The Global Race to Give AI a Body

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The Global Race to Give AI a Body

Picture this: a humanoid robot in a California kitchen, calmly frying a steak. Another in a warehouse, moving boxes with a colleague, coordinating silently through eye contact. Across the world, in a Chinese factory, workers test a new humanoid priced at just RMB 99,000 (USD 13,860), the first of its kind available to everyday consumers.

Scenes like these — once the stuff of sci-fi films — are now unfolding in real time.

Two years ago, Nvidia CEO Jensen Huang predicted that “embodied intelligence” — giving AI a physical form — would be the next frontier. Many dismissed the idea as hype. But today, a global race between the US and China is taking shape, with trillions of dollars in future markets at stake.

If ChatGPT taught machines to “speak,” embodied intelligence is about teaching them to act. It means equipping AI with bodies — humanoid or otherwise — so they can interact with the physical world.

Humanoid robots are the hardest path. They require an integrated “brain” (AI models), advanced sensing, precision motors, lightweight but strong structural materials, and enough computing power to coordinate it all. Each of these is hard on its own. Building them all at once is exponentially harder.

And yet, some of the biggest names in tech believe this is the next industrial revolution.

The US bets on brains

Elon Musk has never been shy about bold predictions. When he told investors in 2023 that humanoid robots could outnumber people by 2040, most rolled their eyes. But then Tesla unveiled Optimus: a robot that can balance, dance, and even cook.

Optimus draws on Tesla’s long history with autonomous driving. Instead of relying on expensive LiDAR sensors, it uses camera-based vision systems — the same tech Tesla deploys in its cars. Its actuators are powerful enough to lift a piano, and its AI “brain” runs on Grok 4, a large model trained on massive datasets using Tesla’s Colossus supercomputer.

Still, Optimus isn’t ready for prime time. It works at 20–30% of human efficiency, costs around USD 60,000 to build, and its delicate hands may last only a few months before needing replacement. For now, it’s a prototype with promise, not a product.

But Musk’s bet is bigger than Optimus itself. By linking the robot project to Tesla’s broader ecosystem — chips, software, and suppliers — he is trying to create a platform play.

Meanwhile, Silicon Valley’s startup machine is at work too. Figure AI, founded only a few years ago, has already soared to a USD 39.5 billion valuation, backed by Microsoft, Nvidia, Jeff Bezos, and others. Its founder Brett Adcock is eyeing what he calls “the USD 40 trillion global labor market” — essentially, half of global GDP.

Figure’s key innovation is Helix, a multimodal AI model that can interpret plain-language instructions and translate them into physical action. In demos, its robots can understand “bring me that extinct animal,” reason symbolically, and fetch a dinosaur toy. They can even coordinate through gaze cues — a step toward real-world teamwork.

The hurdles are steep: collecting the enormous amounts of real-world training data that Helix needs, and overcoming the limits of short-term memory in today’s AI. Still, Figure AI’s funding and ambition have made it one of the most closely watched players in the field.

China bets on bodies

If the US is chasing intelligence, China is chasing scale.

Unitree Robotics, based in Hangzhou, has already put a humanoid robot on the market: the G1, priced at just USD 14,000. For comparison, Tesla is aiming for a future price of USD 20,000–30,000 — but today sells at twice that.

Unitree’s strategy is simple: extreme cost control, mass production, and full use of China’s supply chain depth. It already dominates the quadruped robot market, and its experience in motors and structural parts translates well to humanoids.

Its weakness is software. Unlike Tesla or Figure AI, Unitree lacks a frontier-scale AI model of its own. Its robots can move with precision, but their “brains” remain basic, relying on third-party algorithms.

Another Chinese contender, Agibot, is taking a different path. Founded in 2023 by ex-Huawei engineers, it has built a Huawei-style ecosystem around itself — forging joint ventures with suppliers, material companies, and automation firms. That approach has sped up production dramatically: within a year, it had rolled out its 1,000th humanoid robot, setting an industry record.

Agibot has also been aggressive in capital markets, acquiring companies and pushing its valuation to RMB 15 billion (USD 2.1 billion). But with less technological depth than Tesla or Unitree, it still needs to prove staying power.

The interdependence problem

On paper, this looks like a US vs China race. But peel back the layers and the picture is messier.

Tesla’s Optimus relies heavily on Chinese suppliers for key parts, from sensors to actuators. According to Morgan Stanley, 63% of the global humanoid robot supply chain is in China. At the same time, Chinese robots still depend on US-developed AI models and chips.

That creates a paradox: America leads in “brains,” China in “bodies.” Each side needs the other. And in a geopolitical era of tariffs, tech restrictions, and fragmented supply chains, that interdependence could become both a strength and a vulnerability.

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The standards race

The deeper question is not who can make the cheapest or strongest robot. It’s who will set the standards.

The last industrial revolutions were defined by those who wrote the rulebook: Britain for textiles, the US for automobiles, Japan for semiconductors. In embodied intelligence, the standards are still being written. Will the “brains” (AI models, algorithms) dominate? Or will the “bodies” (motors, materials, manufacturing) prove decisive?

So far, the US has set the intellectual agenda: transformers, diffusion models, reinforcement learning. But China has turned itself into the workshop of the world. Which side adapts faster may determine who leads this new era.

The clock is ticking

AI moves quickly. It took just five years to go from GPT-1 to GPT-4. Many insiders think humanoid robots could go from prototype to commercial deployment in as little as three to five years.

For China, the window to catch up may be less than a decade. Traditional manufacturing advantages — low cost, scale, supply chain efficiency — will matter less if AI can optimize design and production automatically. For the US, the risk is different: leading in algorithms but losing ground if it cannot scale affordable hardware fast enough.

Either way, embodied intelligence is no longer science fiction. It’s a race — for markets, for standards, for control over the next general-purpose technology.

The only real question is: when the robots arrive, will they be American, Chinese, or — inevitably — both?

Interested in learning more about x? Check out our previous coverage here:

• Google’s Last Stand? How India Became the Battleground in the AI War Against Microsoft?

• India’s AI Moment: Market, Lab, or Builder?

• From Hype to How: 5 Lessons from the 2025 State of AI Report

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We’ll be back in your inbox 2 PM IST next Sunday. Till then, have a productive week!

Peeyush and Mohit

Disclaimer: The views, thoughts, and opinions expressed in the text belong solely to the author, and not necessarily to the author's employer, organization, committee or other group or individual.