🔥 LLMs Hit a Data Wall Robots Don’t
• LLMs depend on static, finite datasets, leading to synthetic data decay
• Robots learn by doing through continuous real-world interaction, just like humans
• Physical trial-and-error beats text-based training for genuine adaptation
💡 Generalization Requires a Body
• LLMs struggle with unseen, real-world scenarios
• Robots must generalize to act in dynamic environments (for example, a waiter handling a dropped plate)
• Intelligence emerged from action and perception, not just language
🤖 LLMs Are the Brain Robotics Builds the Body
• LLMs handle high-level reasoning (such as figuring out how to open a door)
• Robots bring perception, motion, and action into the loop
• True AGI demands embodiment—mind and body together
🚀 The Race is Physical
• Tesla Optimus, Figure AI, and Boston Dynamics are betting on embodied AI
• China’s 2025 Robotics Plan aims for humanoid bots in factories and healthcare
• The next “ChatGPT moment” will be a robot that learns like a child
