Robotics

Beijing is establishing humanoid robot schools to train AI for diverse industries, aiming for global leadership in robotics. This state-backed initiative, involving extensive data training and the development of dexterous robotic hands, prepares robots for tasks ranging from domestic chores to complex repairs. The goal is to augment human capabilities by handling dangerous or repetitive work, rather than replacing humans.

Nvidia is establishing a new embodied AI research hub in Singapore, the company’s second in Asia Pacific. This strategic move aims to accelerate embodied AI development, integrating AI with physical systems like robots. Singapore is solidifying its role as an AI innovation center, launching a testbed for AI robotics and a Center for Intelligent Robotics to explore real-world applications. These initiatives underscore Singapore’s commitment to advancing AI technology.

Day two of TechEx North America focused on in-depth AI discussions, acknowledging pitfalls but maintaining optimism. Sessions addressed challenges in enterprise AI implementation, ROI, and adoption, emphasizing data foundations and financial implications. Cybersecurity concerns highlighted the “velocity gap” of rapid AI adoption and the rise of “shadow AI.” The event also showcased excitement for physical AI and robotics, with practical learning opportunities and a business-focused approach.

British tech firm Humanoid will deploy 1,000-2,000 robots at Schaeffler’s global manufacturing sites by 2032, starting in late 2026. This partnership, focusing on tasks like box handling, signals a significant integration of humanoid robots into the automotive supply chain. Concurrently, South Korean startup RLWRLD is collecting human motion data to train AI for robots, aiming for industrial and service applications by 2028, despite labor concerns about job displacement.

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.

SoftBank plans a U.S. IPO for its new AI and robotics venture, “Roze,” potentially this year, targeting a $100 billion valuation. The company will develop data centers and leverage robotics for AI infrastructure. This move aims to fund SoftBank’s substantial AI commitments, including its OpenAI investment, and integrate diverse assets like ABB Robotics. The initiative deepens SoftBank’s focus on the U.S. AI market, following projects like “Stargate” and data center development.

LG and NVIDIA are reportedly in preliminary discussions exploring collaborations in physical AI, data center solutions, and mobility. LG aims to leverage NVIDIA’s processing power for its advanced hardware, particularly in thermal management for AI data centers and low-latency inference for home robots. NVIDIA could gain access to LG’s mass-market data and distribution channels for AI model training, while both companies could benefit from unifying automotive infotainment with NVIDIA’s autonomous driving platforms.

Despite mixed Q1 results, Jim Cramer urges investors to focus on Tesla’s long-term disruptive potential beyond immediate financial performance. He highlights Elon Musk’s ambitious vision in AI and robotics, including the Optimus robot, as key drivers of future value. Cramer views increased capital expenditures as strategic investments in innovation, suggesting patient investors will benefit from Tesla’s expansive technological ecosystem and forward-thinking approach.

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.