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Industry participants: Embodied AI startups raise funds every 1-2 months, far outpacing commercialization
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The embodied intelligence (embodied AI) sector is experiencing an extremely rapid fundraising cycle, with startups closing funding rounds every one to two months and valuations doubling between rounds, according to industry participants at a recent event hosted by Shanghai Future Industry Fund. LuoBo Party founder Huang Yi noted his company has completed five rounds totaling over $100 million. However, this pace far outstrips commercial progress, with few large-scale deployments or real orders. Lenovo Capital's Liu Ruochuan acknowledged that commercial closure and landing lag behind, requiring efforts across the entire supply chain. Shanghai Jiao Tong University's Zhang Zhipeng argued that neither hardware (stable long-term operation) nor application scenarios (warehousing, delivery, home) are ready for mass adoption. He criticized many of the roughly 400 companies for chasing buzzwords like VLA, world models, and RSI rather than deepening technology. Huang Yi advised founders to be disciplined, focus on selling products to generate cash flow, and avoid wasteful spending on models just because funding is abundant. The discussion also questioned whether capital alone can build a sustainable moat, with Liu noting that the mobile internet era showed both successes and failures from heavy capital investment. Lochpine's Qi Lin viewed capital and technology as mutually reinforcing rather than one dominating.
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Rapid-Fire Funding Rounds
In the embodied intelligence sector over the past two years, startups have been closing funding rounds every one to two months, with valuations changing month by month. This stands in stark contrast to the limited progress in large-scale deployment and real commercial orders.
For entrepreneurs, raising as much capital as possible while the capital market is hot is the optimal strategy. But for investors, the question arises: has the bar for investment become too high? And when fundraising significantly outpaces commercialization, is the current funding pace healthy?
These topics were discussed by industry insiders at the "What's Next Dialogue" Physical AI special event, recently co-hosted by the Shanghai Future Industry Fund and Shanghai Future Qidian Community.
"Startups are basically closing a funding round every one to two months, and the valuation for the next round typically increases by one to two times," said Huang Yi, founder and CEO of RoboParty. He revealed that RoboParty has completed five funding rounds, raising over $100 million in total.
The acceleration is felt not only by entrepreneurs but also by investors. Liu Ruochuan, Executive Director and Head of Investment Division II at Lenovo Capital, observed that the embodied intelligence sector is clearly overheated from a capital perspective. "Some companies achieve valuations of hundreds of millions of dollars shortly after being founded. For example, world models—whether from new companies, established ones, or even hardware companies—everyone is talking about world models. Besides the concept itself being grand, it's also because it's a current hotspot for capital."
Zhang Zhipeng, Associate Professor at the School of Artificial Intelligence, Shanghai Jiao Tong University, believes the overall pace of industry fundraising has already moderated somewhat. "The pace from mid-last year to mid-this year was somewhat abnormal."
Technology iteration is also accelerating. "A proposal made three months ago may already be outdated now," Liu Ruochuan said. Huang Yi agreed, noting that the brightest minds are all in the embodied intelligence sector. "Plans can be overturned by the industry in less than three months. It's not uncommon for shareholders to ask daily about product milestones and releases, which puts a lot of pressure on founders."
Commercialization Lags Behind
Against the backdrop of faster fundraising and accelerated technology iteration, how is commercialization progressing?
Liu Ruochuan admitted that the industry's commercial闭环 and deployment are relatively lagging. "This requires efforts across the entire industrial chain—not just tech companies and entrepreneurs on the main track, but also upstream and downstream ecosystems, as well as capital."
"Looking at past industry cycles, it's very normal to go through several ups and downs," Liu added. "The market needs to have reasonable expectations."
Zhang Zhipeng pointed out that neither the hardware nor the application scenarios for embodied intelligence are ready. "For hardware, it's hard to find a platform that can operate stably over the long term. For scenarios—whether express delivery, front-end warehouses, or households—it's still unclear which one can achieve large-scale, stable deployment within a few years. We're still in the exploration, trial, and competition phase."
He believes that the number of companies meeting expectations is not that large. "There are about 400 embodied intelligence companies, but the number truly committed to deep tech development may be smaller than imagined. Many companies focus more on marketing around trending keywords—from VLA (Vision-Language-Action models) to world models, and now to RSI (Recursive Self-Improvement)—without actually delving deep into the technology."
When there is a mismatch between fundraising pace and commercialization progress, how should entrepreneurs balance product development and ecosystem investment?
Huang Yi's answer: calculate how many years the cash on hand can last. "There's no need to be like some embodied intelligence 'brain' companies that raised three to four billion but only spent one to two hundred million. That's a waste of resources and doesn't help drive industry development."
In his view, a key quality for a founder is restraint—knowing what to do and what not to do. That makes the best founder. He plans to focus his main efforts over the next three years on "selling robots, selling hardware." "A company's commercialization path must generate its own cash flow. Just because you've raised a lot of money doesn't mean you can spend recklessly on models. That's irrational."
Can Capital Build a Moat?
Capital is also changing the rules of the game. Currently, funding is concentrating among "head" companies—but this "head" status may be defined by valuation rather than technology or product leadership. Some investors believe that valuation-leading companies have raised enough money, have strong cash reserves, and are safe enough—at least unlikely to fail.
Liu Ruochuan commented that the market should neither underestimate nor mythologize the power of capital. "We need to view it objectively and rationally. Whether capital alone can build a moat—the mobile internet era over the past decade has given us a clear answer. There are classic examples where capital successfully burned through to create platform value, and there are also cases where heavy capital bets ended in nothing."
"Shifting to the hard-tech track, we've seen capital concentration emerge over the past seven to eight years. Frankly speaking, when we evaluate projects, fundraising ability may be one dimension to consider, but it is by no means the only one," Liu said.
Qi Lin, Executive Director at Lochpine Capital, offered another perspective: "Technology is still advancing, and the embodied model track is undergoing continuous iteration. Capital is also driving the market forward. The two are mutually reinforcing—there is no dominance by either side."
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China’s embodied AI startups raise funds every 1-2 months, far outpacing commercial deployment