Unitree Technology (滬: 688836) made a spectacular debut on its IPO day, opening at RMB 1,100 — a 629% premium to its RMB 150.80 issue price. Early investors who won the lottery saw paper gains exceeding RMB 470,000 per lot. Founder Wang Xingxing's net worth briefly touched RMB 130 billion. But beneath the hype lies a sobering reality: the path to genuine embodied intelligence remains far longer than the market assumes.

Unitree's market debut was nothing short of extraordinary:

The company became a household name after its viral Spring Festival Gala performances — first the Yangge dance in 2025, then martial arts kung fu in 2026. From stiff, robotic movements to fluid acrobatics in just one year, the progress was undeniably impressive.

But here is the cold water: these movements, particularly leg locomotion, were built on foundations laid during the Boston Dynamics era. Jumping, running, falling and recovering — all these algorithms have been available in open-source communities for years. The Spring Festival spectacle was the harvesting of existing research, not a breakthrough.

To understand humanoid robotics, we must first understand embodied intelligence (具身智能). Large language models can describe everything about an apple but cannot pick one up. Industrial robotic arms can perform precise operations but cannot understand a sentence. Embodied AI aims to bridge this gap: a robot with a brain that can, without pre-programmed instructions, turn a vague command into a sequence of physical actions while responding to real-world changes.

Three Components of Embodied AI

Legs: A Solved Problem (Mostly)

Leg locomotion is highly repetitive and predictable. The underlying algorithms were effectively solved by:

• ETH Zurich (2019): Legged locomotion control frameworks
• NVIDIA Isaac Gym (2021): Physics simulation for robot training

The difference between robots today is primarily hardware engineering, not software breakthroughs.

Hands: The Real Bottleneck

Hand manipulation is orders of magnitude more complex:

Hand algorithms are a game against the universe of objects — each task has a unique physical trajectory.

Tendon-Driven (腱驅動)

• Mechanism: High-strength cables replace gears and linkages, mimicking biological muscles and tendons
• Advantages: Inherent elasticity provides shock absorption; safer human interaction
• Disadvantages: Lower payload capacity; cable fatigue and precision degradation over time

Motor-Driven (電機驅動)

• Mechanism: Direct motor actuation with gears and linkages
• Advantages: Higher precision and payload capacity; predictable wear patterns
• Disadvantages: Rigid impact forces; less safe for human proximity

Both approaches are still actively explored. Neither has emerged as the definitive solution for general-purpose manipulation.

Unitree's robots can perform backflips and martial arts. But can they hold a coffee cup steadily? The gap between spectacular demonstrations and reliable utility is where the embodied AI field currently lives.

A robot doing a backflip is a circus act. A robot reliably making coffee is a product.

The challenge is not just hardware — it is the integration of perception, planning, and action in unstructured environments. A backflip requires precise control in a controlled setting. Making coffee requires understanding context, adapting to variation, and recovering from unexpected events.

Unitree's IPO pop reflects investor enthusiasm for robotics, not the maturity of embodied AI. The field has made remarkable progress in locomotion, but manipulation — the true test of general-purpose utility — remains in its early stages.

For investors, the key takeaway is: hardware demonstrations are not product readiness. The path from viral video to reliable product is longer than the market currently prices.

Standard Kepler Research | standardkepler.com