Investors are eyeing these five post-2000s individuals.
Gen Z "Embodied Geniuses" have almost become the hottest presence in the current venture capital circle. Several embodied companies led by Gen Z have recently completed multiple rounds of financing in quick succession.
Nijuzhen Technology announced the completion of its first-round financing of over ten million US dollars, jointly invested by Hillhouse Capital and Peking University-affiliated fund Yanyuan Venture Capital. OriginFlow has successively completed angel round, strategic round, and Pre-A1 round of financing, with a cumulative financing amount exceeding 500 million yuan. Institutions such as BlueRun Ventures, Oasis Capital, 58 Strategic Investment, Monolith Capital, and Yuanhe Puhua have intensively placed bets.
Almost at the same time, RoboParty and LiberAI also completed their financing. The former completed tens of millions of US dollars in angel + round financing, led by Shunwei Capital, with additional investment from Xiaomi Strategic Investment. LiberAI secured nearly 500 million yuan in angel + round financing, backed by leading institutions such as Sequoia China, ZhenFund, Meituan Longzhu, and Shunwei Capital.
Lingchu Intelligence completed its financing earlier. In April, the company completed a new round of financing, invested by SDIC Leading and Jingxi Ruiling. Just a month ago, it announced the completion of a total of 2 billion yuan in angel round and Pre-A round financing, led by Xuhui Capital with Shanghai state-owned background, and many old shareholders oversubscribed.
As we understand, one of the embodied companies has recently completed a new round of luxurious financing.
In the past year, I've written several stories about Gen Z in the venture capital circle, such as AI prodigies and Gen Z investors. The tech circle always chases after the young and new trends, but the pace of change is a bit too fast. A year ago, these young people were not the protagonists in the embodied track. Whether it's making the robot body, the brain, or core components, most of the active front-line entrepreneurs were those born in the 1980s and 1990s. Some were university scholars who started businesses, some had long been deeply involved in the industrial mass production system, and some had been in the robot industry for many years before finally waiting for the technological window.
This year, capital has started to shine the spotlight on the younger generation.
Some investors believe that this is the era opportunity for the "Embodied Natives". Compared with the previous generation of robot entrepreneurs, the biggest feature of Gen Z is that they have almost naturally grown up in the context of AI. They have a more intuitive understanding of large models, world models, and multimodal interactions, and are more likely to accept the path of "robots first gain intelligence and then supplement engineering".
A young entrepreneur once told us that he missed the wave of large language models and also the first wave of embodied intelligence. The explosion of world models, end-to-end control, and robot intelligence has finally allowed them to stand at the center of the table for the first time. He's not sure if there will be such an opportunity in the future.
From another perspective, capital isn't suddenly "favoring the young". Instead, the primary market is entering a stage of "scarcity of good projects". As truly imaginative and scarce projects become fewer, the competition among institutions quickly shifts from "selecting projects" to "scrambling for founders".
There is no era for prodigies, only prodigies of the era.
Have a chat in the morning, issue a TS in the afternoon
Compared with the bustling scene of hundreds of companies in the entire embodied intelligence track, the number of truly "embodied prodigy" startup projects isn't that large.
As we understand, if we limit the scope to projects led by Gen Z and have received intensive bets from leading institutions, the current market targets are mainly concentrated in several companies: OriginFlow, LiberAI, RoboParty, Nijuzhen Technology, and Lingchu Intelligence.
These projects have almost been hunted by leading capital since their birth and completed financing in a very short time.
OriginFlow was founded in August 2025 by Qin Shentao, a Gen Z doctoral student at Tsinghua University. The cumulative financing amount has exceeded 500 million yuan within less than a year of its establishment. This company has rapidly completed multiple rounds of financing in a "serial financing" rhythm. The angel round was jointly led by BlueRun Ventures and Oasis Capital. Subsequently, in the strategic round, industrial and alumni-based capitals such as 58 Strategic Investment, Puhua Capital, and Shuimu Tsinghua Seed Alumni Fund were introduced. In the Pre-A1 round, Monolith Capital led the investment alone, and institutions such as Yuanhe Puhua, Yuanhe Origin, and Guofang Venture Capital continued to follow up.
An investor recalled that when first contacting OriginFlow, after chatting in the morning, a meeting with partners was directly arranged at noon. By the afternoon, the institution had completed its decision-making internally and quickly issued a TS (Term Sheet).
The situation is similar for LiberAI and RoboParty.
LiberAI was founded in 2025 and has successively completed seed round, angel round, and angel + round financing, with a cumulative financing amount approaching 500 million yuan, jointly invested by leading institutions such as ZhenFund, Sequoia China, Meituan Longzhu, and Shunwei Capital.
RoboParty completed multiple rounds of financing in less than two months. In November 2025, the company completed nearly ten million US dollars in seed round financing, led by Xiaomi Strategic Investment and Matrix Partners China. A month later, it quickly completed the seed + round financing, and the investors further expanded to institutions such as Guoxiang Capital, Huaying Capital, and BV Baidu Ventures. Subsequently, its tens of millions of US dollars in angel + round financing was led by Shunwei Capital, with additional investment from Xiaomi Strategic Investment.
Huang Yi, the founder and CEO of RoboParty, is one of the youngest entrepreneurs in the humanoid robot industry. After entering Harbin Institute of Technology in 2023, he developed the bipedal humanoid robot AlexBot series during his undergraduate years and made it fully open-source. The relevant projects have been replicated and applied by more than a dozen enterprises and universities. His team's GitHub has accumulated more than 4,000 stars, and the document views have exceeded 200,000. In March 2025, Huang Yi graduated from undergraduate one year ahead of schedule and founded RoboParty, focusing on fully open-source bipedal humanoid robots.
Nijuzhen Technology completed its first-round financing of over ten million US dollars in March this year, jointly invested by Hillhouse Capital and Peking University-affiliated fund Yanyuan Venture Capital. Also in March, Lingchu Intelligence first publicly disclosed its past financing progress, successively completing the angel round and Pre-A round of financing, with a cumulative amount of 2 billion yuan. The angel round investors included "national team" such as China Development Financial and Zhiyuan Robotics, etc. The Pre-A round was led by local state-owned assets such as Xuhui Capital and market-oriented funds. In April, it publicly disclosed the completion of the A round of financing, jointly invested by SDIC Leading and Jingxi Ruiling.
From prestigious backgrounds
Upon closer inspection, it can be found that these so-called "embodied prodigies" didn't suddenly appear out of nowhere. Most of them are "from prestigious backgrounds" and have studied under well-known doctoral supervisors and professors in the field of robotics.
Qin Shentao, the founder and CEO of OriginFlow, studied under Academician Li Keqiang of the School of Vehicle and Mobility at Tsinghua University. He graduated from the robotics major at Harbin Institute of Technology as an undergraduate, studying under Academician Deng Zongquan.
Liu Songming, the founder of LiberAI, studied under Zhu Jun, an expert in the field of machine learning at Tsinghua University, and has published several top conference papers. Co-founder Lin Fanqi studied under Gao Yang, an assistant professor at the Institute for Interdisciplinary Information Sciences at Tsinghua University and co-founder of Qianxun Intelligence.
The two core founders of Nijuzhen, Ji Jiaming and Chen Boyuan, were born in 1998 and 2004 respectively, and are from the School of Intelligence, Institute of Artificial Intelligence, and Yuanpei College at Peking University. Among them, Ji Jiaming studied under Assistant Professor Yang Yaodong of the Institute of Artificial Intelligence at Peking University. Another student of Yang Yaodong, Chen Peiyuan, is one of the co-founders of Lingchu Intelligence. The latter studied under Professors Karen Liu and Fei-Fei Li during his visit to Stanford University and was the first to use reinforcement learning to control both arms and hands simultaneously to complete multi-skill operations in the real world.
Different from the other "student teams", Lingchu Intelligence is a typical combination of "industry veterans + young geniuses". Founder Wang Qibin has nearly 20 years of industrial experience in the fields of mobile phones, smart speakers, and robots, and has completed the closed-loop of product development from 0 to 1 and then to global mass production multiple times. The young technical team represented by Chen Peiyuan is responsible for cutting-edge algorithms and technological breakthroughs.
In the view of Li Jun, the general manager and managing partner of Peking University-affiliated fund Yanyuan Venture Capital, this is exactly the relatively ideal organizational structure in the current field of embodied intelligence: the young are responsible for innovation and technological exploration, while the mature industrial team is responsible for organization management, supply chain, and commercialization. Only by combining the two can the technology in the laboratory be truly brought to real-world scenarios.
In the past few years, Li Jun has invested in many Peking University-affiliated embodied intelligence and world model projects, including Galaxy Universal, Lingchu Intelligence, Nijuzhen, Zhizai Wujie, and Frontier Huichuang. He believes that many of the current star projects are actually labeled and defined after the fact. Whether a startup can succeed has no necessary connection with the age of the team, and age itself is also a "label".
Besides technology, what really matters is whether the founder has the determination and unique entrepreneurial spirit for starting a business. All things ultimately come down to "people". "If they have this kind of spirit, we will firmly invest in them whether they are young or middle-aged. Among the projects we've invested in, the founding teams include those born in the 1970s, 1980s, 1990s, and 2000s, including serial entrepreneurs in the industry and student representatives of Peking University's annual figures." This is Li Jun's view.
"A few geniuses + a team" to create a world model
Compared with the commercialization ability of industrial entrepreneurs, technological innovation is undoubtedly the greatest advantage of young entrepreneurs. At a stage when the technological route of embodied intelligence has not yet converged, young people have every reason to seize such an opportunity.
In the past year, both at home and abroad, the most mainstream financing narrative in embodied intelligence has almost revolved around VLA. Its core logic is to enable robots to understand visual information in the same way that large models understand language and directly output actions. Many companies hope to build the general action ability of robots through the combination of "large models + robots".
Compared with the previous stage that relied on VLA for end-to-end action generation, the "embodied 2.0" concept that has been most discussed in the industry this year emphasizes Physical AI and World Model. From a business perspective, most of the startup projects of these "embodied prodigies" are also concentrated in this area.
Rather than directly producing terminal robot products, they focus more on the construction of the underlying capabilities of embodied intelligence, including physical world models, robot data collection, reinforcement learning training platforms, operational data closed-loops, and infrastructure related to world models.
Sue, an investor from a leading US dollar fund and also a Gen Z investor, has a different judgment on this wave of embodied intelligence entrepreneurs compared to many traditional VCs. In her view, the truly breakthrough things in this round may not come from those who understand the industry best, but rather from the youngest and most cutting-edge researchers.
There are actually "two generations of entrepreneurs" in the robot industry now. The first generation consists of people with traditional robotics backgrounds, such as those involved in motion control, hardware, automation, and robot body manufacturing. They have experienced the accumulation of the robot industry in the past decade, have industrial and engineering experience, and will naturally follow the past data pipelines, engineering paradigms, and delivery logics, but may not be willing to redefine robots themselves.
"Mass production isn't the biggest outcome. The real big outcome is who can define the next-generation robot paradigm." Sue believes that there is a problem in the current robot industry. Although the first wave of companies have raised a lot of money, they often "lack the ability for technological breakthroughs".
They are too likely to follow the old paradigm and mostly follow the past technological routes. "Mature entrepreneurs will subconsciously turn unknown problems into known problems." She said that experience is valuable, but it can also create inertia. Especially when there is a large technological generational difference, old experience may even become a constraint. And many of those who truly try to break the paradigm are front-line researchers.
Sue's way of screening people is also very "research-oriented". She has long been concerned about who did the core work in top conferences and best papers. "I'm not very optimistic about building the robot body first and then developing the algorithms." She believes that the embodied industry has not yet formed a unified standard. The configurations, hardware, and degrees of freedom of different manufacturers are completely different. In this case, if the algorithms are not finalized, it's actually difficult to truly finalize the robot body. In her view, there should be data, models, and world understanding first, and then the robot body design can be deduced.
Most of the "prodigies" come from these front-line researchers. Many of them have backgrounds in AI, CV, or machine learning, and they are thinking about how to encode tactile data, how to incorporate force data into models, and how robots can form world understanding.
In the AI era, there often occurs the situation where "one paper changes the entire industry". In the future, there may also be a situation in the robot field where "a few geniuses + a team" create a general world model.
Prodigies of the era
"There will definitely be new species in the new era, and new species will bring new people. Each generation has its own opportunities and missions. The sense of destiny and resonance with the era will create a group of young entrepreneurs." Li Jun believes that this is one of the reasons why Generation Z is being pursued by VCs at present.
"Do many investors actually not understand the technology and can only judge based on the people?" Li Jun didn't avoid this question. He admitted that there must be irrational emotions in the market, and the fear of "missing out" is prevalent at present. However, since the underlying technologies of embodied intelligence and world models are still developing and have not converged, it's a luxury to expect everyone to fully understand the technology. Even "top scientists can hardly see the end at a glance".
So, most of the time, apart from technology, what investment institutions can grasp are some characteristics of the founders, such as learning ability, cognitive iteration ability, organizational ability, etc., as well as a unique entrepreneurial spirit that's hard to describe. There are no two "identical leaves" in this world. Investment itself is a reflection of the investor's inner world.
This actually reveals a very delicate reality in the current primary market. Most of the time, institutions are betting not on a proven business model, but on the possibility of a founder's future evolution. Especially in long-term tracks like embodied intelligence and world models, where the technological route is constantly changing, it's important for the founding team to be able to bind with top universities like Peking University, which are the sources of scientific and technological innovation, and continuously upgrade and iterate the technology. It's also crucial for the founder to have the ability to continuously evolve and self-correct.
From another perspective, capital isn't suddenly "favoring the young". Instead, the primary market is entering a stage of "scarcity of good projects". As truly imaginative and scarce projects become fewer, the competition among institutions quickly shifts from "selecting projects" to "scrambling for founders". Similar phenomena have actually occurred in the past eras of the Internet, new consumption, and SaaS. It's just that in this round, a group of young technology entrepreneurs have been pushed to the forefront.
"VCs currying favor with the young" isn't the cause but the result. An investor half-jokingly told me, "When you can't compete with others in terms of resources, brand, and relationships, you can only provide emotional value." So, chatting, supporting, scrambling for shares, and making quick decisions have gradually become part of the competition in the primary market.
Therefore, this craze about "embodied prodigies" may have a dual nature. It's both a reward for the young in the new technological cycle and a reflection of the current primary market's anxiety about scarce projects.
The narrative of young entrepreneurs isn't entirely romantic technological idealism. Li Jun is particularly willing to believe and see young entrepreneurs create and define an original basic model architecture in the field of physical AI, while also having the ability to disassemble tasks and implement engineering scenarios. He repeatedly emphasizes, "We should both look up at the stars and keep our feet on the ground."
In his view, this round of investment in embodied intelligence and world models is essentially an investment in "future possibilities". Since the industry pattern is still undetermined, the technology has not fully converged, and the commercialization space has not been fully opened up, the valuation of some projects can't be simply measured by revenue, profit, or orders. What VCs are really betting on is whether these young teams have the opportunity to grow into the