Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Paradigm Secures $1.2 Billion Fund to Invest in AI and Robotics
Paradigm, a prominent investment firm based in San Francisco, has successfully raised $1.2 billion for a new venture fund aimed at expanding its investments into artificial intelligence and robotics. This fund represents a strategic shift for the firm, which has historically focused on crypto investments, and marks a significant increase from its previous $850 million fund announced in 2024. Paradigm is now managing approximately $11.9 billion in assets as of 2025. The expansion into AI and robotics is significant as these sectors are increasingly attracting venture capital, reflecting a broader trend in technology investment. Paradigm's new fund will not only continue to support digital assets but will also target opportunities in frontier technologies, indicating a shift in investment strategy to include emerging technologies beyond blockchain. This move aligns with the growing intersection of AI and crypto, particularly in areas like autonomous payments and programmable financial systems. Looking ahead, Paradigm's approach suggests a potential for innovation at the convergence of AI and crypto technologies. The firm aims to leverage its expertise in software and financial systems to explore new market opportunities. No further timeline was disclosed at the time of publication regarding specific investments or milestones for the new fund.
Industry 4.0 Conference to Take Place in Paris on June 23-24
On June 23 and 24, Paris Expo – Porte de Versailles will host the Tech For Industry Show, a new professional event focused on Industry 4.0 technologies. This gathering aims to highlight advancements in industrial technology and is expected to be a significant highlight on the industrial agenda. Robot-Magazine.fr is serving as an official partner for the event, which promises to attract industry professionals and showcase innovative solutions.
À la une IA Industrie Robotique AMR robots mobiles autonomes automatisation industrielle.
Dassault Systèmes vs Siemens vs PTC : qui gagne la bataille du digital twin ?
The digital twin technology is emerging as a cornerstone of the future industry, aiming to create accurate virtual representations of products, processes, or entire systems. This innovation enables real-time simulation, optimization, and prediction of behaviors. In this competitive landscape, three major players—Dassault Systèmes, Siemens, and PTC—are leading the charge in the battle for dominance in the digital twin market. The ongoing rivalry among these companies highlights the strategic importance of digital twins in enhancing operational efficiency and driving technological advancement. The article originally appeared in Robot Magazine, exploring the competitive dynamics shaping this transformative field.
À la une Actualités IA Industriel Robotique automatisation industrielle.
The Convergence in Perception Systems from Cars to Robots
Humanoid robots are increasingly being integrated into environments where they interact closely with humans, demonstrating the ability to navigate shared spaces and respond to unpredictable behaviors in real time. This advancement marks a significant step in the evolution of robotics, as these machines are designed to operate alongside people, enhancing their functionality and adaptability in everyday situations. The development is part of a broader trend in perception systems, which have seen improvements in both automotive and robotic technologies, allowing for more sophisticated interactions. As this technology continues to evolve, it holds the potential to transform various sectors by enabling robots to assist in tasks that require a nuanced understanding of human behavior and environmental dynamics.
Analog Devices: Architecting Trusted Mobility Analog Devices
After 40 Years in Auto Parts, This 'Shovel Seller' Unveils a Humanoid Robot
Hefei Dingli Kexing Intelligent Robot Co., a joint venture formed by prominent automotive parts manufacturers, has unveiled its first full-sized humanoid robot, marking a pivotal moment in the company's evolution. This launch signifies a strategic shift for the automotive giant as it expands into the robotics sector, emphasizing the growing importance of supply chain integration in the industry. The introduction of the humanoid robot not only showcases technological advancements but also reflects the increasing convergence of automotive and robotics technologies.
Humanoid Robots Robotics Automotive Parts AI Technology
Scott Walter: Why Humanoid Robots Just Need to Be "Good Enough"
Dr. Scott Walter, a leading figure in robotic technology, has dedicated the past 40 years to exploring the convergence of virtual design and physical reality. In a recent interview, he shared insights on the current state of robotics, particularly focusing on Tesla’s Optimus humanoid robot. Walter discussed the challenges surrounding robotic hands, referencing the "Fermi paradox" to illustrate the complexities of creating effective robotic manipulation. He also addressed prevalent misconceptions regarding the safety of home robots, emphasizing that the industry is now poised to tackle issues that have persisted since 1985. This evolution in robotics is attributed to advancements in technology and a growing understanding of human-robot interaction, suggesting a promising future for the field.
Scott Walter Interview
Top 5 Trends of the Industrial Robot Arm Industry in 2026
In 2026, the landscape of industrial automation and robotics is undergoing a transformative shift, moving from rigid machines to intelligent, adaptive systems. This evolution is driven by global manufacturing challenges, including labor shortages and the demand for hyper-personalization. Key advancements in connectivity and artificial intelligence are reshaping productivity and safety on factory floors. A major trend is the emergence of "self-evolving" robots that utilize generative AI to autonomously learn new tasks, minimizing the need for manual programming. Additionally, agentic AI empowers these machines to make informed decisions in complex environments, enhancing their ability to predict equipment failures and optimize operations in real-time. The convergence of Information Technology (IT) and Operational Technology (OT) is facilitating seamless data exchange between digital systems and physical robots. This integration allows for the creation of digital twins, enabling manufacturers to simulate production changes before implementation. Cloud connectivity has become standard, with nearly half of new deployments leveraging IoT technology for predictive maintenance. This capability allows robots to monitor their health and schedule repairs proactively, reducing unplanned downtime and long-term costs. Furthermore, advanced 2D and 3D vision systems are enhancing robots' capabilities, enabling them to perform high-speed quality inspections and adjust their behavior for safety around human workers. The shift towards modular and scalable automation is also notable, as manufacturers adopt flexible robot cells that simplify integration and facilitate quick changeovers. Leading this innovation is JAKA Robotics, whose JAKA A12 model exemplifies the future of flexible automation. With a 12 kg payload and a 1425 mm working radius, the JAKA A12 combines high performance with user-friendly deployment through a wireless software ecosystem, positioning itself as a key player in the evolving industrial landscape.
How a Melexis Collaboration is Working to Develop the Touch-Enabled Robots of the Future
Experts from various fields, including electronic hardware, software, embedded systems, mechanical robotics, and mechatronics, are collaborating to address the complex challenge of integrating feedback mechanisms, such as tactile sensors, with smart and adaptive control systems. This interdisciplinary effort aims to enhance the functionality and responsiveness of robotic systems. The initiative is gaining momentum as advancements in technology continue to evolve, particularly in the context of robotics and automation. By fostering collaboration among specialists, the project seeks to develop innovative solutions that improve the interaction between machines and their environments. This convergence of expertise is crucial for advancing the capabilities of intelligent systems, ultimately leading to more effective and efficient robotic applications across various industries.
Why Robots Are About to Change Everything AND WHY NOW
Recent advancements in artificial intelligence and robotics are ushering in a transformative era for the industry, a moment that experts have anticipated for decades. As AI technologies continue to evolve, they are increasingly being integrated into robotic systems, enhancing their capabilities and efficiency. This convergence is expected to revolutionize various sectors, including manufacturing, healthcare, and logistics, by automating complex tasks and improving precision. The developments are occurring in a landscape marked by rapid technological progress, with significant breakthroughs reported throughout 2023. Researchers and companies worldwide are collaborating to harness these innovations, aiming to create smarter, more adaptable robots that can operate alongside humans in diverse environments. The motivation behind this push is not only to streamline operations but also to address labor shortages and improve safety in hazardous work conditions. As the integration of AI and robotics accelerates, industry leaders are optimistic about the potential for these technologies to drive economic growth and enhance productivity. The ongoing research and development efforts are expected to lead to new applications and solutions that will further shape the future of work and society as a whole.
Dexterous Robots Move From Labs to Industry With NSF Support
In July, the National Science Foundation (NSF) held the kickoff meeting for phase two of its Convergence Accelerator program in Pittsburgh, where participants engaged in knowledge transfer, strategic discussions, planning, and demonstrations. Researchers from Carnegie Mellon University are spearheading efforts to develop advanced robotic hands aimed at enhancing applications in health, agriculture, and manufacturing. This initiative will receive further backing from the U.S. government, facilitating the transition of these innovative robotic technologies from laboratory settings to real-world industrial use.
Announcements Research
When Commercial Drone Technology Meets Defense: A Closer Look at Civil–Military Integration
A recent report from the Foundation for Defense of Democracies (FDD) underscores the significant convergence of commercial drone technology and military applications, highlighting the evolving landscape of the drone industry. This analysis, titled “China’s War Wolves,” emphasizes how shared innovation pipelines are influencing both commercial markets and defense capabilities. The report draws attention to the implications of civil-military integration, particularly in the context of national security and technological advancement. As the demand for drones continues to rise, understanding the interplay between civilian and military uses becomes increasingly critical. The findings are particularly relevant as nations seek to enhance their defense strategies while leveraging advancements in commercial technology.
Applications Defense defense DL Exclusive Drone News Drone News Feeds
Variable Launches DMuon Optimizer to Improve Distributed Muon Model Infrastructure Efficiency by 30%
Variable Robotics has introduced the DMuon optimizer, enhancing the distributed Muon model infrastructure's efficiency by approximately 30%. This new optimizer addresses the additional computational and communication costs associated with using Muon in distributed training, which previously resulted in an end-to-end step time 2.2 times longer than AdamW. The significance of DMuon lies in its ability to maintain the faster convergence benefits of the Muon optimizer while reducing the end-to-end step time to just 1.02 times that of AdamW. This improvement is achieved through fine-grained communication optimization, computation-aware load balancing, and a high-performance kernel system, making DMuon a viable option for embodied model training without requiring changes to parameter update rules or training frameworks. Looking ahead, DMuon is expected to become a new default choice for embodied model training, as it effectively mitigates the redundant computations and communication overhead that previously hindered Muon's performance in distributed environments. No further timeline was disclosed at the time of publication.
Neural Network Optimization Distributed Training Machine Learning Infrastructure AI Models
Smarter Automation with Industrial PCs and HMIs
In a recent episode of the Automation World podcast, host Chris McNamara engaged with Chris Barber, product marketing manager at Phoenix Contact, to explore the evolving landscape of industrial automation. The discussion, which aired on June 24, 2026, delved into the transition towards web-based Human-Machine Interfaces (HMIs), industrial PCs, edge computing, and software-defined control systems. Barber highlighted Phoenix Contact’s innovative PLCnext approach, which integrates traditional operational technology (OT) programming with IT-friendly tools, aiming to simplify integration, enhance real-time processing, and bridge the gap between IT and OT. Barber provided a practical example from the water-wastewater sector, illustrating how edge PCs can significantly improve local alarm handling and data reliability. The conversation also touched on Phoenix Contact’s strengths in hardware and customer support, as well as emerging trends such as cloud-edge convergence and the development of smarter, connected systems that facilitate easier deployment. This insightful dialogue underscores the ongoing advancements in automation technology and its implications for various industries.
Sponsored
AI Framework Improves Learning on Edge Devices
Recent advancements in federated learning technology have made it possible to implement this innovative approach on edge devices, significantly enhancing efficiency in data processing. A new framework, known as FTTE, has been developed to optimize the training process, achieving a remarkable reduction in training memory usage by 80% and a decrease in communication load by 69%. This breakthrough not only streamlines the training process but also ensures rapid convergence, making it a game-changer for organizations looking to leverage edge computing for machine learning applications. The developments were reported in October 2023, highlighting the growing importance of federated learning in managing data privacy and resource constraints in various industries.
Robotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
