AI's Physical Evolution: From Data Centers to Factory Floors
Tesla, aiming to begin external supply of Optimus by 2027, is set to introduce the model into its factories by 2028. Meanwhile, Samsung and LG join the robot development race, despite China's rapid increase in robot shipments, with only 18% being utilized in manufacturing and logistics.
Artificial Intelligence (AI) is no longer confined to screens; it is stepping into the physical realm. AI, trained in data centers, is now being utilized as the brainpower behind robots that move and assemble parts in factories. This marks a significant shift from mere technology demonstrations to the deployment of humanoid robots in industrial settings. Global corporations are intensifying their competition, moving beyond merely replicating robotic movements to securing technologies applicable in real-world production scenarios.
As Physical AI (PAI) commercialization draws nearer, the focus intensifies on mass production capabilities, data collection from work processes, and on-site productivity. While Tesla and Hyundai Motor Group solidify their commercialization timelines, NVIDIA, Samsung Electronics, and LG Electronics are accelerating their efforts in robot development and AI learning technologies.
Tesla's Robot Revolution: Production Begins, External Sales on the Horizon
Early Ramp and Production Goals
In its third-quarter shareholder report, released on the 21st, Tesla announced that its humanoid robot, 'Optimus,' production line at the Fremont, California, factory has entered the initial Early Ramp phase. The company has converted its existing Model S and X production facilities into a robotic production line, with a long-term goal of achieving an annual production capacity of 1 million units.
Elon Musk, Tesla's CEO, predicted during the earnings conference call that weekly production will reach approximately 20,000 units within a year. This is a future target rather than current production figures. Tesla plans to supply external companies with Optimus, after improving its precise hand movements, durability, and AI learning capabilities, by the end of 2027.
Data Acquisition and Learning Environment
To accompany this large-scale learning data acquisition, Tesla is pushing forward with the 'Optimus Academy,' where 10,000 to 20,000 robots will repeatedly perform various tasks to generate learning data. Unlike automobiles, humanoid robots require a separate learning environment to accumulate large-scale data from actual work processes, highlighting the need for dedicated training.
Hyundai Motor Group's Unique Approach to Robotics
Hyundai Motor Group (HMG) takes a distinct approach to its robotics strategy, opting to first deploy Boston Dynamics' humanoid robot, 'Atlas,' within its production facilities to assess its capabilities and cost-effectiveness. Unlike external sales, HMG aims to utilize Atlas to enhance its manufacturing processes.
HMG's plan involves establishing a Robot Meta-Plant Application Center (RMAC) in Georgia, USA, where Atlas will undergo work learning and validation. By 2028, HMG aims to integrate Atlas into its Meta-Plant America (HMGMA) facilities. Initially, the robot will be tasked with sequencing operations, arranging production components in the correct order. The goal is to expand its application to assembly processes by 2030.
While Tesla focuses on mass production and external market penetration, HMG leverages its existing automotive factories as testbeds for robotic technologies and as early adopters. Both companies develop robots capable of working in real industrial settings, but their chosen paths to commercialization differ during this early stage.
Nvidia Expands AI Platform; Samsung and LG Pursue Robot Development and Training
For a humanoid to work in a real factory, it must not only recognize the position and shape of objects but also accurately perform actions such as grasping and moving them. Even when repeating the same task, the position of the object or the surrounding environment may change, so it requires learning capabilities to adapt to various situations.
Nvidia recently expanded its robot development platform, 'Isaac,' and unveiled reference platforms and simulation technologies for humanoid robots. This technology enables robots to learn tasks and verify their safety in a virtual environment before being deployed in actual factories, and global industrial robot companies like ABB Robotics and KUKA are also utilizing this technology.
The domestic electronics industry is accelerating its own robot development while leveraging these AI learning technologies. Samsung Electronics announced the establishment of the RX (Robotics eXperience) Business Promotion Office, which reports directly to the CEO, on July 21st, and has embarked on developing humanoid walking, object manipulation, and AI learning technologies. The company is also pushing to build a robot data factory at its Gumi plant in Gyeongbuk and expanding its cooperation with Rainbow Robotics.
LG Electronics' Robotics Venture: A Look into the Future
LG Electronics has taken a significant step towards expanding its robotics portfolio by establishing the Robotics Business Center last July. The company is simultaneously developing a household robot, 'Cloyd,' and a next-generation humanoid robot. Leveraging NVIDIA's robot AI technology, LG is developing a bipedal humanoid with a target release date of the first quarter of 2027.
The wheel-type Cloyd is currently undergoing testing at the company's washing machine production line in its Tennessee factory.
In tandem with robot development, LG is also securing real-world operational data. The company is collecting robot learning data at its Yangjae Data Factory in Seocho-gu, Seoul, and plans to amass a total of 100,000 hours of data by the end of the year, combining actual and virtual data. Utilizing NVIDIA's Omnibus, Cosmos, and Isaac technologies, LG is expanding real-world operational data into a virtual environment to train its robots.
The reason behind Samsung and LG's utilization of their manufacturing facilities lies in the repetitive assembly, transportation, and inspection tasks that take place in factories. These tasks can serve as valuable learning material to enhance a robot's operational accuracy and environmental adaptability. By concurrently developing their own robots and accumulating data, both companies aim to secure technologies applicable to future manufacturing processes and service sites.
China's Rapid Humanoid Robot Expansion Faces Economic Viability Test Despite Supply Chain Constraints
Chinese manufacturers are leading the charge in expanding the humanoid robot market, rapidly ramping up production volumes. According to market research firm Counterpoint Research, global humanoid robot shipments exceeded 22,000 units in the first half of 2026, a staggering 300% increase year-over-year.
AGIBOT, a Chinese robotics firm, shipped approximately 9,700 units, while Unitree surpassed 7,000. Together, these two companies accounted for over 74% of the global market share. In terms of production, Chinese enterprises are driving the initial supply expansion in the global humanoid robotics space.
However, when examining actual deployment, industrial applications remain limited. Among the shipments in the first half, intelligent manufacturing accounted for only 13%, while warehouse and logistics operations made up a mere 5%. In contrast, the entertainment and data production sectors dominated with over 60% of the shipments. This indicates that the increase in shipments has not yet translated into immediate factory automation or logistics productivity gains.
As China continues to dominate the early supply chain of humanoid robotics, the industry faces the critical challenge of economic viability. With limited manufacturing and logistics utilization, the question remains whether these robots can justify their production costs and deliver tangible benefits to businesses. The next phase of commercialization will be pivotal in determining the long-term success and adoption of humanoid robots in various industries.
The Race to Commercialize Robotics: Overcoming Challenges and Market Dynamics
The utilization of robots in industrial settings demands rigorous validation not only in terms of speed and precision for repetitive tasks but also in their reliability, maintenance costs, and safety when working alongside humans over extended periods. Reuters reported in August that certain humanoid robots exhibit speeds approximately 20% of human capabilities even for simple tasks. While this figure may not be universally applicable to all robots, it underscores the performance gap that exists in real-world applications.
As Tesla and Hyundai Motor Group solidify their production and deployment timelines, and Samsung Electronics and LG Electronics venture into developing their own robots and acquiring learning data, Chinese manufacturers are taking the lead in expanding their shipment volumes. Despite varying commercialization strategies among these companies, the stability of robotic performance in industrial settings and their ability to reduce costs will be pivotal in determining the pace of market expansion.
