Fei-Fei Li: Simulation is Key for Robotics as Real-World Data Falls Short
YunzhuLiYZ · x · 2026-07-30
In a recent discussion, Fei-Fei Li highlighted the critical role of simulation in robotic learning. She explained that simulation allows us to play out events that haven't happened or cannot happen in the real world, enabling robots to learn how to act in those situations. Emphasizing that real-world data alone is insufficient for robotics, she pointed to self-driving cars—specifically Waymo's use of billions of hours of simulation—as proof that even the simplest robots rely heavily on simulated training.
More from Embodied
- From Fast & Furious FPV Drones to Embodied AI: Joining Neros Tech — _sonith · 2026-07-30
- OpenDerm: An Open-Source 4-DOF Home Robot for Early Skin Cancer Detection — plopesresearch · 2026-07-30
- Open-source high-performance desktop robotic arm PAROL6 with full software and STL files — tom_doerr · 2026-07-30
- On-Device Real-Time Video Object Detection with RF-DETR and SwiftUI — amos_gyamfi · 2026-07-30
- Latest Tesla Optimus Demo: Humanoid Robot Shows Upgraded Fluid Motion — Sugar__bae · 2026-07-30
- Meta Smart Glasses Fuel 'Pervert Glasses' Trend, Instagram Cracks Down — fortune · 2026-07-30