Percepto is an Israeli autonomous inspection technology company deploying drone-in-a-box solutions for industrial infrastructure monitoring. Its Percepto Air portfolio and AIM software platform provide automated site surveillance, AI-driven data analysis, and remote inspection for energy, utilities, and industrial facilities.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
At the WAIC 2023, the AI and robotics sectors have become increasingly intertwined, with robotics taking center stage. Various robotic technologies, including humanoid and dual-arm robots, were prominently displayed, showcasing their capabilities and advancements. This year marked a shift in focus from generative AI to the robotics industry, highlighting the evolution of robots and their functionalities. The event revealed a divergence among robotics companies. Some continue to emphasize the capabilities of robots, demonstrating their speed, precision, and fluidity in performing tasks, which captivates public and investor interest. In contrast, companies like Tianji focus on the stability and safety of robotic operations, emphasizing the interaction between AI models and physical environments, thus addressing the practical applications of robotics in real-world scenarios. This shift in focus from capability to foundational infrastructure signifies a critical transition in the robotics industry. As companies recognize that the limitations to robotics deployment may lie in the supporting infrastructure rather than the robots themselves, the industry is poised for a redefinition of what it means for robots to operate effectively in various environments, including factories and homes. No further timeline was disclosed at the time of publication.
Robotics AI Industrial Automation Physical IntelligenceAt the 2026 World Artificial Intelligence Conference in Shanghai, Insight AI launched the world's first embodied semantic intelligence system, insightOS Semantic. This system represents a pivotal shift in the embodied intelligence industry, moving from mere demonstration capabilities to practical applications in real-world scenarios. The significance of this development lies in its comprehensive approach to embodied intelligence, which now requires not only technical prowess but also a robust operating system, scenario validation, and a thriving developer ecosystem. Insight AI aims to address the critical challenges of understanding, adaptability, and evolution in robotics, which have hindered the large-scale deployment of embodied systems. Looking ahead, Insight AI's insightOS Semantic is designed to facilitate seamless communication between humans and robots, enabling task execution through natural language. The system's architecture integrates semantic understanding with physical operation capabilities, promising to enhance the efficiency and intelligence of robots in dynamic environments. No further timeline was disclosed at the time of publication.
Embodied Intelligence Robotic Systems AI Technology Natural Language ProcessingOn July 19, during the 2026 World Artificial Intelligence Conference, Yao Maoqing, Senior Vice President and President of the Embodied Business Division at Zhiyuan, shared insights on the technological pathways for scaling physical AI. Zhiyuan has developed a three-phase training architecture of 'pre-training, post-training, and continuous learning' to advance its VLA and WAM technology routes towards the unified World Reasoning Action Model (WRAM). The integration of data is facilitated by Mifeng Technology, which utilizes the MEgo series of collection terminals and the MEgo Engine governance platform to create a comprehensive physical AI data infrastructure. This infrastructure supports data collection, governance, training, and deployment feedback, ensuring that real-world data continuously enhances model evolution. The collaborative model and data iteration system has already been validated in real industrial scenarios. Yao emphasized that 'models determine the starting point, while data defines the outcome.' He expressed the ambition of Zhiyuan and Mifeng to collaborate with the global academic community, industry, and developer ecosystem to accelerate the evolution of physical AI in real-world applications. No further timeline was disclosed at the time of publication.
Physical AI Data Infrastructure Machine Learning AI DevelopmentOn July 17, 2026, the World Artificial Intelligence Conference (WAIC) commenced in Shanghai, where ChipMing unveiled its series of 3D vision AI modules designed for embodied intelligence and physical AI scenarios. The modules demonstrated core functionalities such as pose estimation and instance segmentation using the self-developed spatial intelligent chip running YOLO26, alongside a 3D virtual safety zone application that integrates depth perception and AI recognition technologies. The significance of these modules lies in their ability to operate reliably in industrial environments, with a temperature range of -10℃ to 50℃. They support USB 3.0 and GMSL 2.0 protocols, ensuring high bandwidth and long-distance transmission capabilities. The built-in spatial intelligent chip allows for local processing of data, enhancing privacy and reliability by keeping sensitive information on-device, which is crucial for applications in security, healthcare, and industrial quality inspection. Looking ahead, the 3D virtual safety zone demo showcased at WAIC attracted considerable attention, highlighting the modules' capabilities in object classification and selective alarm systems. Users can choose from various module models based on specific use cases, ensuring ease of installation and strong feasibility for engineering applications. No further timeline was disclosed at the time of publication.
3D Vision AI Embodied Intelligence Industrial Automation AI TechnologyAt the 2026 WAIC, a notable shift in robotics was observed as manufacturers increasingly focused on developing dexterous hands. Over the past two years, the industry has seen a surge in the complexity of these hands, with degrees of freedom increasing from six to twelve, sixteen, or even more. The ability of a robotic hand to perform tasks such as solving a Rubik's Cube or threading a needle has become a key benchmark for technological capability. As more dexterous hands demonstrate impressive capabilities, the industry must now address critical questions about their operational continuity, scalability, repairability, and the data they generate to enhance future performance. Companies like Aoyi Technology are expanding their product boundaries beyond mere actuators to include tactile-enabled devices like ROHand and OpenArm, integrating data collection and training tools into a cohesive system. This evolution signifies a shift from merely creating human-like hands to developing hands that can engage in a robotic learning loop. The industry's future hinges on whether these hands will become high-end toys or genuine industrial products, with reliability emerging as a core performance metric alongside flexibility and load capacity.
Dexterous Hands Robotics Technology Industrial Automation Sensor TechnologyFrom July 17 to 20, 2026, the World Artificial Intelligence Conference (WAIC 2026) took place in Shanghai, showcasing significant advancements in the AI sector. Luming Robotics presented its latest embodied intelligence practices, emphasizing real-world applications and industrial collaboration. The company introduced its Prime R0 embodied brain and data collection capabilities, demonstrating a comprehensive technology system that spans 'scenarios, data, and models.' The importance of this event lies in the shift towards practical applications of embodied intelligence, moving beyond mere technical demonstrations. Luming Robotics highlighted the three developmental stages of embodied intelligence: industrial, commercial, and domestic. The industrial sector, characterized by clear task boundaries and quantifiable ROI, serves as the optimal starting point for scaling and iterating embodied intelligence technologies. Looking ahead, Luming Robotics announced a collaboration with Mitsubishi Electric Automation (China) to develop industrial assembly scenarios, marking a significant step towards autonomous task understanding and environmental adaptation. No further timeline was disclosed at the time of publication.
Embodied Intelligence Industrial Robotics Data Collection AI TechnologyBiren, a Shanghai-based startup, is pioneering optical technology to connect thousands of AI accelerators into unified computing systems. As AI models grow increasingly complex, the demand for efficient interconnectivity among GPUs has intensified, with traditional copper connections reaching their limits. Biren's innovative near-packaged optics (NPO) architecture aims to support clusters of up to 1,024 AI accelerator cards, significantly enhancing computing capabilities. This advancement is crucial for AI infrastructure companies striving to meet the needs of models with trillions of parameters. Biren's approach addresses the scalability challenges faced by conventional server architectures, which typically cap at around 128 GPUs. By positioning optical fibers closer to chips, the company enhances bandwidth and data transmission efficiency, positioning itself against competitors like MetaX and Alibaba. Looking ahead, Biren is testing its NPO interconnect system while also developing an orthogonal hardware architecture in collaboration with ZTE. Although the semiconductor industry is still in the early stages of optical interconnect technology, widespread adoption is projected for around 2028, contingent on further advancements and real-world validation of these systems.
AI and RoboticsResearchers from MIT, IBM, and Red Hat have introduced the Geometric Inference Feedback Tuning (GIFT) framework, which enhances AI's ability to convert 2D images into functional CAD programs. This innovation significantly improves design accuracy while reducing inference computation by approximately 80%. The GIFT framework addresses the challenge of limited high-quality CAD training data by utilizing the AI's own mistakes as a learning tool. The importance of this development lies in its potential to streamline the CAD design process, which is often hindered by the need for extensive datasets linking images to CAD programs. By focusing on 'near-misses'—outputs that are close to correct—the GIFT framework provides valuable insights into the AI's understanding, ultimately leading to better training examples and more reliable designs. Looking ahead, the GIFT framework's dual techniques, including GIFT-REJECT, promise to further refine AI-generated CAD outputs. As the research progresses, the effectiveness of GIFT in real-world applications will be closely monitored, particularly in industries reliant on precise CAD designs, such as aerospace and automotive engineering. No further timeline was disclosed at the time of publication.
AI and RoboticsFaraday Future's AI subsidiary, FFAI, announced its accelerated expansion into commercial robotics at Automate 2026 in Chicago. The company showcased its 'one brain, multiple forms' robotics platform and revealed that June robot shipments are expected to exceed 100 units, bringing total first-half deliveries to over 220 units, surpassing its initial target ahead of schedule. This milestone is significant as it marks FFAI's transition from an education-focused robotics business to industrial automation, targeting commercial deployments across manufacturing, logistics, and research. The company presented a range of robotics products, including the All-New Futurist humanoid robot and the FF Faber mobile manipulator series, highlighting its commitment to integrating advanced AI technologies into various applications. Looking ahead, FFAI outlined a broader strategy focused on an open embodied AI ecosystem, which includes its EAI Brain software platform and an EAI Data Factory for operational data collection. No further timeline was disclosed at the time of publication.
Artificial Intelligence Events News ai All-New Futurist Automate 2026Fujitsu has initiated a partnership with Japanese robotics firms Fanuc, Yaskawa Electric, and Kawasaki Heavy Industries to advance the development and deployment of physical AI in sectors such as manufacturing, logistics, and healthcare. This collaboration will leverage Nvidia's physical AI technologies to create a collaborative control platform that connects digital systems with robots and physical equipment. The initiative aims to accelerate the adoption of physical AI, addressing challenges like labor shortages and an aging workforce while enhancing global competitiveness. The platform will optimize production planning in manufacturing, automate material handling in logistics, and improve healthcare operations by automating the transport of medical supplies and assisting with patient interactions. Fujitsu plans to develop an open collaborative control platform that integrates AI, robotics, and data analysis technologies, ensuring interoperability and addressing cybersecurity concerns. No further timeline was disclosed at the time of publication.
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