Part II: Competing in the age of embodied AI (Analyst Angle) - RCR Wireless

The manufacturing-first model (Tesla): Optimus inverts the equation. By designing explicitly for manufacturability and reusing automotive supply chains (think motors, batteries, power electronics, and compute platforms adapted from vehicle production) Tesla’s stated goal is a unit cost under $20,000, though this target remains unproven at scale. The robots are initially far less capable than Atlas, but the model is deployment-driven: iterate through volume production, improve through field The state-supported model (China): Dozens of startups (Unitree, Fourier Intelligence, UBTech) compete to build low-cost humanoids, leveraging Shenzhen’s dense manufacturing ecosystem for rapid hardware iteration. Local governments provide subsidies and guaranteed purchase orders to accelerate deployment, treating humanoid robotics as strategic industrial policy rather than purely market-driven development. The result: Western industrial robots often exhibit higher initial performance, but partially integrated Chinese firms can improve faster through deployment-driven learning. Over a ten-year horizon, the question is whether initial capability advantage or iteration speed matters more. The answer likely varies by application.

Arena 3: Humanoid robots (the next general-purpose platform)