Physical AI

Nvidia partners with Chinese robot maker Unitree to launch a new robotics platform for researchers, signaling its “physical AI” ambitions. The integrated system combines Unitree’s H2 humanoid robot with Nvidia’s Jetson Thor platform and AI models, aiming to democratize access to advanced robotics development. This collaboration supports Nvidia’s vision for a multi-trillion-dollar physical AI industry and expands its software development footprint.

The Physical AI Expo North America, May 18-19, 2026, in San Jose, will gather experts to explore the transition of AI from abstract concepts to tangible, real-world applications. The event focuses on enterprise-scale deployment strategies for robotics, autonomous systems, and AI infrastructure, bridging the gap from prototype to production. Leading minds will discuss practical execution, reliability, safety, and the engineering required for AI to thrive in dynamic physical environments.

Physical AI integrates AI into real-world systems, posing complex governance challenges. With industrial robot adoption soaring, the market for Physical AI is projected to expand significantly. Unlike software AI, physical systems interact directly with dynamic environments and human users, demanding stringent safety parameters and clear escalation protocols. Google DeepMind’s Gemini Robotics, built on embodied AI principles, exemplifies this shift, offering advanced capabilities for robot control and reasoning. Effective Physical AI requires generality, interactivity, and dexterity, alongside robust visual perception, spatial reasoning, and task planning. Safety controls, traditionally software-based, must now be embedded into system design for physical interactions, with frameworks like NIST and ISO adapting to this evolving landscape.

Kakao Mobility is investing heavily in in-house Level 4 autonomous driving technology as part of its “Physical AI” strategy. The company presented its plans at the 2026 World IT Show, detailing a roadmap focused on advanced machine learning, robust redundancy, and rigorous validation. Key initiatives include developing a safety management platform with a passenger visualizer, an operational control center, and fostering an open ecosystem by sharing datasets, HD maps, and APIs. Their Gangnam autonomous service has demonstrated a strong safety record, signaling progress towards broader deployment.

Sony AI’s table tennis robot, Ace, challenges elite human players, showcasing advancements in physical AI with split-second decision-making and motor control. Ace uses high-speed perception and AI algorithms to execute complex shots. In trials, it achieved victories against professionals, a significant feat compared to previous robots. This development pushes the boundaries of AI in dynamic, real-world environments, with potential applications in manufacturing and service robotics.

Hyundai Motor Group is pivoting beyond automotive to “physical AI,” integrating intelligence into robots for physical world interaction. With a $26 billion U.S. investment, the group aims for human-robot collaboration, scaling humanoid robot production for factories and exploring applications in logistics and mobility. This strategy, driven by Chairman Chung Eui-sun, emphasizes synergy between humans and machines to enhance efficiency and quality, complemented by significant investment in hydrogen technology.

Thrive Logic and Asylon partner to introduce “Physical AI” for network edge security. This integration combines Asylon’s robotic patrols with Thrive Logic’s AI agent analytics for proactive, autonomous incident detection and response. The goal is to minimize response times, enhance operational resilience, and provide security leaders with reliable, auditable coverage in exterior security zones. This human-AI collaboration shifts security from reactive to strategic oversight.

Physical AI, specifically humanoid robots, are proving vital for customer service, addressing labor shortages and the limitations of traditional automation. A partnership between KDDI and AVITA exemplifies this, combining robust communication infrastructure with advanced avatar technology. These robots, designed with human-like expressions and movements, aim to replicate nuanced nonverbal cues crucial for hospitality. Leveraging powerful data centers and AI models like Google’s Gemini, they are being prepared for commercial trials, marking a significant step from digital to physical customer interaction.

Physical AI development is fragmented. While giants like OpenAI focus on large models, Hitachi and Siemens champion domain expertise. Hitachi’s approach emphasizes foundational understanding of physics and industrial equipment, citing projects with Daikin and JR East as proof of concept. Their R&D also targets accelerating software development and ensuring safety through integrated design. Hitachi Vantara is also leveraging NVIDIA hardware for advanced digital twins, aiming to create robust physical AI systems.

Alibaba has launched RynnBrain, an AI model for robotics, to enhance robots’ environmental understanding and object recognition. This strategic move places Alibaba in the competitive “physical AI” sector, alongside global giants like Nvidia, Google, and Tesla, all racing to advance AI in robotics. By open-sourcing RynnBrain, Alibaba aims to accelerate its adoption and innovation in this rapidly expanding field.