Humanoid data

📰 MIT Technology Review

Robotics companies are collecting vast amounts of data on human movement to train humanoid robots, using tactics like paying people to film themselves doing tasks or playing games that control robotic arms.

intermediate Published 21 Apr 2026
Action Steps
  1. Join online platforms that collect human movement data, such as apps that pay users to film themselves doing tasks.
  2. Participate in games or simulations that control robotic arms to improve their dexterity.
  3. Explore virtual simulations that model human movement and friction.
  4. Investigate the use of large language models in robotics, such as applying scaling laws to robotics training.
  5. Research the ethics of collecting and using human movement data for robotics training.
Who Needs to Know This

Robotics engineers, AI researchers, and data scientists can benefit from understanding the latest trends in humanoid robot training, which relies on large amounts of human movement data.

Key Insight

💡 Human movement data is crucial for training humanoid robots, and companies are using innovative tactics to collect it.

Share This
🤖 Robotics companies are collecting human movement data to train humanoid robots. Join apps, play games, or participate in simulations to contribute! #AI #Robotics

Key Takeaways

Robotics companies are collecting vast amounts of data on human movement to train humanoid robots, using tactics like paying people to film themselves doing tasks or playing games that control robotic arms.

Full Article

Title: Humanoid data

URL Source: https://www.technologyreview.com/2026/04/21/1135656/humanoid-data-robot-training-ai-artificial-intelligence/

Published Time: 2026-04-21T16:45:00-04:00

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# Humanoid data

Robotics companies want tremendous amounts of data on how we move our hands and limbs, and their tactics are getting strange.

By
* [James O'Donnell archive page](https://www.technologyreview.com/author/james-odonnell/)

April 21, 2026

![Image 1](https://wp.technologyreview.com/wp-content/uploads/2026/04/humanoid-dataC2.jpg)

Stephanie Arnett/MIT Technology Review | Adobe Stock

I was recently invited to join an app that would pay me cryptocurrency to film myself doing tasks like putting food into a bowl, microwaving it, and then taking it out. Another website suggested I try a new game in which I'd remotely control a robotic arm in Shenzhen, China, as it completed puzzles and tasks, to help improve the robot's dexterity.

What on earth is happening? Well, just as our words became training data for large language models, robotics companies are betting that data about the way we move will help them build more capable humanoid robots. They see humanoids—despite being trickier to train than simple robotic arms—as more easily slotting into the places where humans work today (and someday replacing them entirely).

This new notion for how to train humanoids arguably began with the launch of ChatGPT in 2022. Large language models were able to generate text through exposure to massive amounts of training data—every word ever written that AI companies could find (or, some argue, steal). Roboticists wanted to apply these scaling laws to robotics but lacked an internet-size collection of data describing how we move.

Put off by how difficult this would be to amass, companies used workarounds, like teaching robots to move in virtual simulations. However, simulations never perfectly model how things like friction or elasticity work in the
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