Physical AI

BlackBerry is pivoting from its iconic phones to become a leader in physical AI, specifically robotics. Its safety-critical QNX operating system, already dominant in automotive, is now being expanded into industrial automation, automated warehouses, and medical devices. This strategic shift, focusing on specialized applications rather than humanoid robots, is driving significant growth and investor confidence, with the company citing a substantial backlog for QNX software in this burgeoning sector.

XPENG’s physical AI division secured over $900 million, valuing its IRON humanoid robot platform at $6.3 billion. This funding will accelerate robotics R&D, mass production, and global commercialization. The company’s integrated approach, leveraging its EV expertise and proprietary AI technology, positions it to lead in the physical AI era. Investors, including Tencent and Alibaba, recognize XPENG’s potential for scalable, automotive-grade humanoid robot manufacturing.

Nvidia’s new open-source Medical Physics Simulation framework enables healthcare robots to learn through “Physical AI,” acquiring embodied experience via detailed simulations rather than just data. This approach accelerates the generation of rare, critical scenarios, moving beyond traditional AI by simulating physical interactions and anatomical variations. It aims to provide a transparent, reproducible development process crucial for regulatory approval in the highly regulated healthcare sector. Leading companies are exploring this technology for various applications, though real-world clinical deployment of policies learned through this methodology is still in early stages.

ON Semiconductor’s CEO defended a major acquisition of Synaptics, aiming to capitalize on a projected $30 billion “physical AI” market. Despite investor skepticism and a stock sell-off, the company believes the deal will expand its addressable market to $243 billion by 2030, enhancing its edge AI capabilities for applications like autonomous vehicles and robotics. The CEO emphasized the strong complementary nature of the businesses and the continued robust performance of its core operations.

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.