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机器人企业骗局曝光:路演厅里上演“提线木偶” 聪明投资人也栽跟头

翟智超 2025/11/11 17:39
翟智超 2025/11/11 17:39

邦小白快读

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人形机器人市场存在骗局和投资风险,需关注重点信息和实操规避。

1.关键骗局曝光:企业虚假宣传订单和技术实力,例如初创公司伪造5000万元订单,无研发中心却展示人形机器人;技术造假如遥操作系统伪装成全自主分拣,实际依赖人工操控。

2.实用数据洞察:2025年中国具身智能市场规模预计52.95亿元,人形机器人市场82.39亿元,但2025年前7个月融资事件141起中,单笔过亿融资51起,显示泡沫风险;投资人经验如Gashero指出技术认知鸿沟和害怕错过心态易致误判。

3.风险规避建议:专业投资人如萧依婷团队通过MIT博士等专业背景鉴别项目,100个项目仅投1-2个;买家应实地核实订单真实性避免受骗。

具身智能领域的品牌声誉和市场潜力并存,需优化营销策略和产品开发。

1.品牌营销警示:企业虚假打造品牌形象,例如创始人自称中科院系却无真实研发支撑,暴露信誉风险;数据显示市场规模高速增长,2025年预计超52亿元,吸引资本但需真实创新。

2.产品研发启示:技术造假案例如物流分拣系统伪装感知能力,提醒真实研发重要性;消费趋势显示用户行为趋向AI产品,但夸大技术(如宣称大模型理解所有物体)易失用户信任。

3.渠道建设参考:贴牌生产模式依赖代工厂,但供应链问题影响交付;借鉴辰韬资本合伙人强调专业团队审查,避免定价竞争中的水分。

人形机器人市场机遇与风险并存,卖家可从中汲取增长策略和风险提示。

1.增长市场数据:2025年具身智能市场规模52.95亿元,人形机器人82.39亿元,融资事件141起;消费需求变化表现为FOMO心态驱动投资,但需求真实度需核实。

2.风险提示和应对措施:骗局如订单转手和遥操作造假导致供应链中断;事件负面影响需学习Gashero观点,警惕技术包装;正面机会在于市场扩张,但可学习点如专业投资人萧依婷团队100选1的筛选逻辑。

3.合作方式和商业模式:最新模式如贴牌生产暴露合作风险;扶持政策启示为依靠专业团队如MIT博士进行尽职调查,以规避风险。

产品生产和数字转型面临挑战,工厂需把握真实商业机会和技术启示。

1.生产需求问题:贴牌模式暴露产能不足,企业无自建工厂靠代工;设计需求显示造假实例如简易场景搭建机械臂,揭示真实设计和质量的重要性。

2.商业机会洞察:市场规模2025年超52亿元,融资事件频发;推进数字化启示如Gashero指出技术迭代快,工厂应加强自主研发。

3.电商和风险规避:数字化案例表明遥操作软件调用开源模型;可学习点如投资人强调核实订单,避免供应链中断风险。

行业技术痛点和发展趋势需要专业解决方案,服务商可优化服务响应。

1.行业发展趋势:具身智能赛道加速扩张,2025年市场预计52.95亿元,但技术迭代快,如大模型可靠性不足引发规划任务失败。

2.新技术和客户痛点:骗局如遥操作系统伪造感知能力,暴露认知鸿沟;客户痛点包括投资人FOMO心态导致误判,和初创公司虚假包装。

3.解决方案启示:专业投资机构采用MIT博士团队进行鉴别;案例中Gashero建议真实价值识别;服务可围绕尽职调查工具降低风险。

平台招商和运营需规避骗局风险,回应商业需求并提供可靠管理。

1.商业需求和问题:企业需求如订单核实问题,暴露贴牌模式缺陷;平台问题包括招商中遥操作造假误导投资人。

2.平台最新做法和风向规避:专业机构做法如萧依婷团队技术鉴别;风险规避启示从数据入手,2025年市场超52亿元但融资泡沫需筛选真实项目。

3.运营管理建议:政策无直接但可参考Gashero观点,加强平台对项目背景审核;管理费逻辑暴露预算驱动投资风险,提示平台强化透明规则。

具身智能产业新动象揭示研究启示,涉及商业模式和政策问题。

1.产业新动向和新问题:市场扩张中骗局频发,如虚构团队背景和遥操作造假;新问题包括技术路线不明朗,如VLA技术可靠性不足引发质疑。

2.商业模式分析:贴牌生产和融资驱动模式揭示不健康结构;代表企业如初创公司暴露靠资源获取订单;数据如2025年市场52.95亿元提供实证。

3.政策法规启示:案例中无人追责背景虚假,提示监管漏洞;Gashero观点可引申政策建议:加强投资规范和市场透明。

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声明:快读内容全程由AI生成,请注意甄别信息。如您发现问题,请发送邮件至 run@ebrun.com 。

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Quick Summary

The humanoid robot market is rife with scams and investment risks, requiring a focus on key information and practical avoidance strategies.

1. Key scam exposures: Companies falsify order books and technical capabilities—for instance, startups fabricating ¥50 million orders or displaying humanoid robots without R&D centers; technical deception includes disguising teleoperation systems as fully autonomous sorting, when they actually rely on manual control.

2. Practical data insights: China's embodied AI market is projected to reach ¥5.295 billion by 2025, with humanoid robots at ¥8.239 billion. However, of 141 financing deals in the first seven months of 2025, 51 exceeded ¥100 million, signaling bubble risks. Investor experiences, such as those shared by Gashero, highlight how technical knowledge gaps and fear of missing out (FOMO) lead to misjudgment.

3. Risk mitigation advice: Professional investors like Xiao Yiting's team use expert backgrounds (e.g., MIT PhDs) to vet projects, investing in only 1–2 out of 100 opportunities; buyers should conduct on-site verification of orders to avoid fraud.

The embodied intelligence sector offers both brand reputation opportunities and market potential, necessitating optimized marketing and product development strategies.

1. Brand marketing warnings: Companies risk credibility by fabricating images—e.g., founders claiming ties to the Chinese Academy of Sciences without genuine R&D backing. Market data shows rapid growth, with a projected ¥5.295 billion market by 2025, attracting capital but demanding real innovation.

2. Product R&D insights: Technical fraud cases, such as logistics sorting systems masquerading as感知-enabled, underscore the importance of authentic development. Consumer trends favor AI products, but exaggerated claims (e.g., asserting large models understand all objects) can erode trust.

3. Channel building references: OEM models rely on contract manufacturers, yet supply chain issues disrupt delivery. Learning from partners like Chen Tao Capital, who emphasize professional team scrutiny, helps avoid inflated pricing competition.

The humanoid robot market presents both opportunities and risks, offering sellers growth strategies and risk alerts.

1. Growth market data: The embodied AI market is forecasted at ¥5.295 billion by 2025, with humanoid robots at ¥8.239 billion and 141 financing deals. Demand shifts show FOMO-driven investments, but authenticity requires verification.

2. Risk alerts and responses: Scams like order transfers and teleoperation fraud cause supply chain disruptions. Negative cases, per Gashero's views, warn against technical packaging; positive opportunities lie in market expansion, with lessons from investors like Xiao Yiting's team, who select only 1 in 100 projects.

3. Collaboration models and business strategies: New models like OEM production reveal partnership risks. Support policies suggest relying on expert teams (e.g., MIT PhDs) for due diligence to mitigate risks.

Product manufacturing and digital transformation face challenges, requiring factories to grasp real business opportunities and technical insights.

1. Production demand issues: OEM models expose capacity shortages, as firms lack own factories and depend on contractors. Design fraud cases, such as simple setups mimicking robotic arms, highlight the need for authentic design and quality.

2. Business opportunity insights: The market is projected to exceed ¥5.295 billion by 2025, with frequent financing deals. Digital advancement lessons, from sources like Gashero, indicate rapid tech iteration, urging factories to boost independent R&D.

3. E-commerce and risk avoidance: Digital cases show teleoperation software using open-source models. Takeaways include investor emphasis on order verification to prevent supply chain disruptions.

Industry pain points and trends demand professional solutions, enabling service providers to optimize responses.

1. Industry development trends: The embodied AI track is expanding rapidly, with a ¥5.295 billion market expected by 2025, but fast tech iteration—e.g., unreliable large models causing task failures—poses challenges.

2. New technologies and client pain points: Scams like teleoperation systems faking感知 capabilities reveal knowledge gaps. Client issues include investor FOMO leading to misjudgment and startup false packaging.

3. Solution insights: Professional investment firms use MIT PhD teams for vetting; cases like Gashero's advise identifying real value. Services can focus on due diligence tools to reduce risks.

Platform recruitment and operations must avoid scam risks, address business needs, and ensure reliable management.

1. Business demands and issues: Client needs, such as order verification, expose OEM model flaws; platform issues include teleoperation fraud misleading investors during recruitment.

2. Latest practices and risk avoidance: Professional approaches, like Xiao Yiting's team's technical screening, offer guidance. Risk mitigation stems from data—e.g., a ¥5.295 billion market by 2025 requires filtering genuine projects amid financing bubbles.

3. Operational management advice: While no direct policies exist, Gashero's views suggest enhancing background checks on projects; budget-driven investment risks, revealed by fee structures, prompt platforms to strengthen transparency rules.

New dynamics in the embodied AI industry reveal research implications involving business models and policy concerns.

1. Industry trends and emerging issues: Scams proliferate amid market expansion, such as fictitious team backgrounds and teleoperation fraud; new problems include unclear tech pathways, like VLA reliability doubts.

2. Business model analysis: OEM production and financing-driven models expose unhealthy structures; representative firms, like startups, rely on resource access for orders. Data, such as the ¥5.295 billion market by 2025, provides empirical evidence.

3. Policy and regulatory insights: Cases of unaccountable background falsification point to regulatory gaps; Gashero's views imply policy recommendations: strengthen investment norms and market transparency.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

人工智能浪潮的席卷下,具身智能机器人被视为“AGI终极载体”,一条万亿级赛道正加速展开,但喧嚣之下也有暗影。

日前,一名上海投资人刘尚宪告诉蓝鲸科技记者,他们在考察一家人形机器人初创企业时,发现了明显的“水分”。“该公司成立于今年4月,既无研发中心,也无自建工厂,却宣称已手握5000多万元订单。创始人以‘中科院系’自居,办公区内陈列多款外观前沿的人形机器人,试图构建技术实力雄厚的企业形象。”

上述案例并非孤例。某具身智能创始团队成员李峰也向蓝鲸科技记者表示,其所在相关产业社群中,“某家企业又完成亿元级融资”、“某大厂战投已入场”等消息不断。但李峰也表示,当前市场上还出现了一些包装精巧的“具身智能项目”,这类项目仅需几步操作,就能快速成型,并登上路演舞台。李峰称,这类“遥操作造假”在机器人领域已是公开的“潜规则”。

此外,某大学机器人系统架构师、知乎创作者Gashero也指出,除上述案例外,有团队也常虚构成员背景,例如具有“大厂背景”或“高校团队”身份等,而真正在职人员通常不会公开以单位名义从事营利活动,长期使用此类头衔而未受追责的,身份真实性往往存疑,需要警惕。

令人意外的是,蓝鲸科技记者通过采访得知,面对“技术包装”,不少经验丰富的投资人依然选择出手。多位投资人表示,骗局得逞的背后,不仅是技术认知的鸿沟,更映射出创投圈在历次技术浪潮中反复陷入的悖论:当“害怕错过”的集体焦虑,撞上以“月”为单位迭代的技术黑箱,理性往往让位于恐惧,真实也容易湮没于表演。

“转手订单+贴牌生产”模式

在刘尚宪遇到的上述案例中,面对“无自有产能如何保障交付”的质疑,相关企业创始人回应称,可通过代工厂完成生产,并强调机器人编码已开源、制造难度有限,认为“订单本身就是核心竞争力”。

“但我们判断其本质并非科技企业,而更像一家依靠资源获取订单、进行贴牌销售的贸易公司,其订单真实性也难以核实。”刘尚宪称。

刘尚宪认为,当前人形机器人领域虽热度不减,但真正专注研发创新的企业仍属少数。

“除部分已形成技术影响力的企业在持续推进研发外,仍有大量初创公司停留在’转手订单+贴牌生产’的浅层模式,甚至出现依靠夸大技术实力吸引融资的现象,这与前几年人工智能行业的发展阶段有相似之处。”刘尚宪说。

上述李峰提及的“具身智能项目”项目则更具欺骗性。具其介绍,这类项目往往在办公区以纸箱、货架搭建简易场景,伪装成“物流分拣系统”。硬件上采用两套数字舵机机械臂套件,外观呈现四条机械臂协作,实际仅两条从臂具备动力,主臂仅作采集用途。组装过程也不难:团队用铝型材将两条从臂固定,再在结构顶部安装结构光摄像头,以此营造“感知—执行一体化”的假象。

李峰称,软件层面更具表演性,即在普通台式机上调用qwen-VL等开源模型提取目标,再借助OpenCV绘制检测框、叠加深度图,包装成具备“多模态感知”的视觉系统。完成技术包装后,团队便开始了路演表演。团队便指着屏幕上跳动的检测框,宣称其大模型“能理解世界上所有物体”,机械臂具备“全自主分拣能力”,“再投入几亿元即可研发出AGI机器人”。

然而,这套看似流畅的“全自主分拣”系统背后,隐藏着一个关键骗局。李峰告诉蓝鲸科技记者,所谓的智能操作实为精心伪装的“遥操作”:演示过程中,数字舵机主臂的控制线被刻意延伸至画面之外,由人员在投资人视线盲区手动操控完成动作。整个系统并无真正的感知与决策能力,却被公然标榜为“全自主智能分拣”。

Gashero指出,不仅初创团队,部分知名公司也曾采用类似手法。他强调,遥操作本身具备技术价值,问题在于有意混淆“人在回路的半自主”与“全自主智能”,误导投资人判断。

而乱象背后,或是具身智能赛道巨大预期之下,引发的对资本的“抢位”。《2025人形机器人与具身智能产业研究报告》显示,预计2025年中国具身智能市场规模将达52.95亿元,人形机器人市场更达82.39亿元,约占全球一半。2025年前7个月,该领域国内融资事件已达141起,超过2024年全年;其中单笔过亿融资51起,多家头部企业累计融资额超20亿元。

有投资人“100个项目,才投1-2个”

值得一提的是,上述乱象之下,在科技创投领域,投资人被创业者“误导”的现象时有发生。

Gashero对蓝鲸科技记者坦言,任何一个新兴领域都难以完全避免这种情况。这一现象在国际创投圈甚至被概括为“fake it,until make it”——即先通过包装制造假象,再设法弥补漏洞。

当下,广义互联网、人工智能等前沿领域的技术迭代速度不断加快,导致技术认知的有效期大幅缩短。“一旦脱离技术一线两三年,认知就可能全面落后,”Gashero指出。

Gashero称,许多曾被看重的“技术背景”,如今可能已难以真实反映当下的研发能力。他举例说,就在一年多前,行业还普遍认可具身智能的VLA技术路线,认为可以将复杂规划任务完全交由大语言模型处理,但几个月后的实践就证明,大模型在规划任务上的可靠性仍显不足。

在这种技术路线尚不明朗的背景下,“怕错过”(FOMO)心态成为影响投资决策的重要因素。Gashero分析认为,适度的FOMO是合理的,因为成功的企业需要在关键时点作出关键决策。他以通信行业为例:诺基亚因犹豫,而错失智能手机转型机遇,摩托罗拉则因过度超前的铱星计划陷入困境。

面对技术与市场的双重不确定性,投资人的风险逻辑也在不断演变。“高收益必然伴随高风险,这是基本规律,”Gashero强调,投资人不应追求无风险的高回报。在他看来,投资人的核心职责并非精准预测未来,而是有效识别真实价值,剔除虚假包装。

面对技术快速迭代带来的挑战,有专业投资机构在谨慎应对。已投资部分具身企业的辰韬资本合伙人萧依婷向蓝鲸科技记者透露:“我们投资团队包括MIT的博士、牛津的博士等。市场化的GP主要就是靠专业吃饭,所以前台都是理工科博士。”

在萧依婷看来,专业投资人必须具备过硬的技术鉴别能力。“专业投资人是不会被骗的,被骗的投资人就是功课没做足。”她直言,“当然技术好,也有成功和失败,但专业判断是投资的前提。”

“当前具身智能企业确实存在滥竽充数,”萧依婷表示,“我们有时候看了100个项目才投1-2个。”

不过,投资行为往往有时也关乎预算逻辑。深圳某投资经理就向蓝鲸科技记者透露,为用完当年额度、维持来年预算,即使项目存疑也可能投资。“既然某些基金核心收入是管理费,且风险本就预期之内,那么亏损也就成了‘合规的常态’。”

注:文/翟智超,文章来源:蓝鲸新闻,本文为作者独立观点,不代表亿邦动力立场。

文章来源:蓝鲸新闻

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