Japan’s Next Frontier in AI: “Physical AI” Takes Shape with Digital Twin Platforms

As generative and agentic AI grow in Japan’s businesses, industry leaders are now focusing on a new trend: “Physical AI.” This type of AI works directly with the physical world using robotics and connected devices. At a recent tech briefing, 菱洋エレクトロ (Ryoyo Electro) shared its plans to boost physical AI. They are creating digital twin platforms and working with partners like NVIDIA and avatarin.

The shift to physical AI marks a key change in how companies use artificial intelligence. It goes beyond data analysis and software. AI is advancing in many areas. These include manufacturing automation, service robotics, and daily tasks. Digital twin technology is central to this shift. These are accurate virtual copies of physical systems. They allow quick simulation, training, and learning. This happens without the costs and risks tied to real-world testing.

What Is Physical AI and Why It Matters

Physical AI means putting artificial intelligence in robots, edge devices, and autonomous machines. These systems can see, think, and act in real-world settings. Physical AI differs from traditional AI, which is limited to apps and data centers. It must handle complex sensory inputs and interact with both humans and machines in unpredictable spaces. This ability creates new opportunities in many industries. It includes smart factories, service robots in retail and hospitality, and logistics automation.

菱洋エレクトロ’s vision places digital twin platforms at the core of physical AI development. Digital twins help developers create models of physical spaces. They also generate synthetic data for AI training. This solves a major problem in physical AI: the lack of real-world data needed for effective model training. Simulating environments helps train robots and autonomous systems safely. This speeds up deployment and cuts development costs.

During the event, Ryoyo Electro executives stressed the need for early investment in infrastructure and skills. They want to ensure Japanese companies don’t fall behind in this new field. This reflects earlier concerns about using generative AI.

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Key Partnerships in the Physical AI Ecosystem

Ryoyo Electro has built its physical AI strategy around collaborating with technology leaders:

• エヌビディア: It is a key partner. It leads in high-performance AI computing and edge inference hardware. NVIDIA’s CEO, Jensen Huang, sees digital twins as a key pillar for future AI systems. This fits well with powerful computing and edge devices. His view supports Ryoyo Electro’s direction.
• avatarin: A provider of service robotics and AI systems, avatarin offers expertise in how robots and humans interact. This matters a lot in customer service.

In today’s world, partnerships are key. They help tackle the complex task of merging AI, sensors, robotics, and real-time control into smooth systems. No single company can handle this challenge alone.

日本のハイテク産業への影響

New Growth Frontier Beyond Software AI

The Japanese tech sector is known for its top-notch hardware and robotics. It’s set to take the lead in physical AI. Domestic companies with a solid background in precision engineering and factory automation can blend these strengths with AI. This combination leads to systems that are smart and physically capable.

Physical AI could spark Japan’s industrial revival. It can make factories more independent and stronger, especially during labor shortages. Digital twin ecosystems connect current industrial systems with future autonomous operations. They support national goals for manufacturing innovation and AI adoption.

Skills and Talent Challenges

Ryoyo Electro executives are excited about physical AI. However, they know that talent shortages and a lack of understanding hold back investment. To address this gap, the company has expanded its RYOYO AI Techmate Program to include digital twin support, partner matching, development resources, training, and consulting services, helping organizations build confidence and capability in adopting these technologies.

Focusing on building skills is crucial for Japan’s tech industry. The quick rise of generative AI has revealed skill gaps that slow down deployment. Physical AI’s complexity includes sensors, robotics, simulation, and machine learning. This will need even more expertise.

Broader Effects on Businesses in Japan

Manufacturing and Industrial Operations

Physical AI and digital twins can change how production lines are optimized and maintained in manufacturing. Companies can simulate production workflows and machinery in virtual environments. This helps reduce unplanned downtime, boost throughput, and enhance safety. Businesses using these tools can boost productivity and cut costs. This helps them stay competitive at home and abroad.

Service and Retail Environments

Physical AI can boost service industries like hospitality, logistics, and healthcare. It helps with repetitive tasks and enhances customer experience. AI-powered robots can manage deliveries, answer customer questions, and tackle complex inventory tasks. They do this with little help from humans. This technology helps solve ongoing labor shortages and allows for new service models.

Supply Chains and Logistics

Physical AI also aligns with broader trends in smart logistics. Smart robots and self-driving vehicles trained in simulations can work efficiently in warehouses and distribution centers. They boost speed, accuracy, and safety in order fulfillment. This makes a big difference in today’s competitive supply landscape.

Conclusion: Physical AI as a Strategic Imperative

Ryoyo Electro’s move into physical AI and digital twin tech shows a key change in Japan’s tech industry approach to AI. As generative and agentic AI grow, physical AI becomes the next frontier. This is where AI engages with the real world to tackle complex business and operational challenges.

Japan’s tech sector and industrial businesses must invest in physical AI, digital twin platforms, and partnerships with global leaders like NVIDIA. This will help them stay competitive and drive innovation. Challenges still exist, especially in talent development and education. However, physical AI offers a chance to lead in a time when digital and physical systems come together.