36 related articles

Why do billion-dollar robot companies like Figure and Physical Intelligence all demo folding laundry? A deep dive into deformable object manipulation, Moravec's Paradox, and why laundry folding is the ultimate test of general-purpose robotics.

RLC (Reinforcement Learning Conference) is a dedicated RL academic conference, yet far less known than NeurIPS or ICML. This article analyzes why and explores its future potential in the RLHF era.

Figure.AI demos F.03 robot autonomously climbing a ladder, showcasing breakthroughs in dynamic balance, multi-limb coordination, and embodied intelligence for industrial applications.

Deep analysis of Google Gemini Robotics ER 2's three core breakthroughs: video understanding, tool orchestration, and multi-robot collaboration, exploring how embodied reasoning drives robots from passive execution to autonomous intelligence.

Can switching to plumbing or electrical work really protect you from AI long-term? This article analyzes white-collar vs. blue-collar replacement timelines, the durability of the physical moat, and personal strategies more important than picking the right career track.

Explore RRT co-inventor James Kuffner's career from Cloud Robotics and Google Robotics to Symbotic CTO, driving robots from labs to Walmart warehouse-scale deployment.

Deep dive into Google DeepMind's Gemini Robotics 2: its whole-body intelligence, dexterous manipulation, adaptive reasoning, and how multi-robot collaboration is advancing embodied AI from lab to reality.

Deep dive into Google DeepMind's Gemini Robotics 2: its three core capabilities of whole-body intelligence, dexterous manipulation, and adaptive reasoning, plus how multi-robot collaboration is pushing embodied AI from labs into the physical world.

Deep analysis of how Google DeepMind's Gemini Robotics 2 empowers Apptronik's Apollo 2 humanoid robot with whole-body intelligence, exploring VLA model breakthroughs and the commercialization outlook for general-purpose robots.

Google DeepMind releases Gemini Robotics 2, achieving humanoid full-body control, multi-step error recovery, multi-robot coordination, and on-device deployment with built-in safety mechanisms.

Google DeepMind releases Gemini Robotics 2, a robot foundation model enabling humanoid full-body control, multi-step error recovery, multi-robot coordination, and on-device deployment.

Satyress's Threehalves centaur teleoperated robot sparks debate. This 7-foot quadruped robot targets hazardous work but draws comparisons to amusement rides. Deep analysis of its design logic and positioning.

Deep dive into Google DeepMind's Gemini Robotics 2: how whole-body intelligence unifies perception, reasoning, and motor control, and the challenges of bringing embodied AI from lab to commercial deployment.

Deep dive into Google DeepMind's Gemini Robotics 2: how whole-body intelligence unifies perception, reasoning, and motor control, and the challenges from lab demos to commercial deployment.

Deep dive into Google's Gemini Robotics 2 and its three core capabilities: full body intelligence, advanced dexterity, and multi-robot teamwork—achieving universal robot AI with one brain for any robot.

Deep dive into Google's Gemini Robotics 2 and its three core capabilities: full body intelligence, advanced dexterity, and multi-robot teamwork—achieving universal robot AI with one brain for any robot.

Analysis of the U.S. ban on Chinese humanoid robots: data security concerns, industrial protection motives, and how the AI race extends into Physical AI and robotics hardware.

Analysis of the U.S. ban on Chinese humanoid robots: data security concerns, industrial protection motives, and how the AI race extends into Physical AI and robotics hardware.

Deep dive into how Transformer² uses a unified Transformer architecture to integrate robot morphology design and motion control into one model, enabling task-driven end-to-end co-design for embodied AI.

DeepSeek founder Liang Wenfeng reveals a five-step AGI roadmap from chain-of-thought to embodied intelligence. How does TileLang crack domestic GPU substitution under a 20,000-card constraint?