Introduction.
A series of breakthrough innovations announced in the first two weeks of September 2025 have the potential to bring not just technological advances, but fundamental change to the manufacturing industry. This blog will provide an in-depth analysis of the major AI news during this period, particularly in terms of its application to the manufacturing industry.
Major AI News Overview
1. historic breakthrough for GoogleDeepMind (September 17)
Google DeepMind’s announcement of its Gemini 2.5 AI model has been positioned as a “historic moment” in the field of AI. The AI system won a gold medal in an international programming competition and demonstrated problem-solving abilities on par with the world’s best programmers The Guardian.
Notably, the AI solved a complex fluid dynamics problem in less than 30 minutes. This was a real-world engineering challenge of optimally distributing fluids through a network of interconnected reservoirs. This achievement is comparable in importance to Deep Blue’s chess victory in 1997 and AlphaGo’s Go victory in 2016.
Manufacturing Applications: This breakthrough could bring revolutionary changes in areas such as optimization of complex production processes, real-time quality control, and predictive maintenance. In particular, the problem-solving capabilities of fluid dynamics can be directly applied to cooling system design in the chemical process industry and automotive manufacturing.
2. transformation of the manufacturing industry by Physical AI (September 9)
The World Economic Forum’s white paper, “Physical AI: Powering the New Age of Industrial Operations,” articulates the next generation of automation in manufacturing World Economic Forum.
Physical AI represents an evolution from traditional fixed robots to adaptive systems with the ability to learn. This technology is evolving in three stages
- Rule-based robotics: conventional explicit programmed control
- Training-based robotics: Learning-based systems using machine learning
- Context-based robotics: AI-equipped systems that understand their environment and make decisions autonomously
Manufacturing applications:
- Amazon Case Study: Deployment of Over 1 Million Robots in 300 Distribution Centers Increases Efficiency by 25% and Skilled Positions by 30
- Foxconn Case Study: AI-Driven Robotic Workforce Reduces Cycle Times by 20-30%, Error Rate by 25%, and Operating Costs by 15
3. SpikingBrain 1.0 in China (September 9)
SpikingBrain 1.0 from the Chinese Academy of Sciences is an innovative AI model that mimics the firing patterns of neurons in the human brain The AI Track. the system is 100 times faster than traditional AI models and uses significantly less power.
Technical Features:
- Hybrid Linear Attention Mechanism
- 100x faster with TTFT (Time To First Token) with 4 million tokens
- Low power consumption due to high sparseness
Manufacturing Applications: This technology could revolutionize real-time quality inspection, predictive maintenance, and energy efficient production control systems. In particular, power savings will be an important contribution to sustainable manufacturing.
4. $300 billion contract between Oracle and OpenAI (September 10)
A five-year, $300 billion cloud computing deal between Oracle and OpenAI provides an important foundation for accelerating industrial applications of AI technology The AI Track.
The contract provides 4.5 gigawatts of computing power, which is an enormous amount of processing power equivalent to a medium-sized power plant. This infrastructure will enable large-scale deployment of AI applications in the manufacturing industry.
Manufacturing applications:
- Large-scale digital twin simulation
- Real-time, company-wide production optimization
- AI-driven management of global supply chains
5. Quantinuum’s Quantum Generation AI (announced Feb 4, noted Sept)
The Generative Quantum AI (Gen QAI) framework presented by Quantinuum is a breakthrough technology that leverages data generated by a quantum computer to train AI systems Quantinuum.
Key Features:
- Addressing complex problems that cannot be solved with classical computing
- Applications in drug development, financial market forecasting, and real-time logistics optimization
- Helios system to be operational in mid-2025
Manufacturing applications:
- Molecular-level design of new materials
- Quantum optimization of complex manufacturing processes
- Innovative Development of Battery Technology
6. other important developments
ByteDance’s Seedream 4.0 (September 10): 2K output-ready AI image generation technology with 6 image reference consistency and natural language editing capabilities. Applicable for rapid prototyping and visualization of product designs in the manufacturing industry.
Anthropic’s $1.5 billion copyright settlement (Sept. 6): a landmark case on copyright issues for AI training data, providing guidance on managing legal risk in the implementation of AI in manufacturing.
Swiss Apertus Model (Sept. 4): a fully open-source large-scale language model for improving transparency and accessibility in the manufacturing industry.
Comprehensive application analysis for manufacturing
1. innovative optimization of production processes
The technologies presented in this issue will fundamentally change the production process in the manufacturing industry:
Real-time optimization: The complex problem-solving capabilities demonstrated by Google’s Gemini 2.5 enable real-time optimization of entire production lines. Adjustment tasks that previously relied on human experience and intuition can now be performed by AI with mathematical precision.
Evolution of Predictive Maintenance: SpikingBrain’s high-speed, power-saving processing capabilities make it feasible to continuously monitor the condition of manufacturing equipment and predict failures in advance at a realistic cost.
Automation of quality control: Developments in physical AI will enable AI to perform quality inspections that were previously performed visually by skilled technicians with greater accuracy than humans.
2. revolution in supply chain management
Global Optimization: Oracle’s massive cloud infrastructure enables supply chain optimization on a global scale. AI can manage the entire process from raw material procurement to final product delivery in an integrated manner.
Risk Prediction and Response: The computational power of quantum AI enables us to detect supply risks in advance and prepare alternatives that were previously unpredictable.
Accelerate new product development
Innovation in Materials Science: Quantum AI enables new materials design at the molecular level. This will greatly accelerate the development of lighter, stronger, and environmentally friendly alternative materials.
Streamlining the design process: Integrating AI-based image generation technology with 3D modeling can significantly shorten the time from product design to prototype production.
4. realization of sustainable manufacturing
Optimize energy efficiency: Power-saving AI technologies such as SpikingBrain can significantly reduce energy consumption throughout the manufacturing process. This is critical to achieving carbon neutral manufacturing.
Waste reduction: Precise demand forecasting and production planning with AI can minimize waste from overproduction.
5. workforce transformation and skills improvement
Evolution of Collaborative Robots: With the development of physical AI, collaboration between humans and robots will become more natural and efficient. The division of roles will become clearer: robots will be in charge of dangerous tasks, while humans will be in charge of tasks that require creative judgment.
Skills Sophistication: While traditional simple tasks will be automated, the demand for highly skilled personnel to manage AI systems, analyze data, and make strategic decisions will skyrocket.
Issues and Considerations
1. barriers to technology adoption
Size of initial investment: The introduction of these advanced AI technologies requires a substantial initial investment. Financing is a key issue, especially for small and medium-sized enterprises (SMEs).
Widening skills gap: Rapid advances in AI technology will increase the number of tasks that cannot be handled by traditional skill sets. Companies will need to implement proactive human resource development programs.
2. security and privacy
Data Protection: AI applications in the manufacturing industry involve the processing of vast amounts of confidential corporate data. It is essential to strengthen cyber security measures.
Intellectual Property Rights: As the Anthropic copyright settlement case demonstrates, the rights relationship for data used in AI training should be clearly defined.
3. regulation and standardization
Need for international standards: In the global manufacturing industry, there is an urgent need for international standardization regarding AI technology.
Ethical Considerations: It is important to ensure transparency and accountability of AI decision-making and consistency with human values.
Future Outlook
Short-term outlook (until the end of 2025)
- Commercial deployment of physical AI: More manufacturing companies begin to deploy physical AI, following the successes of Amazon, Foxconn, and others.
- Demonstration of Quantum AI: With Helios System in Operation, Manufacturing Industry Applications of Quantum AI are in Full Swing
- Widespread use of power-saving AI: Technologies such as SpikingBrain make AI processing commonplace in edge computing
Medium-term outlook (2026-2027)
- Fully Autonomous Factories: “Dark Factories” with Minimal Human Intervention
- Global Optimization: Production optimization on a global scale using Oracle-OpenAI infrastructure
- High-volume production of custom products: AI-based individual optimization for both efficiency in high-volume production and customization
Long-term outlook (after 2028)
- Industrial Applications of General Purpose Artificial Intelligence (AGI): Further development of the reasoning capabilities demonstrated by Google’s Gemini, AGI is being used in all areas of manufacturing.
- Full realization of circular economy: perfect recycling system with AI to achieve zero waste manufacturing
- Space Manufacturing: AI Technology Brings Manufacturing Activities in Space into Full Swing
summary
The advances in AI technology announced in the two weeks of September 2025 represent a true tipping point for the manufacturing industry: the demonstrated problem-solving capabilities of Google’s Gemini 2.5, the adaptive robotics of physical AI, the power-saving acceleration of China’s SpikingBrain, and the large-scale infrastructure of Oracle and OpenAI’s large-scale infrastructure building, each with the power to revolutionize a different aspect of manufacturing.
The combination of these technologies will cause the manufacturing industry to experience a fundamental transformation, including
- Super-efficient production system: AI-based full optimization for lean production
- Sustainable manufacturing: minimizing environmental impact through power-saving technology and precision control
- Highly customized products: meet individual needs while maintaining the efficiency of mass production
- Predictable manufacturing environment: anticipate and address failures, quality issues, and supply risks in advance
- Human-centered, high-value-added operations: Shift of human resources to operations that require creativity and strategic thinking
Successful manufacturing companies will not implement these technologies in isolation, but rather as an integrated ecosystem. In parallel with technology adoption, they must also proactively address issues such as human resource development, security measures, and regulatory compliance.
The September 2025 AI revolution is just the beginning. The manufacturing industry is now undergoing the most dramatic transformation in its history, and the companies that can adapt to this change will be the next generation of industry leaders.
Source List
- The Guardian – Google DeepMind claims ‘historic’ AI breakthrough in problem solving (September 17, 2025)
- World Economic Forum – Physical AI is changing manufacturing – here’s what the era of intelligent robotics looks like (September 9, 2025)
- The AI Track – China Unveils Brain-Inspired Model SpikingBrain1.0 Claiming 100x Speed Gains (September 9, 2025)
- The AI Track – Oracle Secures $30 Billion OpenAI Cloud Deal, Reshaping AI and Enterprise Infrastructure (September 10, 2025)
- Quantinuum – Quantinuum Announces Generative Quantum AI Breakthrough with Massive Commercial Potential (February 4, 2025)
- Reuters – AI set to transform global trade, says World Trade Organization report (17 September 2025)
- The AI Track – ByteDance Launches Seedream 4.0, Challenging Google DeepMinds Nano Banana in AI Image Generation (September 10, 2025)
- The AI Track – Anthropic will Pay $1.5 Billion in Landmark AI Book Piracy Settlement (September 6, 2025)
- The AI Track – Switzerland Releases Apertus, a National Open-Source AI Model (September 4, 2025)
- The AI Track – Albania Appoints AI Bot Minister to Fight Corruption in World First (September 12, 2025)
