was a tangled web of emotions, and opening that door again felt frightening and strangely alluring. After a long pause, with a quiet sigh and a mix of uncertainty and unspoken longing, he said yes. He had no idea that this one choice would take him on an unexpected journey — one of rediscovery, buried emotions, and long-forgotten moments.

Soon after, a package arrived: the “Memory Kit.” Inside was a small, button-like device. When he placed it near his temple and turned it on, a soft, warm female voice spoke — it was an AI guide, carefully designed to help him recall the woman he once loved.

But there was a problem.

He couldn’t remember her. Not her voice. Not her face. Everything about her was blurry, as if time had quietly erased the edges of their story.

The AI gently suggested that he try looking for old photos or videos that might spark his memory. He made his way down to the dusty basement, where time seemed to have stood still. After rummaging through boxes filled with forgotten keepsakes, he finally found some old photographs. But something was deeply unsettling — her face had been cut out of every single one.

He froze. He couldn’t even remember what she looked like. The memories that were once vivid and full of warmth now felt distant, like shadows slipping through his fingers.

As fragments of the past began to surface, he remembered how they first met — how she was engaged at the time. Still, their connection was undeniable. They fell in love, stole moments between the chaos, travelled together, and took countless photos. And yet, for reasons he couldn’t fully explain even to himself, he had removed her face from every picture.

One memory struck him with particular force. It was his birthday. She, a gifted cellist, had gone on tour with her orchestra and couldn’t be there. She had called to wish him a happy birthday. But he made a mistake that many men might make on a lonely night — his female colleague picked up the phone. The silence on the other end spoke louder than any words. They fought. Words were said that couldn’t be taken back. She returned only long enough to pack her bags — and then she was gone.

In fact, after their fight, he had bought a ring. With hope still alive in his heart, he travelled to the city where her orchestra was performing and reserved a table at an elegant restaurant, planning to propose. But fate, as it often does, had other plans. He was too late.

Years later, with the guidance of the AI, he uncovered something he had missed all those years ago — a note she had left behind in the room before she walked away. Somehow, back then, he had completely overlooked it.

In that note, she made a heartbreaking confession: she, too, had momentarily lost her way. In her confusion, she had been unfaithful, and later discovered she was pregnant. She admitted there was no love in that betrayal, only fear and loneliness. She asked for his forgiveness and left an address, hoping he would still want to see her, to talk, to try again.

But he never read the note. And because of that missed moment, their story, once full of love and possibility, was lost forever, drowned in misunderstanding and silence.

He carried the weight of regret like a shadow, following him through the rest of his life.

Until, in the final moments of his journey, the AI revealed a truth she had kept hidden: she was not just an artificial guide, but the digital avatar of his ex-girlfriend’s daughter.

In the final scene, he attended his former lover’s funeral. In the quiet hall, a girl sat on stage, playing the cello. The music drifted softly through the air, like a voice calling from the past — familiar, aching, beautiful.

And in that moment, as the notes wrapped around him like an old memory, he finally saw her face again. Her smile. Her eyes.

Love had never truly vanished. It had simply waited — buried beneath time, silence, and sorrow — until he was ready to find it again.

He finally found peace.

This is the story told in the seventh season of Black Mirror, in the hauntingly beautiful episode titled “Eulogy.”

The Lingering Shadows: Forgetting Isn’t Always Letting Go

People are complex. Sometimes, a casual decision made years ago — or a moment of impulse — can leave us with a lifetime of regret.

There are things we believe we’ve moved on from, memories we think we’ve buried. But in truth, they linger like seeds planted deep within us. Over time, they grow into quiet knots in our hearts — subtle, but powerful. Without even realizing it, these knots can shape how we live today, influencing our emotions, our relationships, and the choices we make.

Echoes of What Was: AI’s Invitation to Face Lost Moments

We all carry a few lingering regrets — missed chances, words left unsaid, paths not taken. Sometimes, they rise to the surface when we least expect it.

But what if an AI could help you “go back,” not to change the past, but to revisit those moments? To see what you missed, to feel what you buried, to say what was left unspoken. Would you take that chance?

Maybe nothing on the outside would change — but inside, something might shift. You might finally release the emotions you’ve held in for so long, or find the courage to truly face your regrets… and make peace with them.

I’d love to hear your story. What’s the one moment you wish you could revisit — and would you want AI to help you do it? Share your thoughts in the comments below.

「硬核」突围:中国人形机器人从实验室「跑」向万亿场景

DeepSeek的爆火让资本圈陷入一场幻觉:仿佛只要给机器人装上AI大模型,就能瞬间解锁《西部世界》般的智能。但现实是,当科技巨头们还在实验室里调教大模型的“逻辑脑”时,成功 “破圈出道” 的是那些能做出各种炫酷动作的具身机器人。例如,宇树科技的机器人会鲤鱼打挺,优必选的Walker X会打太极,甚至连北京人形机器人创新中心的“天工Ultra” 都跑完了半程马拉松。

这背后折射出当前人形机器人产业的核心矛盾:

当前人形机器人产业的核心矛盾是 “炫技级硬件能力” 与 “尚处发展初期的 AI 水平” 间的显著断层。

根据立德机器人平台的报告,2025 年中国人形机器人市场规模将达 82.39 亿元,但其中超过 70% 的订单来自工业场景(如汽车制造、3C 电子)。在这些场景中,机器人仅需 “精准执行预设动作”,尚未对 “自主决策” 能力形成广泛刚需 。

人形机器人产业发展的新催化剂

刚刚过去的 4 月份,有两件和人形机器人相关的活动格外引人瞩目。4 月 15 日,第二届中国人形机器人与具身智能产业大会在北京举办;4 月 19 日,全球首场人形机器人半程马拉松赛事在北京亦庄鸣枪开跑。

据赛事官方数据显示,此次比赛全程 21.0975 公里,吸引了 20 支机器人队伍参赛,同时还有 12000 名人类选手同场竞技,最终仅有 6 支机器人队伍完成比赛,完赛率为 30%。

冠军“天工Ultra”以2小时40分42秒刷新运动性能纪录,最高时速达12公里/小时,续航突破2小时。这场充满科技感与挑战性的赛事,不仅是机器人技术的试金石,更折射出中国人形机器人产业发展的新趋势与新机遇。

技术验证:突破实验室的 “极限挑战”

马拉松赛事堪称检验机器人技术的 “终极考场”,对机器人的长时运动稳定性和复杂地形适应性提出了极高要求,有力推动技术从实验室走向商业应用。

  • 关节灵活性与动力系统革新:国产谐波电机的广泛应用成为一大亮点,通过降低电机转速,大幅提升关节输出能力。
  • 散热系统的极限考验:高负荷运行下,机器人关节需在 3 小时内完成超 10 万次动作,产生的高热量对散热系统是巨大挑战。
  • 开放环境适应性:面对大风、降雨、不同路面材质及坡度变化,基于强化学习的算法发挥了关键作用。某机器人通过实时感知环境数据,动态调整步态,在强风环境下依然保持稳定前行,展现出强大的环境适应能力。
  • 电池续航与能源管理:机器人换电技术成为赛事一大看点,热插拔技术实现了无需关机即可快速更换电池,类似无人机的备用电源设计,让机器人续航能力得到显著提升。
  • 通信系统的抗干扰能力:20 支机器人伍同场竞技,电机运行对信号的干扰、机器人之间的信号冲突等问题亟待解决。

产业链协同:国产核心部件的 “高光时刻”

这场机器人赛事不仅是前沿技术的竞技场,也成为展示中国工业供应链协同能力的重要平台。通过提升国产核心零部件的可见度与影响力,大大加速了进口零部件替代的进程。

像灵动科技、绿的谐波和柯力传感等公司充分展现了自身的实力,它们的产品在紧密相连的价值链中发挥着关键作用 —— 从动态平衡算法、力控传感器,到执行器、谐波减速器、空心杯电机、灵巧机械手、3D视觉系统,以及应用场景的数据提供商等各个环节均有涉及。

政策与资本:产业发展的 “双引擎”

在中国前瞻性的政府政策与大量资本投资的协同推动下,中国的机器人行业正经历着前所未有的增长。这种双引擎驱动的方式不仅加速了技术进步,还巩固了中国在机器人与智能制造领域的全球领先地位。

2025 年 3 月 5 日,李强总理的《政府工作报告》为中国的科技未来勾勒出了一幅全面的路线图。报告首次将 “具身智能” 和 6G 技术列为重点发展方向,同时还强调了促进商业航天事业、低空经济、生物制造以及量子技术的发展。这些领域被视为培育 “新质生产力” 的关键所在,彰显了中国致力于高科技、高效且可持续发展的决心。

在资本层面,产业基金通过 “产业运营” 模式整合生态,吸引行业内企业战略注资或提供订单,为产业发展注入强大动力。

国家创投基金:国家发展改革委宣布设立国家级创业投资引导基金,重点支持机器人、人工智能及前沿创新领域。该长期基金计划在20年内吸引近1万亿元人民币(约合1380亿美元)的投资,体现了中国对技术持续发展的强大决心。

工行科技创新基金:中国工商银行启动总规模800亿元人民币(约合110.4亿美元)的科技创新基金,聚焦半导体、先进制造等“硬科技”领域。此举与国家支持民营经济和推动科技进步的战略高度契合。

通过政策与资本的双重引擎,中国正加快构建一个融合政府引导与金融支持的协同生态系统。这不仅推动了机器人技术的快速落地,也为中国在全球新一轮技术创新竞争中抢占高地打下坚实基础。

商业化之路:技术、应用与成本的 “铁三角”

中国的人形机器人产业正在快速发展,这一进程由三大相互依存的支柱共同驱动:技术创新、多元化应用场景,以及成本优化。

中国企业在人形机器人研发方面不断取得突破,致力于实现与人类动作和互动的高度仿真。例如,灵动科技开发的算法已使机器人能够实现如持续奔跑等动态动作;而帕新科技则打造出具备触觉识别能力的传感器,使机器人能够分辨不同人类皮肤的质感。这些技术进展对于推动机器人融入以人为本的使用环境至关重要。

目前,人形机器人在中国的多个行业中已逐步落地应用。以汽车制造业为例,优必选正与一汽-大众等整车厂商合作,将机器人应用于装配线上,用于螺栓紧固和零部件安装等任务。

要实现人形机器人的广泛应用,降低生产成本是关键一环。中国制造商正凭借强大的电子和新能源汽车产业链,获得如执行器、电池等关键零部件的成本优势。例如,普渡机器人位于江苏的超级工厂年产能高达10万台,通过自动化与标准化联合生产大幅降低单位成本。而特斯拉的Optimus人形机器人中,超过50%的零部件来自中国,其中包括电机、传感器和减速器,凸显出中国在硬件制造上的全球竞争力。

中国式创新的「非对称突围」

中国正在走一条务实的发展路径——依托具有成本优势的硬件供应链抢占真实应用场景,并利用由此积累的数据反哺人工智能的演进。在最近的机器人赛事中,“天工Ultra”的夺冠不仅是捧回了一座奖杯,更是一种信号。

中国式的“非对称突围”是一种独特而扎根现实的战略:通过深厚的制造能力和以场景为驱动的快速迭代,迈向人工智能的长期领先。在这一战略中,每一颗螺丝、每一个传感器、每一条数据,都是一个更大系统的一部分,正悄然而有力地重塑智能机器的未来。

特别鸣谢以下专家的看法和专业分享:(排名无先后顺序)

  • 李丰,峰瑞资本创始合伙人;
  • 谌威,钛虎机器人产品生态负责人;
  • 何刚,财经领域专家,《财经》杂志主编;
  • 李翔,《详谈》主理人,得到 APP 前总编辑。

English version

Beyond the Lab: How China’s Humanoid Robots Are Running — Literally — Toward Commercialization KellyOnTech

The viral rise of DeepSeek has created a widespread illusion in the tech investment world: that equipping robots with large language models (LLMS) will instantly unlock Westworld-style intelligence. But while tech giants are still fine-tuning their AI “brains” in the lab, it’s the embodied robots — those capable of striking physical feats — that are already stealing the spotlight.

From Unitree’s robots performing backflips, to UBTech’s Walker X practicing Tai Chi, and even Tiangong Ultra completing a half-marathon, these machines showcase remarkable hardware finesse — but not true autonomy.

The Core Contradiction

At the heart of the humanoid robotics industry lies a growing gap:

Advanced hardware performance vs. underdeveloped AI cognition.

According to the Lide Robotics Platform, China’s humanoid robot market is projected to reach ¥8.24 billion (~$1.1B) by 2025, with over 70% of orders coming from industrial use cases such as automotive and electronics manufacturing. In these environments, what’s required is precise execution of pre-programmed tasks, not AI-driven decision-making.

A New Catalyst for the Humanoid Robotics Industry

April brought two high-profile events that spotlighted the rapid momentum in humanoid April brought two high-profile events that spotlighted the rapid momentum in humanoid robotics. On April 15, the 2nd China Humanoid Robotics and Embodied Intelligence Industry Conference was held in Beijing. Just days later, on April 19, the world’s first Humanoid Robot Half Marathon took place in Yizhuang, Beijing.

The race covered a full 21.0975 kilometres, drawing 20 robot teams and 12,000 human runners. Only 6 robot teams crossed the finish line — an impressive but modest 30% completion rate. The champion, Tiangong Ultra, broke performance records with a time of 2 hours, 40 minutes, and 42 seconds, hitting a top speed of 12 km/h and sustaining operation for over 2 hours.

More than a spectacle, this event served as a technological stress test and a vivid signal of new trends and opportunities emerging in China’s humanoid robotics industry.

Technology Proven: Pushing the Limits Beyond the Lab

The humanoid robot half marathon served as the ultimate proving ground, testing long-duration stability and terrain adaptability under real-world, high-stress conditions. It marked a critical step in transitioning robotic technologies from lab prototypes to commercial viability.

Key Technical Breakthroughs:

  • Joint Flexibility & Power System Innovation
    The widespread use of domestic harmonic drive motors was a standout. By reducing motor speed, they significantly enhanced joint output and control precision.
  • Thermal Management Under Extreme Stress
    Robots performed over 100,000 joint movements within 3 hours, generating substantial heat. This pushed thermal dissipation systems to their limits.
  • Environmental Adaptability in Open Terrain
    Facing wind, rain, varied surfaces, and elevation changes, reinforcement learning algorithms proved essential.
  • Battery Life & Power-Swap Efficiency
    Hot-swappable battery systems emerged as a key innovation, allowing seamless power replacement without shutting down, similar to drone backup systems, greatly extending operational duration.
  • Communication & Interference Resistance
    With 20 robots competing simultaneously, signal interference from motors and overlapping transmissions exposed the need for robust, anti-interference communication architectures.

Industrial Synergy: A Spotlight Moment for Domestic Core Components

This robotics competition was not merely a battleground for cutting-edge technologies — it also served as a crucial platform for showcasing the collaborative strength of China’s industrial supply chain. It accelerated the replacement of imported components by boosting the visibility and influence of domestic core suppliers.

Companies like Motional Electric, Leader Harmonic, and Keli Sensing demonstrated their capabilities in full, with their products playing key roles across a tightly connected value chain — from dynamic balance algorithms and force control sensors to actuators, harmonic reducers, hollow cup motors, dexterous robotic hands, 3D vision systems, and data providers for application scenarios.

Policy and Capital: The Dual Engines Driving China’s Robotics Industry

China’s robotics sector is experiencing unprecedented growth, propelled by a synergistic blend of forward-thinking government policies and substantial capital investments. This dual-engine approach is not only accelerating technological advancements but also solidifying China’s position as a global leader in robotics and intelligent manufacturing.

On March 5, 2025, Premier Li Qiang’s Government Work Report unveiled a comprehensive roadmap for China’s technological future. For the first time, the report highlighted “embodied intelligence” and 6G technology as focal points, alongside the promotion of commercial space endeavours, the low-altitude economy, bio-manufacturing, and quantum technology. These areas are identified as critical to cultivating “new quality productive forces,” emphasizing the nation’s commitment to high-tech, efficient, and sustainable development.

Complementing policy directives, industrial funds are adopting an “industrial operation” model to integrate the ecosystem, attracting strategic investments or orders from industry players and injecting strong momentum into the sector’s development.

  • National Venture Capital Fund: The National Development and Reform Commission announced the establishment of a state-backed venture capital fund targeting robotics, AI, and cutting-edge innovations. This long-term fund aims to attract nearly 1 trillion yuan (approximately US$138 billion) over 20 years, underscoring China’s commitment to sustained technological advancement.
  • ICBC’s Technology Innovation Fund: The Industrial and Commercial Bank of China (ICBC) launched an 80 billion yuan (US$11.04 billion) fund focused on bolstering “hard technology” sectors, including semiconductors and advanced manufacturing. This initiative aligns with central directives to support the private economy and technological progress

China’s dual-engine strategy of policy support and capital investment is driving the rapid development of its robotics industry. By fostering a synergistic ecosystem that combines governmental guidance with financial backing, China is well-positioned to lead the next wave of technological innovation in robotics and intelligent manufacturing.

Commercialization Path for Humanoid Robots in China: The “Iron Triangle” of Technology, Application, and Cost

China’s humanoid robotics industry is rapidly advancing, driven by a strategic focus on three interdependent pillars: technological innovation, diversified application scenarios, and cost optimization.

Chinese companies are making significant strides in developing humanoid robots that closely mimic human movements and interactions. For instance, LimX Dynamics has developed algorithms enabling robots to perform dynamic motions like continuous running, while PaXini Technology has engineered tactile sensors that allow robots to distinguish between different human skin textures. These advancements are crucial for integrating robots into environments designed for human use.

Humanoid robots are increasingly being deployed across various sectors in China. In the automotive industry, companies like UBTECH are collaborating with manufacturers such as FAW-Volkswagen to integrate robots into production lines for tasks like bolt tightening and component assembly.

Reducing production costs is essential for the widespread adoption of humanoid robots. Chinese manufacturers benefit from a robust electronics and electric vehicle supply chain, which provides critical components like actuators and batteries at lower costs. For example, Pudu Robotics’ super factory in Jiangsu boasts an annual capacity of 100,000 units, reducing per-unit costs through automation and standardized joint production. Tesla’s Optimus relies on >50% Chinese-made parts, highlighting cost advantages in motors, sensors, and reducers.

Conclusion: The “Asymmetric Breakthrough” of Chinese Innovation

China is charting a pragmatic course — leveraging its cost-effective hardware supply chain to seize real-world application scenarios, and using the resulting data to fuel AI evolution. The victory of “Tiangong Ultra” at the recent robotics competition is more than just a trophy — it’s a signal.

China’s asymmetric breakthrough is a uniquely grounded approach that transforms manufacturing depth and scene-driven iteration into long-term AI leadership. In this strategy, every bolt, sensor, and data point becomes part of a much larger system that is quietly, but powerfully, reshaping the future of intelligent machines.

Special thanks to the following experts for their insights and professional sharing: (in no particular order)

  • Chen Wei, Head of the Product Ecosystem of Titanium Tiger Robotics;
  • Li Feng, Founding Partner of FreeS Fund;
  • He Gang, an expert in the financial field and Editor-in-Chief of Caijing Magazine;
  • Li Xiang, Host of “In-Depth Talks” and former Editor-in-Chief of the Dedao APP.

阿尔茨海默病风险因素(不仅仅是年龄)——附科学自测方法

人的大脑从什么年龄段开始“偷懒”?

先来个小测试:你觉得大脑从什么时候开始衰老?

  • A. 20~30岁(青春正盛,大脑却悄悄“退休”?)
  • B. 30~40岁(事业巅峰期,脑子先“罢工”?)
  • C. 40~50岁(中年危机才来?晚了!)

答案:20多岁!

没错,就在你纠结“中午吃啥”的时候,你的大脑已经开始“衰退之旅”——神经元连接减少、记忆力逐渐“掉线”,甚至为未来的阿尔茨海默病埋下隐患。

阿尔茨海默症的最大风险因素是什么?

阿尔茨海默症的最大风险因素不是年龄,而是大脑老化的速度。

根据世界卫生组织2021年的数据,全球范围内,患有痴呆症的人数已超 5500 万。预计到 2050 年将飙升至 1.39 亿 。尤其当祖辈或家属中有阿尔茨海默症患者时,由于携带致病基因,这类人未来患痴呆症症的风险会显著增高。

漫漫人生,能够常伴我们的始终是自己。但是,如果患上阿尔茨海默症,在晚年失去独立生活能力,那情何以堪?

不过,别担心:根据科学研究表明约 40% 的大脑老化受生活方式影响,这意味着我们有能力减缓大脑老化进程。也就是说如果能跟踪大脑随时间的老化情况,并衡量生活方式的改变是否有效延缓了大脑衰老。

如何判断你的大脑是否健康?

时钟绘制测试(Clock Drawing Test)

先来做一个小测试,叫做画钟测试(Clock Drawing Test),这个测试能在很短的时间内测试受试者的大脑的四大核心功能。画钟测试在80%的痴呆早期筛查中有效,且比单纯问卷更客观!

请在一张白纸上画一个圆形时钟,并完成以下任务:

  1. 画出所有12个数字(位置要对哦!)。
  2. 将时间设置为“10点45分”(长短针分明!)。
  3. 自由发挥:给你的时钟加个创意边框(比如花朵、星星或小动物)。

测试原理:暗藏玄机的“时钟”

这个看似简单的任务,其实综合评估了大脑的 4大核心功能

  1. 视空间能力(圆形是否扭曲?数字是否挤在一侧?)。
  2. 执行功能(能否规划数字布局?时针分针逻辑?)。
  3. 注意力(是否漏掉数字或画错时间?)。
  4. 抽象思维(创意边框反映联想能力)。

评分标准(满分4分,下面每项因素各一分)

📊 结果参考

  • 4分:认知功能良好!
  • 2-3分:建议复查(如MoCA测试)。MoCA 测试即蒙特利尔认知评估量表(Montreal Cognitive Assessment),是一种用于评估认知功能的工具。
  • ≤1分:需就医进一步评估。
10:45

视频版

检测大脑健康的四大关键测试是什么?

结合我看过的国内外目前顶尖的大脑检测项目,要比较准确地跟踪和检测我们大脑的老化过程,需要多模态检测,具体包括四个关键测试:

  1. MRI (磁共振成像)— 它是一种利用磁场和无线电波来生成人体内部详细图像的医学检查技术。对于大脑来说,MRI 可以提供非常清晰的结构图像,帮助医生诊断各种问题,比如肿瘤、中风、脑损伤、阿尔茨海默症等。
  1. 血液生物标志物 — 大脑检测中的血液生物标志物,简单来说,就是通过抽血来检测一些特定的分子或物质,从而间接了解大脑的健康状况。这种方法比传统的脑部扫描(如 MRI)更方便、更便宜,而且不需要复杂的设备。常见的与阿尔茨海默症密切相关的生物标志物包括β-淀粉样蛋白(Aβ)和 Tau 蛋白等等。
  1. 认知测试— 大脑健康检测中的认知测试,是一种通过一系列问题或任务来评估你的记忆力、注意力、语言能力、逻辑思维等认知功能的工具。认知测试是一种非侵入性的评估方法,旨在检测大脑的认知功能是否正常。它可以帮助早期发现认知障碍,比如轻度认知损害(MCI)、阿尔茨海默症、血管性痴呆等。
  1. 基因分析 — 对于有脑部疾病家族史的个体,基因分析可以检测其携带相关致病基因的情况,评估其发病风险。

为什么评估大脑健康需要综合测试?

单一检测方法无法全面评估大脑健康,综合测试能弥补各自局限,提高准确性:

  1. 互补性:MRI看结构,血液标志物看生化变化,认知测试评估功能,基因分析预测风险。
  2. 早期筛查:单独使用可能漏诊(如早期阿尔茨海默病MRI可能正常,但血液标志物已异常)。
  3. 减少误判:认知测试易受教育水平影响,基因检测无法反映当前状态,需结合其他数据。

大脑健康是综合了 “身体 – 心理 – 遗传” 的复杂网络,单一检测如同盲人摸象。综合测试并非冗余,而是通过多维度证据链提高诊断精度,为个性化预防或治疗提供科学依据。

视频版

English version

Alzheimer’s Disease: The #1 Cause Isn’t Age! + A Scientific Self-Test Method

Alzheimer’s Disease: The #1 Cause Isn’t Age! + A Scientific Self-Test Method

At What Age Does the Brain Start to “Slow Down”?

Let’s start with a quick test: When do you think the brain begins to age?

A. 20–30 years old (In your prime, but is your brain secretly “retiring”?) 

B. 30–40 years old (At your career peak, but is your brain already “on strike”?) 

C. 40–50 years old (Midlife crisis?)


The answer: Your 20s!


Surprising, right? While you’re busy deciding what to have for lunch, your brain has already begun its decline — neuronal connections start decreasing, memory gradually weakens, and even the groundwork for future conditions like Alzheimer’s may be laid.

What Is the Biggest Risk Factor for Alzheimer’s?

The most significant risk factor for Alzheimer’s isn’t age — it’s brain aging.


According to the World Health Organization’s 2021 data, more than 55 million people worldwide have dementia, and this number is expected to soar to 139 million by 2050. Those with a family history of Alzheimer’s, especially those carrying certain genetic risk factors, face a significantly higher likelihood of developing the disease.


Throughout life, the one constant companion we have is ourselves. But if Alzheimer’s robs us of our independence in old age, what could be more devastating?


The good news: Scientific research suggests that up to 40% of brain aging is influenced by lifestyle choices. This means we have the power to slow the aging process. By tracking brain health over time and assessing the impact of lifestyle changes, we can take proactive steps to preserve cognitive function for the future.

How to Assess Your Brain Health?

 — Clock Drawing Test

Let’s start with a simple yet powerful test — the Clock Drawing Test. This quick assessment evaluates four key brain functions and is effective in 80% of early dementia screenings, offering a more objective measure than standard questionnaires.

Try It Yourself:

On a blank sheet of paper, draw a circular clock and complete the following tasks:

✅ Write all 12 numbers in the correct positions.

✅ Set the time to 10:45 (make sure the hour and minute hands are distinct).

✅ Get creative — add a decorative border (i.e. flowers, stars, or animals).

What This Test Reveals

This seemingly simple task evaluates four core cognitive functions:

  1. Visuospatial ability (Is the circle distorted? Are numbers crowded on one side?)
  2. Executive function (Is the number placement logical? Are the hands drawn correctly?)
  3. Attention (Did you miss numbers or set the wrong time?)
  4. Abstract thinking (Your creative border reflects associative thinking skills.)

Scoring Criteria (Total: 4 points, 1 point each)

Clock Drawing Test Scoring Criteria

📊 Results Interpretation: 

🔹 4 points — Normal cognitive function! 

🔹 2–3 points — Consider further evaluation (e.g., MoCA test). 

🔹 1 point or less — Seek medical assessment.

Try it out and see how your brain is doing!

Video version

The Four Key Tests for Monitoring Brain Health

  1. MRI (Magnetic Resonance Imaging) — MRI uses magnetic fields and radio waves to generate detailed images of the brain. It provides high-resolution structural scans, helping doctors diagnose conditions such as tumors, strokes, brain injuries, and neurodegenerative diseases like Alzheimer’s.
  2. Blood Biomarkers — Blood tests can detect specific molecules or substances that indicate brain health. Compared to traditional imaging techniques like MRI, blood biomarker analysis is more convenient, cost-effective, and requires minimal equipment. Common biomarkers include beta-amyloid (Aβ) and tau proteins, which are closely linked to Alzheimer’s disease.
  3. Cognitive Testing — Cognitive assessments evaluate your cognitive functions, such as memory, attention, language skills, and logical reasoning, through structured tasks and questionnaires. These non-invasive tests help identify cognitive impairment at an early stage, including mild cognitive impairment (MCI), Alzheimer’s disease, and vascular dementia.
  4. Genetic Analysis — For individuals with a family history of neurological disorders, genetic testing can identify risk-related genes and assess predisposition to conditions like Alzheimer’s and other neurodegenerative diseases.

Why is a Comprehensive Approach Necessary?

No single test can fully assess brain health. A multimodal approach compensates for individual limitations, improving accuracy:

Complementary Insights — MRI examines brain structure, blood biomarkers reveal biochemical changes, cognitive testing evaluates functional performance, and genetic analysis predicts risk factors.

Early Detection — Some diseases may not show up in MRI scans in the early stages, but abnormal blood biomarkers can provide early warning signs.

Reducing Misdiagnosis — Cognitive tests can be influenced by education levels, while genetic testing only indicates risk, not current health status. Combining multiple tests provides a more reliable assessment.

Brain health is a complex interplay of biology, psychology, and genetics. Relying on a single test is like the blind men and the elephant — each gives only a partial picture. A multimodal approach builds a stronger evidence base for precision prevention, early intervention, and personalized care.

中文版

AI Hallucination Survival Guide: Case Studies, Causes, and Prevention Strategies

AI Hallucination Survival Guide: Case Studies, Causes, and Prevention Strategies

Have You Ever Been “Fooled” by AI?
 — The $5,000 Lesson from a Lawyer

Let’s start with a real case: Steven A. Schwartz, a veteran lawyer with over 30 years of experience, was fined $5,000 for submitting AI-generated false information in court.

In 2023, Schwartz represented Roberto Mata in a lawsuit against Avianca Airlines. Mata claimed he injured his knee after being struck by a metal food cart during a flight. Schwartz used ChatGPT for legal research to support his case and cited multiple “court cases” in his legal brief. However, the judge soon discovered that these cases didn’t exist in any legal database.


Schwartz later recalled that he specifically asked ChatGPT whether the cases were real, and the AI confidently assured him they were. 

Unfortunately, he was misled by AI hallucinations.

Today, let’s talk about AI hallucinations — why AI sometimes makes things up and how to avoid being misled by it.

What Is AI Hallucination?

AI Hallucination is when the content generated by a large language model like ChatGPT looks reasonable but is completely fictitious, inaccurate, or even misleading.

For example:

You ask AI: “Who invented time travel?” 

AI responds: “Dr. John Spacetime invented time travel in 1892 and was awarded the Nobel Prize in Physics for his discovery.”

Sounds fascinating, right? But there’s a problem — it’s completely false! Dr. John Spacetime doesn’t exist, time travel hasn’t been invented, and the Nobel Prize wasn’t even established until 1901.

How Does AI Hallucination Happen?

According to a research team led by Professor Shen Yang at Tsinghua University, AI hallucinations mainly stem from five key issues:

1. Data Availability Issues — AI relies on training data that may be incomplete, outdated, or biased.

2. Limited Depth of Understanding — AI struggles with complex questions and often makes assumptions.

3. Inaccurate Context Interpretation — AI may misinterpret the context of a query, leading to misleading responses.

4. Weak External Information Integration — AI cannot access or verify real-time external information and depends solely on existing data.

5. Limited Logical Reasoning & Abstraction — AI often makes logical reasoning and abstract thinking errors, especially for complex tasks.

Image source: Types of AI hallucinations summarized by Professor Shen Yang’s team.

Types of AI Hallucinations


Based on these factors, AI hallucinations can be categorized into five main types:

1. Data Misuse — AI misinterprets or incorrectly applies data, resulting in inaccurate outputs.

2. Context Misunderstanding — AI fails to grasp the background or context of a query, leading to irrelevant or misleading answers.

3. Information Fabrication — AI fills gaps with made-up content when lacking necessary data.

4. Reasoning Errors — AI makes logical mistakes, leading to incorrect conclusions.

5. Pure Fabrication — AI generates entirely fictional information that sounds plausible but has no basis in reality.

Tips to Protect Yourself from AI Hallucinations

AI hallucinations are inevitable, but you can reduce the risk of being misled by improving how you interact with AI. Here are two simple yet effective strategies:

1. Give Clear Instructions — Don’t Make AI “Guess”

— Be specific: Vague prompts can cause AI to “fill in the blanks” with incorrect information. Instead of asking, “Tell me some legal cases,” ask, “List U.S. federal court cases related to aviation accidents from 2020.”

Set boundaries: Define limits for AI responses, such as “Use Xiaomi’s 2024 Financial Statement.”

Request sources: Ask AI to provide citations or references so you can verify the information.

2. Verify AI’s Output — Don’t Trust It Blindly


 — Check sources: If AI provides references, make sure they exist and are credible. Verify citations from websites or academic papers.

 — Stay skeptical: Treat AI-generated content as a reference, not absolute truth. Use your own expertise and common sense to assess accuracy.

Cross-check with other tools: Use multiple AI platforms to answer the same question and compare the results.

Remember, no matter how smart AI seems, it’s just a tool — the real judgment lies with you. Instead of getting tricked by AI, learn how to outsmart it!

Key Considerations for Choosing an AI Hallucination Detection Tool

With the rise of AI-generated content, many companies now offer solutions to help businesses detect and mitigate AI hallucinations. While I do not endorse specific providers, here are some key factors to consider when making a selection.

1. Core Evaluation Criteria

The most important aspect is assessing how the tool conducts fact-checking. Look for:

 — The evaluation metrics it uses to measure AI accuracy.

 — Whether it provides detailed explanation reports that clearly identify hallucinations, explain their causes, and cite reliable sources.

2. Advanced Features to Match Your Needs

Depending on your company’s specific use case, consider whether the tool offers:

 — Real-Time Verification Pipelines — Detects and corrects hallucinations as AI generates content.

Multimodal Fact-Checking — Simultaneously verifies text, images, and audio for accuracy.

Self-Healing AI Models — Automatically corrects inaccurate outputs without human intervention.

 — Enterprise-Specific Knowledge Integration — Custom AI fact-checking models tailored to private datasets.

3. Unique Differentiators


Some providers offer specialized features that may align with your company’s budget and requirements, such as:


 — Synthetic Data Generation for Hallucination Training — Creates controlled datasets to enhance AI verification models.

Crowdsourced Human Review — Combines AI detection with expert reviewers for hybrid verification.

 — Legal & Compliance Fact-Checking — Monitors AI-generated content for regulatory and contractual compliance.

 — Proprietary Transformer-Based Verification — Uses a unique AI architecture optimized for detecting hallucinations.

Choosing an AI hallucination detection tool is fundamentally about balancing the Accuracy–Cost–Scalability triangle. It’s essential to address current business pain points, pinpoint the affected processes, weigh costs against benefits, and ensure flexibility for future tech upgrades and expansion.

中文版

AI幻觉避雷指南:AI幻觉案例、成因与防御全解析

你有没有被AI“忽悠”过?

——从资深律师被罚5000美元说起

先讲一个真实案例:执业30多年的资深律师 Steven A. Schwartz,因在法庭上提交了由AI生成的虚假信息,被罚款5000美元。

2023年,Schwartz 律师代理客户罗伯托·马塔 (Roberto Mata) 起诉哥伦比亚航空公司。案件起因是马塔在飞行中被金属餐车撞伤膝盖。Schwartz 律师使用 ChatGPT 进行法律研究,并在法庭简报中引用了多个“案例”。然而,法官发现这些案例在法律数据库中根本不存在。

事后,Schwartz 律师回忆,他特意询问 ChatGPT 这些案例是否真实,AI信誓旦旦地给出了肯定答复。结果,他却被AI“坑”了。

今天,我们就来聊聊 AI 幻觉 —— 为什么AI会“胡说八道”,以及如何避免被它“忽悠”。

什么是 AI 幻觉?

AI 幻觉就是人工智能大模型像 ChatGPT 生成的内容看似合理,但实际上完全是虚构的、不准确的,甚至是误导性的。

AI 幻觉

举个例子:

你问 AI:“谁发明了时间旅行?”

AI 回答:“约翰·时空博士在1892年发明了时间旅行,并因此获得了诺贝尔物理学奖。”

听起来很酷,对吧?但问题是——全是假的!约翰·时空博士根本不存在,1892年也没有诺贝尔物理学奖(诺贝尔奖始于1901年)。

AI 幻觉是如何产生的?

清华大学沈阳教授团队总结之所以会出现AI幻觉主要是五个方面的问题,分别是:

  1. 数据可用性问题:AI依赖的训练数据可能不完整、过时或有偏差。
  2. 理解能力深度不足:AI对复杂问题的理解有限,容易“想当然”。
  3. 语境精确度不够:AI可能误解问题的上下文,导致回答偏离实际。
  4. 外部信息整合能力弱:AI无法实时获取或验证外部信息,只能依赖已有数据。
  5. 逻辑推理和抽象能力有限:AI在推理和抽象思维上容易出错,尤其是面对复杂任务。
图片来源:清华大学沈阳教授团队AI幻觉分类表

基于这些问题,AI 幻觉可以分为五大类:

  1. 数据误用:AI错误地使用或解读数据,导致输出不准确。
  2. 语境误解:AI未能正确理解问题的背景或上下文,给出偏离实际的回答。
  3. 信息缺失:AI因缺乏必要信息而“脑补”内容,填补空白。
  4. 推理错误:AI在逻辑推理过程中出错,导致结论错误。
  5. 无中生有:AI完全虚构信息,生成看似合理但实际不存在的内容。

个人防 AI 幻觉有什么小妙招?

AI幻觉虽然不可避免,但我们可以通过改善与AI的交互方式,有效减少被“忽悠”的风险。以下是两个简单实用的技巧:

1. 清晰输入指令:别让AI“猜谜语”

问题要具体:模糊的指令容易让AI“脑补”出错误答案。比如,别问“告诉我一些法律案例”,而是问“请列举2020年美国联邦法院关于航空事故的案例”。

设定边界:明确限制AI的回答范围,比如“仅基于2024年小米公布的财报”。

要求参考资料:让AI提供信息来源或引用出处,方便后续核查。

2. 及时核查输出:别全信AI的“鬼话”

检查来源:如果AI提供了参考资料,务必核实其真实性。比如,查看引用的网站或文献是否存在。

保持怀疑:将AI的输出视为“参考”而非“事实”,用你的专业知识或常识进行判断。

多工具对比:用不同的AI工具验证同一问题,看看结果是否一致。

记住,AI再聪明也只是工具,真正的判断力还在你手中。与其被AI“忽悠”,不如学会如何与它“斗智斗勇”!

公司挑选 AI 幻觉识别工具有什么关键考量?

市面上涌现出众多助力公司应对 AI 幻觉的公司。在此,不做具体推荐,仅在您挑选时提供几点注意事项。

首要的是评估这些机构事实核查的方式,包括设定的评估指标,以及是否提供详尽的解释报告,清晰标记 AI 幻觉的缘由并附上来源参考。

然后根据公司具体应用场景,来判断是否需要以下附加功能,比如:

实时验证管道:在 AI 生成内容时,即刻检测并纠正幻觉;

多模态验证:同步对文本、图像及音频进行事实核查;

自修复 AI 模型:AI 能自动修正错误内容,无需人工干预;

企业专属知识集成:基于私有数据集,定制 AI 事实核查模型。

另外,部分公司还提供差异化功能,您可根据预算与需求进行抉择:

用于幻觉训练的合成数据生成:创建可控数据集,优化 AI 验证模型能力;

众包人工审核:将 AI 与专家审核员结合,采用混合验证模式;

法律与合规性核查:着重监测 AI 内容是否符合法规和合同要求;

专有 Transformer 模型验证:借助独特 AI 架构,专门强化幻觉检测能力 。

总结一下,选择AI幻觉检测工具,本质是平衡”精准度-成本-扩展性”的三角博弈——既要针对当前业务痛点,精准定位业务受幻觉干扰环节,权衡成本收益,又要预留技术接口应对未来需求升级,预留发展空间。

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English version https://mansinternational.org/ai-hallucination-survival-guide-case-studies-causes-and-prevention-strategies/

大语言模型是霍金 Manus 竟成其 “轮椅” KellyOnTech

有没有人跟我一样坐等 Manus 拯救的?邮箱里堆了超过5800封邮件,私信天天爆满,我都感觉自己马上要被这些信息 “淹没”,直接进入想罢工摆烂的状态了。

现在,我已经迫不及待地搓手等待 Manus 的申请码了! 快来拯救我吧,Manus!

2025 年 3 月 6 日,AI 发展迎来重磅时刻 ——Manus 发布!这可是能脱离人工直接指导,独立完成复杂现实任务的自主 AI 代理,由中国初创公司 Monica 打造。

Manus 的名字源自拉丁语“Mens et Manus”(头脑与手),与麻省理工校训不谋而合,象征着创意与执行的完美结合。

“AI 界的六边形战士” 肖弘

提到 Manus 有必要先了解一下被誉为“AI 界的六边形战士” 的创始人肖弘。肖弘虽然是90后,但其实是创业老手,以其卓越的技术能力和商业化经验闻名。

图片来源:新浪科技 Monica 创始人 肖弘

2015 年创立夜莺科技,推出微信公众号运营工具 “壹伴助手” 和 “微伴助手”,服务超 200 万 B 端用户,2020 年项目被某独角兽企业收购。

2022 年他创立 “蝴蝶效应” 公司,推出 AI 浏览器插件 Monica,最初以 ChatGPT for Google 插件形式进入市场,快速积累超 1000 万用户,成为海外头部 AI 助手产品。

Manus 项目最早在2017年上半年开始融资,创始团队以 300万人民币出让10%的股权,但当时许多投资机构并不看好这一项目。然而,肖弘凭借其坚持和创新,最终将 Manus 打造成全球首款通用AI代理产品,重新定义了AI的能力边界。

Manus 到底解决了什么问题

我们常说,认知和见识决定生活的高度。很多人都有目标,比如“今年存一万元去旅游”,但往往缺乏清晰的规划路径。这就是 Manus 的用武之地!

Manus 作为 AI 代理(Agent),它不仅能提供建议,还能独立规划并执行复杂任务,直接交付完整成果。它的强大之处在于:

  1. 连续自主执行:无需反复提示,Manus 可以自主完成任务。
  2. 多任务处理:一次接收一堆任务,甚至能自动解锁压缩包!
  3. 智能拆解与规划:比如,当测试者麻宁让 Manus “给4岁孩子讲清楚伯努利原理”时,Manus 自动拆解任务,生成互动网页,用气球、飞机、泡泡等生活场景辅助理解,还附上了互动小游戏。相比之下,ChatGPT 或 DeepSeek 只能提供文字回答。

技术优势

Manus 采用 Multiple Agent 架构,能在虚拟机中调用多种工具(如编写代码、浏览网页、操作应用等),直接完成任务。在 GAIA 基准测试*中,它的性能甚至超越了 OpenAI的产品。

*GAIA基准测试是一项用于衡量AI代理在无需持续人类指导的情况下,独立规划、执行和完成现实世界任务能力的测试。

Manus比通用大语言模型厉害吗

Manus 和通用大语言模型并不是同一类产品。知名创业者傅盛的观点很有道理,大语言模型,比如 DeepSeek、ChatGPT,是智能的核心,如同拥有深邃思考的大脑。而 Manus 本质上是强化了 AI 的易用性,像是给这个强大的 “大脑” 加了加了一层“外壳”,帮助它与各种网站和工具无缝对接。

打个比方,大语言模型就像《时间简史》的作者、著名物理学家霍金——拥有深邃的思考和理性,却在和世界的互动上存在局限。Manus 就像霍金的轮椅,有了它,霍金才能自如地与外界交流。

A Brief History of Time Stephen Hawking

Manus 的独特之处在于,它将大语言模型的智能转化为实际的行动力,让 AI 不仅会“想”,更会“做”。

Manus 是通用人工智能代理吗

这句话本身值得商榷。大语言模型(如 DeepSeek,ChatGPT)才是“通用”的,而 AI Agent(如 Manus)更像是基于人类经验总结的模板,帮助大语言模型在特定领域增强能力。由于每个领域的模板不同,AI Agent 很难穷尽所有的领域,很难做到真正的“通用”。

畅想一下,未来我们可能会出现各种专用 AI 代理。就像人类虽然智力相近,但通过不同培训形成了不同的专业能力。我个人更加偏向 agent 是专业选手。

关于 Manus,你怎么看?欢迎留言分享!

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English version

Hawking’s Brain Meets Its Wheels: The Big Language Model Meets Manus in a Revolutionary Fusion KellyOnTech

Is anyone else eagerly waiting for Manus to save the day? My inbox is buried under 5,800+ unread emails, and my direct messages are constantly overflowing. I feel like I’m drowning in information and want to go on strike.

Overflowing Emails and DMs

Now, I can’t wait to rub my hands and wait for Manus’s application code! Come and save me, Manus!


 On March 6, 2025, AI development ushered in a major moment — Manus was released! This is an autonomous AI agent that can independently complete complex real-world tasks without direct human guidance. It was created by the Chinese startup Monica. 


The name Manus comes from the Latin “Mens et Manus” (head and hand), which coincides with the motto of MIT, symbolizing the perfect combination of creativity and execution.

Xiao Hong — China’s “Ultimate AI Warrior”

To understand Manus, you first need to know its founder — Xiao Hong, widely recognized as the “Hexagonal Warrior in AI” for his exceptional technical expertise and commercialization skills. 

Image source: Sina Technology Monica Founder Xiao Hong


Born in the 1990s, Xiao Hong is already a seasoned entrepreneur:

2015: Founded Nightingale Technology, launching WeChat tools Yiban Assistant and Weiban Assistant, serving 2M+ business users. The project was later acquired by a unicorn in 2020.

2022: Founded Butterfly Effect and launched the AI browser plug-in Monica — initially a ChatGPT-for-Google tool. It quickly amassed 10M+ users, becoming a top AI assistant worldwide.

Xiao Hong actually started raising funds for Manus back in 2017, selling 10% equity for 3M RMB (USD 410K). At the time, many investors were skeptical. But through persistence and innovation, Manus has emerged as the world’s first general AI agent, redefining what AI can achieve.

What problem does Manus solve?

We often say that your knowledge and vision shape your life. Many people set goals — like saving $10,000 for a trip — but struggle to create a clear, actionable plan. That’s where Manus comes in!

As an AI agent, Manus doesn’t just give advice — it independently plans and executes complex tasks, delivering real results. Here’s what makes it a game-changer:


1. Autonomous Execution — No need for constant prompts. Manus completes tasks independently. 

2. Multitasking Mastery — It can handle multiple tasks at once, even unpacking compressed files automatically. 

3. Smart Task Breakdown — When tester Ma Ning asked Manus to “explain Bernoulli’s principle to a 4-year-old”, Manus didn’t just generate text — it created an interactive webpage with balloons, airplanes, and bubbles, plus mini-games to make learning fun. In contrast, ChatGPT or DeepSeek would only provide a text-based explanation.


Technical Advantages 

 Manus uses a Multiple Agent architecture, leveraging tools like code writing, web browsing, and app operation within a virtual environment to complete tasks. In the GAIA benchmark*, it even performs better than other AI products, such as OpenAI.


* The GAIA benchmark is a test that measures how well an AI agent can plan, execute, and complete real-world tasks independently — without constant human guidance.

Is Manus Better Than General Large Language Models?

Manus and general large language models (LLMs) like DeepSeek and ChatGPT aren’t the same kind of product. 

As serial entrepreneur Fu Sheng aptly puts it, LLMs are the core of intelligence — like a deep-thinking brain. Manus, on the other hand, enhances AI’s usability by adding a “shell” to this powerful brain, enabling it to seamlessly connect with websites, tools, and the real world.

Serial entrepreneur Fu Sheng

Here’s a simple analogy:


 — LLMs are like Stephen Hawking (the famous physicist behind A Brief History of Time) — brilliant, deep thinkers but limited in interacting with the world.
 — Manus is like Hawking’s wheelchair, empowering him to communicate and act freely.

A Brief History of Time Stephen Hawking

What makes Manus unique? It bridges the gap between intelligence and execution, turning AI’s knowledge into action.

Is Manus the World’s First General AI Agent?

This claim is a bit tricky. Large language models (LLMs) like DeepSeek and ChatGPT are “general” by nature, while AI Agents like Manus act more like specialized templates built on human experience, enhancing LLMs’ capabilities in specific areas. Since each field requires different templates, it’s nearly impossible for AI Agents to cover all domains and achieve true “generality.”


In the future, we’ll likely see multiple specialized agents — much like humans, who share similar intelligence but develop unique professional skills through different training. So agents are destined to be experts, not jacks-of-all-trades.


What’s your take on Manus? Share your thoughts below!


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