Real-world video data provides virtually unlimited training material for AI models

Embodied AI’s ability to collect real-world data through cameras and sensors represents a fundamental shift away from reliance on internet-sourced training data.

Key metrics and scale: The volume of data collected through real-world capture far exceeds traditional internet-based sources.

• A single camera running continuously can generate the equivalent of FineWeb’s entire 15T token dataset (the largest open-source English training dataset) in just 15.6 years
• A network of one million cameras could generate one trillion training tokens in the time it takes to read a short article
• The data collection equation is straightforward: Data Scale = Number of Sensors × Time Elapsed

Technical advantages: Real-world data capture offers distinct benefits over internet-sourced training data.

• While internet content requires human effort to create and curate, real-world capture provides a continuous stream of unfiltered data
• Video data can be collected at massive scale – just 32.8 seconds of video capture can generate one million training tokens
• Sensor networks can be systematically adjusted to control for biases, unlike human-created content

Data quality considerations: The nature of real-world data differs fundamentally from text-based training data.

• Video tokens capture visual patterns, motion, and physical interactions rather than abstract concepts
• Real-world capture records reality as it exists, bound by physics and social dynamics
• This approach reduces human interpretation bias present in curated internet content

Practical implications: The shift to unlimited real-world data collection could enable significant advances in AI capabilities.

• Robots could develop improved ability to adapt to varied physical environments
• Autonomous vehicles might better handle unpredictable scenarios
• AI systems could develop deeper understanding of physical world interactions

Future trajectory: The elimination of data scarcity through embodied AI presents compelling possibilities for artificial intelligence development.

• With computing power and budgets expanding, data availability has been a key bottleneck
• Unlimited real-world data collection could remove this constraint
• This development may prove crucial for advancing toward artificial general intelligence (AGI)

Looking ahead: While the full impact of unlimited training data remains to be seen, the transition from scarce, human-created content to boundless real-world capture represents a significant evolution in how AI systems learn and understand the world around them.