Iván Hernández Dalas: How to avoid the teleoperation trap in robotics development
Flexion is building a reinforcement learning and sim-to-real platform for humanoid robots. Source: Flexion In the past 18 months, humanoid robotics companies have raised billions of dollars – a majority of which is quietly funding hiring humans to operate robots. This means the robotics industry has a teleoperation and data problem it keeps describing as a labor solution. Teleoperation and human demonstration at scale have become the dominant method for training physical AI systems, attracting serious capital, recruiting workers across lower-wage economies, and earning enthusiastic coverage as evidence of progress. The assumption underneath all of it is that enough demonstrations will eventually produce robots capable of generalizing across real environments. I believe that assumption deserves a lot more scrutiny than it’s getting. Teleoperation hits a structural wall Language models trained on text can draw from decades of writing, articles, and books. With robots, there...