给宇树甩了两张工牌

marsbit2026-06-02 tarihinde yayınlandı2026-06-02 tarihinde güncellendi

Özet

英伟达在台北发布了人形机器人Isaac GR00T参考设计,由宇树科技提供身体、Sharpa提供灵巧手、英伟达提供Jetson Thor芯片及全套软件栈。这套“交钥匙”方案旨在服务高校及研究人员,可将实验准备时间从几天缩短到几小时,其合成数据生成能力极强。同日,宇树科技A股首发过会,估值420亿,但其募资的最大投向是自研具身大模型(大脑)。 文章指出,英伟达的参考设计模式与当年高通在手机行业的“交钥匙”方案类似,可能通过开源模型和软件来锁定其硬件生态,从而掌握行业规则制定权,将利润集中于“大脑”环节。宇树科技虽为参考设计供应身体,却同时大力投资自研大脑,并已在其G1机器人上同时运行英伟达GR00T、自研UnifoLM及第三方中科第五纪模型,这被视作一场“穿着合作外衣的独立战争”。 目前,仅特斯拉凭借其FSD数据飞轮、自研芯片和超级制造体系,在机器人领域实现了完全脱离英伟达的闭环。文章认为,机器人的身体(运动控制、灵巧操作等)目前仍有较高的技术门槛和差异化空间,未像手机硬件那样完全同质化。宇树押注自研大脑,是在与时间赛跑,窗口期可能只有两三年。若其自研大脑成功,则能掌握主动权;若失败,则可能面临被标准化方案锁定在低利润“身体制造商”位置的风险。

黄仁勋在台北流行音乐中心的演讲,到了最后压轴环节。结果上台是一台机器人。

不知道从什么时候开始,大家管机器人叫「植物人」。可能,因为它还不够灵活吧,这么说好像也没错。

01

你看看黄仁勋怎么介绍这台机器人的,身高1.8米,体重68公斤,全身75个自由度;他在台上开了个玩笑,说这个身高体重「跟我差不多」。挺有意思的。

这台机器人叫Isaac GR00T,英伟达官方给的定义是参考设计,三个供应商各管一块。

身体来自宇树科技的H2 Plus,手来自新加坡Sharpa的五指灵巧手,大脑是英伟达自己的Jetson Thor芯片,加上全套Isaac GR00T软件栈。

我注意到一个细节:

英子说,这套参考设计的目标用户,是高等教育机构和大学研究人员;首批客户包括斯坦福和苏黎世联邦理工。

配套的开发平台和模型代码,马上会放到GitHub和Hugging Face上;全套软件栈开箱即用,研究团队的准备时间从几天缩短到几小时。

换句话说,英伟达做的不只一台机器人。

它是一个交钥匙工程;身体、大脑、数据生成工具、训练框架、仿真环境,全给你打包好了,你只需要接上电源,就能开始做实验。

我去查了一下他们的数据生成能力。

英子说了,用Cosmos 3和Isaac GR00T Blueprint,11个小时可以生成78万条合成运动轨迹。78万条什么概念?相当于6500小时的人类示范数据;差不多就是一个工程师连续不停地教机器人动作,教9个月。

然后,今天下午,上交所上市审核委员会公布了结果,宇树科技首发过会,符合发行条件。

73天,从受理到过会,募资42.02亿,整体估值420亿。A股人形机器人第一股,锁定了,这一前一后的,我都想用双喜临门来形容。

但有一个细节值得注意,

黄仁勋的演讲里,宇树的名字出现在身体那一栏。Sharpa出现在手那一栏;英伟达自己占据大脑、算力、模型、仿真、数据生成这一整段。

而下午,上海那场审议里,宇树拿到了420亿估值。招股书上写得明明白白,募资里最大的一笔投向,是具身大模型。是大脑。

英伟达说你是我的身体,同一天,宇树说我要造自己的大脑。怎么回事?

02

我想了一个词,参考设计。这个词挺中性的,就像一份技术文档,一套方案,你参考一下。

科技圈里这个词出现过很多次了,每次出来,后面的剧情都差不多。

最有代表性的一次,在手机行业。

2010年前后,高通开始做一件事。它把骁龙芯片、基带、安卓系统、驱动层、硬件接口这些全部打包在一起,变成一套完整的手机参考设计。

行业里叫turnkey,翻译过来就是交钥匙。

什么意思呢?你是一家手机品牌商,不用自己有芯片设计能力、系统调试能力,也不用养硬件研发团队。拿着高通这套方案,找一家ODM工厂,改改外壳,贴上自己的logo,一台手机就出来了。

红米第一代就是这么来的。当年,小米找闻泰代工,用的就是高通方案,那一年,闻泰出货了6550万台。

听起来多赢,高通卖了芯片,品牌商省了研发,ODM工厂吃到了订单。

然后我去查了一下后面的事。

华勤技术,中国最大的手机ODM公司,2024年前三季度营收超过700亿,归母净利润20亿。龙旗科技,营收350亿,净利润不到5亿。

700亿营收,20亿利润,净利润率不到3%。

这几家公司的手机代工毛利率,长期在5%到11%之间打转。行业里的人管这个叫辛苦钱;上面被芯片商压着,下面被品牌商比价,中间被同行卷着。越做越大,越做越薄。

闻泰科技,曾经的ODM出货冠军,2025年初做了一件事,把整个ODM业务卖给了立讯精密,彻底退出手机代工;卖掉之后全面转向半导体,它的半导体业务毛利率37.47%,是手机代工的七倍多。

你看,做身体做到全球第一,最后选择不做了。

这个故事跟今天有什么关系?我把高通当年和英伟达今天做的事情放在一起看了看。

高通出了芯片加安卓加参考设计,手机行业里所有人都用了。结果呢?硬件变得千机一面,利润从品牌商和制造商手里,慢慢流到了芯片商、操作系统商手里。

英伟达今天出了Jetson Thor芯片加Isaac GR00T模型加参考设计。模型代码全部开源,仿真框架也开源了,数据生成工具也打包好了。

我去看了英伟达现在的合作名单,宇树在用Jetson Thor,智元、银河通用、优必选都在用。甚至Figure AI在用,波士顿动力在用,亚马逊和Meta也在用。

宇树是十几个身体供应商之一。

英伟达的机器人部门VP说过一句话,原话是:我们不生产机器人,也不制造汽车;我们通过基础设施计算机和软件,为整个行业提供技术支持。

这句话,高通十五年前说过一个几乎一模一样的版本。

当一家公司说:我们不做终端产品,只提供平台和工具时,它其实在宣布一件事:规则我来定。

GR00T模型开源,和当年谷歌把安卓开源,同一个逻辑。软件免费给你,为了让你离不开我的硬件。用了我的模型、仿真平台,就要跑在我的芯片上。

我的看法是这样的:

参考设计,像一份权力分配协议,谁发参考设计,谁就在定义这个行业里大脑值多少钱,身体值多少钱。

手机行业已经回答过一次了,做身体的公司,700亿营收,利润率不到3%;做大脑的公司,一年光专利授权费就能收几百亿美金,现在,巧了,机器人行业拿到了同样的协议。

03

我去翻了宇树的招股书。42亿募资里,20.22亿要投到智能机器人模型研发上,占了48%,是所有项目里最大的一笔;11.1亿投本体研发,4.45亿投新产品,6.24亿建制造基地。

砸钱最多的地方,是大脑。宇树肯定知道这个局。

王兴兴说过一句话,大意是过去十年犯的最大错误,就是低估了AI的技术进步,他原来的团队重心一直放在本体和运动控制上,直到最近两年才开始往具身大模型上加码。

一边给英伟达的参考设计供应身体,一边拿20亿去造自己的大脑。这是穿着合作外衣的独立战争。

我查了一下细节,英伟达的GR00T N1.5,已经在宇树G1机器人上跑通了;开源社区的开发者拿着代码,直接在G1上做了部署和操作任务演示。GitHub上有完整的部署教程。

也就是说,英子的大脑,已经装进了宇树的身体里。而且是公开的,任何人都能复制这个过程。

那宇树自己在做什么呢?

2025年9月,宇树开源了自研的世界模型UnifoLM-WMA-0。2026年1月,又发了视觉语言动作模型UnifoLM-VLA-0。

到了5月25号,就是上会公告发布那天,宇树测试发布了WVLA2.0具身大模型,让G1机器人在有人走动干扰的复杂环境下,独立完成了会议室物品整理和分类收纳,没有任何远程操控。

两套大脑,跑在同一个身体上,一套是英伟达的,开源的,全世界都能用,一套是宇树自己的,刚起步,还在追。你让我怎么形容?

这里还有一个角色值得关注。

我查到一家公司叫中科第五纪,2024年9月才成立,核心团队来自中科院和清华;今年连拿三轮融资,红杉中国领投了Pre-A轮,最新的A轮由孚腾资本和上海半导体产投投的。

它的身份是宇树科技001号具身操作大脑供应商。

双方基于宇树G1人形机器人平台,在电力行业做了软硬一体化解决方案;中科第五纪同时也在和美的合作,它的机器人已经进入美的佛山工厂的产线实际运作了。

你发现问题了吗?

宇树身体上跑着的大脑,不只两副,有三副。英伟达的GR00T,宇树自研的UnifoLM,还有中科第五纪的FAM系列模型。

为什么一个做身体的公司,要同时对接三套大脑?因为它还没有自己的。

宇树2025年的研发费用率是8.53%,1.45亿;同行优必选是25%,5.07亿。宇树是行业头部里研发投入占比最低的公司之一。

这20亿,是补课的钱。问题是,补课有窗口期。

英伟达的GR00T是开源的,迭代速度很快。N1到N1.5只隔了不到三个月,只要GR00T够好用,越来越多的开发者和客户就会默认选它。

就像安卓当年铺开之后,你再去做一个自己的手机操作系统,不是不可以,是越来越难。

宇树现在做的事,相当于一边在安卓手机上装高通芯片出货赚钱,一边在实验室里悄悄做自己的芯片和操作系统。

我相信,两副大脑同时存在的状态不会持续太久,结局无非两种。要么自研大脑追上来了,英子的可以不用;要么追不上,英伟达的变成唯一选择,那宇树就真的只剩身体了。

04

说到这,有个问题绕不过去。有没有人真的不用英伟达的大脑,自己搞定一切?

有,一家。特斯拉。而且目前只有这一家。

Optimus人形机器人用的芯片,是特斯拉自研的FSD芯片,就是它装在车上做自动驾驶那套。

同一套训练管线、数据标注体系、神经网络架构,从车上直接搬过来。连推理硬件都通用,现在跑在HW4上,下一代升级到AI5。

我查了一下最新进展,今年一季度财报电话会上,马斯克确认了几个时间点。

Optimus V3年中发布,7到8月弗里蒙特工厂启动量产。这条产线的前身是Model S和Model X的生产线,5月退产后正在改造成Optimus专用线,目标年产能100万台。

100万台。宇树2025年全年人形机器人出货5500台。

差了180倍。

同时,特斯拉的AI5推理芯片已经完成流片,自研芯片供应体系成型了;这意味着从训练到推理,从云端到机器人端侧,整条链路上没有英伟达的东西。

我认为,特斯拉做到这件事,靠三张牌。

第一张,FSD的数据飞轮。几百万辆特斯拉每天在路上跑,持续回传真实世界的视觉数据。

这些数据用来训练自动驾驶,也在训练机器人的感知和决策,Optimus的团队不需要从零收集机器人数据,因为车的数据可以复用。

第二张,自研芯片。

从Dojo到HW4到AI5,特斯拉一直在做自己的计算架构。虽然Dojo中间波折不少,AI5也刚流片,但方向没变过,它不想把大脑的底层硬件交给别人。

第三张,超级工厂。

特斯拉造过上百万台车的那套制造体系,可以直接用来造机器人;供应链管理、质量控制、产能爬坡,这些不是花钱能快速买到的。

现在回过头看宇树,这三张牌一张都没有。这是不是意味着宇树一定变成闻泰?不一定。

因为宇树有一张特斯拉没有的牌,核心部组件自研自产率超过90%。电机、减速器、控制器,都是自己做的。

四足机器人的运动控制算法从零开发,人形机器人H1立项六个月出成品,全职参与的人只有三个,这说明宇树的身体是有技术含量的。

这里有个关键区别,很多人在做手机和机器人类比的时候忽略了。

手机的物理形态已经趋同了。

一块屏幕,一颗芯片,一块电池,外壳不同而已。硬件上几乎没有差异化空间。所以,芯片商一出参考设计,所有手机长得都一样,品牌商只能拼营销和价格。

机器人不一样,能不能稳稳走路,单脚站住被人踹一脚不倒,用五根手指拧开瓶盖,这些能力到今天,不同公司之间差距非常大。

这意味着,至少在当前阶段,做身体不一定就是死路;身体本身还有溢价空间,还没有被标准化吃掉。

不过,行业里也有新趋势在出现。我注意到一个判断,具身智能芯片的需求,正在从采购标准品走向定制专用SoC。

意思是,将来可能每家机器人公司都会和芯片公司合资做自己的专用芯片;如果这个趋势成立,英子参考设计的锁定效应就会被削弱。

目前,这扇窗还开着,翻过去,是特斯拉。翻不过去,是闻泰,宇树拿20亿去赌的,就是这件事。

窗口不会一直开着,GR00T每迭代一个版本,这扇窗就往下落一点。N1到N1.5,三个月,留给宇树的时间,可能是两三年。

当然,也别太悲观。一些个人调研看法而已。

本文来自微信公众号“王智远”(ID:Z201440),作者:王智远

İlgili Sorular

Q文章中提到黄仁勋在演讲中介绍的机器人Isaac GR00T,其身体部分由哪家公司提供?

A由宇树科技的H2 Plus提供。

Q宇树科技在招股书中计划将募集资金最大的一笔投向哪个领域?

A最大一笔资金投向是具身大模型,即机器人的‘大脑’研发。

Q文章将英伟达的‘参考设计’策略与历史上哪个行业的类似策略进行了类比?

A与2010年前后高通在手机行业推出的‘交钥匙’(turnkey)参考设计策略进行了类比。

Q文章指出,目前唯一一家不依赖英伟达大脑而自行搞定机器人大脑和芯片的公司是哪家?

A是特斯拉。

Q根据文章,宇树科技除了使用英伟达的GR00T模型外,还计划或已经使用了哪些其他‘大脑’?

A除了英伟达的GR00T,宇树还在开发自研的UnifoLM系列模型,并与中科第五纪的FAM系列模型合作。

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The crypto market is in a period of significant debate, with leading institutions offering differing views on whether a bottom has been reached. Three prominent firms have published detailed analyses: * **Galaxy Digital** argues Bitcoin has **not yet bottomed**. Their analysis of 13 historical indicators across six dimensions (valuation, profit-taking, miner pressure, etc.) shows only four are fully met. They project a potential bottom range between $30k and $54k. * **NYDIG** states a bottom is **possible but not likely**. While metrics are close to historic bear market extremes, they note the absence of a classic panic-selling event. They also suggest increased institutional adoption may have structurally altered the market cycle, potentially leading to a shallower downturn. * **Standard Chartered Bank** asserts the **bottom has already occurred** at around $59k. They cite two key factors: potential US-Iran diplomatic progress and the anticipated SpaceX IPO, which they believe absorbed capital and caused ETF selling pressure that is now subsiding. They forecast a year-end price target of $100k. Despite the surface-level disagreement, the reports share critical common ground more valuable for long-term investors: 1. All three believe the market bottom will form **within this year**. 2. All agree the current price is **closer to the bottom than to previous highs**. 3. All maintain a **bullish long-term outlook** for Bitcoin and a new cycle. The core takeaway is that while the exact bottom price ($40k, $50k, or $60k) is debated, the consensus is that a bottom is imminent. For long-term holders, the primary focus should not be pinpointing the absolute low, but on the future potential for prices to reach $100k, $200k, or higher. The fundamental thesis for Bitcoin—sovereign debt accumulation, inflation, declining trust in centralized institutions, global digitization, and improved accessibility—remains intact and is arguably strengthening. The overall landscape is viewed as more favorable than in previous crypto winters.

marsbit28 dk önce

Has the Crypto Market Bottomed? Here's What Institutions Think

marsbit28 dk önce

The 'Chip' Challenge and Breakthroughs in China's Optical Industry Chain

China's Photonics Industry: Bottlenecks and Breakthroughs In the global AI race, computing chips dominate the narrative, but the underlying bottleneck increasingly defining the scale of AI clusters is light—or more specifically, optical connectivity. Optical modules, which translate electrical signals to light and vice versa, are crucial for connecting thousands of GPUs in AI data centers, preventing data congestion and ensuring efficient model training. High-speed modules (800G, 1.6T) are now standard, with performance hinging on advanced DSP (Digital Signal Processor) chips. This is where a critical dependency lies. Two US giants—Marvell and Broadcom—collectively dominate over 90% of the high-end DSP chip market. Chinese optical module leaders like Zhongji Innolight and Eoptolink rely on these chips to manufacture modules for overseas AI customers, primarily in North America. While this creates a supply chain vulnerability, complete decoupling is difficult. Marvell derives over half its revenue from Greater China, and the US firms depend on Chinese partners for chip packaging and optical components. The risk from laser chips (e.g., from Lumentum), another key component, is considered more manageable due to multiple global suppliers and faster progress in domestic alternatives from companies like YOFC and Accelink. To mitigate risks, China's industry is pursuing a multi-pronged strategy: diversifying supply chains and locking in long-term orders; fostering a domestic market ecosystem to adopt homegrown DSPs from firms like Huawei HiSilicon and CETC; accelerating R&D in high-speed DSPs and advanced packaging; and investing in next-gen technologies like silicon photonics and Co-Packaged Optics (CPO) to reduce reliance on discrete DSPs. The ultimate solution lies not in short-term博弈 but in persistent advancement of domestic high-end chip R&D and manufacturing. While challenges remain in performance, certification, and ecosystem building, China's vast domestic market and manufacturing base provide a crucial buffer, buying time for the industry to achieve greater technological independence.

marsbit42 dk önce

The 'Chip' Challenge and Breakthroughs in China's Optical Industry Chain

marsbit42 dk önce

Behind SpaceX's $2 Trillion Market Cap: Why Does Musk Always Have the Next Move Planned?

On June 12th, SpaceX debuted on the Nasdaq, reaching a valuation that briefly touched $2 trillion. This marked the culmination of a 24-year journey from its founding in 2002, driven by Elon Musk's frustration at the high cost of buying rockets. The company's path was defined by early failures, with its first three Falcon 1 launches ending in explosions before a successful 2008 flight opened the era of commercial spaceflight. Key to its model was a fixed-price NASA contract, incentivizing cost reduction. SpaceX mastered rocket reusability, first achieving a Falcon 9 landing in 2015, which drastically cut launch costs. This enabled its profitable Starlink satellite internet constellation, envisioned years before reusability was proven, to create an internal market for frequent launches. Similarly, the next-generation Starship rocket was in development long before its first flight, with its business case evolving from Mars colonization to supporting the emerging concept of in-orbit data centers for AI—a story now central to its valuation. The company's recent IPO, a reversal of its long-standing "no IPO" stance, is funding this ambitious "space-based compute" vision. While major tech players like Google, Blue Origin, and others are investing heavily, significant technical and cost hurdles remain. Ultimately, SpaceX's history is one of creating its own demand: first with Starlink and now with space-based AI compute, betting that its next rocket will enable its next giant market.

marsbit45 dk önce

Behind SpaceX's $2 Trillion Market Cap: Why Does Musk Always Have the Next Move Planned?

marsbit45 dk önce

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HTX.com’a hoş geldiniz! Synfutures (F) satın alma işlemlerini basit ve kullanışlı bir hâle getirdik. Adım adım açıkladığımız rehberimizi takip ederek kripto yolculuğunuza başlayın. 1. Adım: HTX Hesabınızı OluşturunHTX'te ücretsiz bir hesap açmak için e-posta adresinizi veya telefon numaranızı kullanın. Sorunsuzca kaydolun ve tüm özelliklerin kilidini açın. Hesabımı Aç2. Adım: Kripto Satın Al Bölümüne Gidin ve Ödeme Yönteminizi SeçinKredi/Banka Kartı: Visa veya Mastercard'ınızı kullanarak anında Synfutures (F) satın alın.Bakiye: Sorunsuz bir şekilde işlem yapmak için HTX hesap bakiyenizdeki fonları kullanın.Üçüncü Taraflar: Kullanımı kolaylaştırmak için Google Pay ve Apple Pay gibi popüler ödeme yöntemlerini ekledik.P2P: HTX'teki diğer kullanıcılarla doğrudan işlem yapın.Borsa Dışı (OTC): Yatırımcılar için kişiye özel hizmetler ve rekabetçi döviz kurları sunuyoruz.3. Adım: Synfutures (F) Varlıklarınızı SaklayınSynfutures (F) satın aldıktan sonra HTX hesabınızda saklayın. Alternatif olarak, blok zinciri transferi yoluyla başka bir yere gönderebilir veya diğer kripto para birimlerini takas etmek için kullanabilirsiniz.4. Adım: Synfutures (F) Varlıklarınızla İşlem YapınHTX'in spot piyasasında Synfutures (F) ile kolayca işlemler yapın.Hesabınıza erişin, işlem çiftinizi seçin, işlemlerinizi gerçekleştirin ve gerçek zamanlı olarak izleyin. Hem yeni başlayanlar hem de deneyimli yatırımcılar için kullanıcı dostu bir deneyim sunuyoruz.

212 Toplam GörüntülenmeYayınlanma 2024.12.21Güncellenme 2026.06.02

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