Will the Wave of Robot Company IPOs Produce the Next Tesla?

Will the Wave of Robot Company IPOs Produce the Next Tesla?

Embodied Intelligence: China’s New National Strategy in 2025

image

Source | Phoenix Finance (finance_ifeng)

Image source | Midjourney

From Iron Man–style test flights, to robots picking tea leaves, to elderly care robots assisting mobility, sci-fi is fast becoming reality. In China’s 2025 Government Work Report, “embodied intelligence” is named as a national strategy for the first time — hitting fast‑forward on a technological revolution.

image

(Yunqi Town, Hangzhou, West Lake District — test flight pilot in gear reminiscent of Iron Man. Image: Hangzhou Zhi Yuan Research Institute)

---

Mass Production Meets Capital Frenzy

2025 is being called the first year of mass production for embodied intelligence:

  • Big moves by unicorns:
  • Zhi Yuan Robotics completed share restructuring.
  • Unitree Robotics began IPO counseling.
  • Over a dozen firms are rushing to list.
  • Internet giants join in: JD.com, Tencent, and Alibaba are acquiring into the sector, raising barriers for new entrants.

Reality check: Behind the exuberance, many star firms are still losing money. Capital excitement meets commercialization anxiety — defining the real state of the industry.

image

---

Capital’s “Blazing Oil Feast”: Losses Across the Board

The 2025 spotlight: XPeng’s humanoid robot IRON and Elon Musk’s endorsement fueled investors’ frenzy.

Yet financial filings tell a sobering story.

Loss‑making IPO hopefuls in 2024:

  • Geek+
  • Yunji Technology
  • Ufactory
  • Stand Robotics
  • Mega Robotics
  • Woan Robotics
  • Ledong Robotics

Even UBTECH — dubbed “first humanoid robot stock” — posted 1.305B RMB revenue, but 1.124B RMB net loss in 2024.

Other examples:

  • Mega Robotics: Revenue doubled in 2 years (455M → 930M RMB), but annual net losses stayed at 700–800M RMB.
  • Stand Robotics: 251M revenue in 2024, yet 273M RMB losses across 3 years.
  • Ledong Robotics: >40% CAGR, 467M revenue, still lost 56.48M RMB.
  • Woan Robotics: 610M revenue peak, but 3.07M RMB annual loss; over 100M RMB cumulative loss.

Why so unprofitable?

  • High R&D intensity:
  • Stand Robotics spends >18% of revenue on R&D.
  • UBTECH invests ~40% annually into R&D.
  • Long cycles, high investment, and slow adoption curves.

Bright spots:

  • Unitree Robotics: ~100M RMB net profit in 2024.
  • Boombing Robotics: Profitable, but at risk of customer concentration.
image

---

Why the Rush to IPO Despite Losses?

Robots are stepping from lab to living room — but profitability is distant. Many founders view IPOs as a way to secure:

  • Long‑term funding
  • Strategic market positioning
  • Ecosystem advantage (over short‑term profits)

They’re also constrained by investment terms:

  • IPO or buyback within 5 years
  • Founders face joint liability & unlimited personal guarantees — risking personal assets if targets aren’t met.

Investor Reality Check

  • Current “robotics era” profit turning point is still ~3 years away.
  • “One robot per household” could take a decade.
image

---

Policy & Capital Connectivity: The Hong Kong Chapter 18C Effect

Hong Kong’s Chapter 18C allows non-profitable tech companies to go public, offering:

  • International capital access
  • Relief from dwindling RMB-based financing

In 2025, embodied intelligence entered the national strategic priority list, spurring local policy support and fueling the IPO wave.

Yang, a partner in GEIA — Global Embodied Intelligence Accelerator, predicts:

  • Faster track evolution & iteration
  • Bubble squeeze‑out and resource concentration in top‑tier firms
image

---

From Blue Ocean to Red Ocean

Demand is booming — and competition is intensifying:

  • Mid‑to‑low‑end price wars: ¥80k–¥100k vs high‑end ¥250k models.
  • Supply chain risks:
  • Stand Robotics suffered component shortages in 2022, halting production.
  • Humanoid robot components (servos, reduction gears, controllers) = >70% of costs.

Market Challenges

  • Overheated investment → low-quality projects get funded.
  • “Marionette show” demos in pitches.
  • Commercialization needs real-world data, but most robots are still in demo stage.

---

Strategic Recommendations from Yang

  • Reverse product development: Start with exact application needs, then build tech.
  • Feasible entry points:
  • Consumer companionship & entertainment
  • Industrial/service niches
  • Upgrade traditional robotics with embodied intelligence — driving M&A.

Favorite picks:

  • Unitree Robotics → product prowess
  • Zhiyuan Robotics → strong ecosystem-building
image

---

AI Tools as Strategic Allies

Platforms like AiToEarn官网 provide open‑source global AI content monetization — integrating:

  • AI content generation
  • Multi‑platform publishing (Douyin, Kwai, WeChat, Bilibili, Rednote, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, X)
  • Analytics & model ranking (AI模型排名)

Such tools mirror the interconnected thinking embodied intelligence companies need — combining creation, distribution, and storytelling to accelerate adoption.

---

Capital Wager: Next Tesla or Next Bubble?

Tesla took a decade of losses before profitability.

Now, embodied intelligence IPOs are betting on the next trillion‑yuan market.

Final Test:

The firm that crosses break‑even first with a scalable, replicable business model will claim the “ticket to the future.”

---

In short:

Embodied intelligence is now a national priority, capital markets are ablaze, but the road to mass‑market adoption is long, costly, and competitive. Those who master innovation + commercialization + communication will lead — others risk burning out before the robots arrive in every home.

Read more

Translate the following blog post title into English, concise and natural. Return plain text only without quotes. 哈佛大学 R 编程课程介绍

Harvard CS50: Introduction to Programming with R Harvard University offers exceptional beginner-friendly computer science courses. We’re excited to announce the release of Harvard CS50’s Introduction to Programming in R, a powerful language widely used for statistical computing, data science, and graphics. This course was developed by Carter Zenke.