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America’s Race For Humanoid Robots: Can It Catch Up with China?

U.S. tech giants are betting big on humanoid robots, but analysts warn they’re already trailing China. With Nvidia’s Jensen Huang and Tesla’s Elon Musk fueling investor enthusiasm, the competition is heating up. Yet, China’s rapid progress mirrors its dominance in electric vehicles, positioning it ahead in this new frontier.

The Robotics Revolution

Humanoid robots—AI-driven machines designed to mimic human movement—are set to transform industries from manufacturing to customer service. The U.S. sees them as crucial to future economic growth, but analysts caution that China’s aggressive industrial policies and supply chain advantages give it a head start.

Nvidia’s Huang recently unveiled new tech for humanoid robotics, while Musk’s Tesla aims to produce 5,000 Optimus robots in 2024. That puts it ahead of U.S. rivals like Apptronik and Boston Dynamics, but not China’s Agibot, which has matched Tesla’s production target. Meanwhile, Unitree Robotics has already sold humanoid models directly to consumers.

Price & Scale: China’s Edge

Morgan Stanley estimates humanoid robot production costs range from $10,000 to $300,000. But China’s scale is driving prices down. Unitree’s G1 starts at $16,000, while Tesla’s Optimus Gen2 is projected at $20,000—if Tesla can optimize costs using Chinese components.

China isn’t just ahead on pricing. Over the past five years, it has filed 5,688 humanoid robot patents—compared to just 1,483 from the U.S. EV giants like BYD and Geely have already deployed Unitree’s robots in factories, while Beijing actively supports large-scale production.

The U.S. Challenge

A recent SemiAnalysis report warns that China’s humanoid robots are entirely independent of U.S. components, posing an “existential threat” to American industry. To compete, U.S. firms must strengthen domestic manufacturing and diversify supply chains.

Bank of America predicts humanoid robot adoption will soar, reaching 1 million annual sales by 2030 and 3 billion in operation by 2060. But for now, China leads. If the U.S. wants a stake in the future of robotics, time is running out.

Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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