Robotics Industry Faces 100,000-Year Data Gap as Companies Turn to Traditional Engineering to Bridge AI Divide

Robotics companies face a massive 100,000-year data shortage compared to AI language models, prompting industry leaders like Waymo and Ambi Robotics to combine traditional engineering with AI to create commercial robots that generate real-world data while performing tasks like driving taxis and sorting packages.

• Robotics faces a massive 100,000-year data gap compared to language models, as current robot datasets contain only about 1 year of data while AI language models train on the equivalent of 100,000 years of human-readable content
• Companies like Waymo and Ambi Robotics successfully combine traditional engineering methods with AI to create 'data flywheels' where commercial robots collect real-world data while performing useful tasks like driving taxis and sorting packages
• Good old-fashioned engineering (GOFE) methods based on established math and physics can bridge this gap by enabling robots to work reliably in commercial environments immediately, generating the massive datasets needed for future general-purpose robots