Robots Shift From Imitation to Real-World Task Practice
Scobleizer · x · 2026-07-11
The reply emphasizes that most robots still learn by imitating human demonstrations. However, relying solely on imitation only replicates human performance; it cannot run faster or more reliably than the demonstrator, nor does it learn the cost of failure.
The author argues that the direction taken by @TheHumanoidAI on Kinetiq Ascend is critical:
- No longer just replicating demo actions
- Instead, having humanoid robots practice in real production tasks
- Representing a shift in physical AI from "looking like it can do it" to "actually doing it in real-world scenarios"
The same post mentions that @Scobleizer has compiled the most comprehensive list of robotics-related accounts on X.
Related event: Humanoid Robots Shift to Real-World Reinforcement Learning(3 posts)→
More from Embodied
- Sunday Robotics Hires Strategic Projects Lead to Accelerate Home Robots — tonyzzhao · 2026-07-22
- Tesla’s summer update lets Grok make calls, control climate, and play music — Polymarket · 2026-07-22
- Hugging Face Teases Agentic Training Environments with OpenEnv for August Launch — mervenoyann · 2026-07-22
- NVIDIA shows 22 SIGGRAPH papers and Omniverse tools for robot simulation — facontidavide · 2026-07-22
- Nothing phone mockup turns a film joke into a modular design meme — ZeYanjie · 2026-07-22
- Lightwheel AI Launches SimReadyGen: Text-to-Physics-Accurate Robot Sim Assets — ZeYanjie · 2026-07-22