Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Méca-Précis utilizes robotic measurement cell to eliminate inspection bottlenecks
French precision engineering firm Méca-Précis has implemented an automated part inspection system to enhance efficiency in its operations. The new robotic measurement cell integrates a coordinate measuring machine (CMM) from Mitutoyo with automation technology developed by Engineering Data. This advancement comes in response to growing production volumes, which had turned traditional inspection processes into a bottleneck, particularly for clients in the aerospace and space sectors that demand high precision and reliability. The automation aims to streamline the inspection workflow, ensuring that quality control keeps pace with increased manufacturing demands.
Engineering Robotics advanced manufacturing aerospace components aerospace manufacturing automated inspection
SpaceX's Starmind Faces Feasibility Challenges for 1 Million Satellite Deployment
On January 30, 2026, SpaceX submitted a request to the FCC to launch up to 1 million satellites as part of its Starmind orbital compute constellation. This ambitious plan is unprecedented, as the total number of satellites ever launched globally is in the low tens of thousands. The proposal seeks a waiver from standard deployment milestones, citing reliance on the Starship's full reusability for success. The significance of this request lies in the technical and logistical challenges it presents. Experts warn that low Earth orbit may not support the proposed number of active satellites without risking a debris cascade. SpaceX's own IPO prospectus acknowledges unresolved dependencies related to Starship's launch cadence and reusability, which are critical for the orbital AI compute strategy. Looking ahead, the timeline for achieving the necessary launch cadence and manufacturing capacity remains uncertain. SpaceX's Gigasat facility in Texas aims for volume production by late 2027, but this would require unprecedented output levels. No further timeline was disclosed at the time of publication, leaving the feasibility of the Starmind project in question.
SpaceX Unveils AI1 Satellite Specs for Starmind Constellation with Key Thermal Challenges
SpaceX has introduced the AI1 satellite, the inaugural component of its Starmind constellation, which stands 20 meters tall and has a wingspan of 70 meters. This orbital compute node is designed to deliver computing power equivalent to one NVIDIA GB300 server rack, utilizing a unique cooling system with deployable liquid radiators. The satellite's specifications were revealed during a presentation on June 8, 2026, ahead of SpaceX's IPO. The significance of the AI1 satellite lies in its role as a compute platform rather than a traditional satellite, focusing on running AI inference workloads. The satellite's cooling system, which is critical for its operation in the vacuum of space, is designed to reject heat through infrared radiation. However, independent engineers have raised concerns about the feasibility of the thermal and mass claims made by SpaceX, suggesting that the cooling requirements may exceed practical limits. Looking ahead, SpaceX plans to launch two AI1 prototypes in early 2027, with full-scale production expected to commence later that year at its Gigasat facility in Bastrop, Texas. The ongoing debate regarding the satellite's thermal management capabilities will be crucial to monitor as the project progresses, with no further timeline disclosed at the time of publication.
SpaceX Launches Starmind Project for 1 Million AI Satellites by 2028
SpaceX has officially named its orbital AI infrastructure project 'Starmind,' which aims to deploy a constellation of up to 1 million satellites. This initiative, confirmed by Elon Musk on June 22, 2026, will enable AI inference directly in space, utilizing solar energy rather than terrestrial power sources. The first satellite, designated AI1, was unveiled on June 8, 2026, and is designed to operate in sun-synchronous orbits. The significance of Starmind lies in its potential to overcome the limitations faced by ground-based data centers, such as land, power, and water constraints. By running AI computations in orbit, Starmind can provide a more efficient solution to the growing demand for AI computing power. The project leverages the existing Starlink infrastructure for data transmission, distinguishing its function from Starlink's internet relay capabilities. Looking ahead, SpaceX plans to begin hardware deployment with the AI1 satellite, while full-scale production and deployment of the satellite constellation are targeted for 2028. As of now, no Starmind satellites have been launched, and further engineering challenges remain to be addressed, particularly regarding the scalability of the satellite design.
How Melbourne’s AI and Data Center Flywheel Is Accelerating Research Innovation
Melbourne is solidifying its status as a global hub for artificial intelligence (AI) research and advanced engineering, driven by significant investments in infrastructure and a growing concentration of talent. The city, renowned for hosting major events like the Australian Open and Formula 1 Grand Prix, is now leveraging its organizational capabilities to support large-scale compute and data-intensive research. In February 2026, Monash University unveiled MAVERIC, Australia's largest university-based AI supercomputer, developed in collaboration with NVIDIA and Dell Technologies. This state-of-the-art facility is designed to enhance medical research, enabling Australian scientists to work with sensitive datasets securely. The supercomputer exemplifies Melbourne's commitment to fostering cross-disciplinary collaborations and advancing research in fields such as cancer detection and drug discovery. Melbourne's infrastructure is further bolstered by the expansion of data centers, including CDC Data Centres' new campus, which will provide over 800 megawatts of digital capacity essential for AI workloads. The city's strategic investments, including a AUD $2 billion AI infrastructure hub in Fishermans Bend, are positioning it as a national leader in high-performance AI. Moreover, Melbourne's selection to host international technology conferences, such as Data Center World Australia and The AI Summit Australia in September 2026, underscores its growing influence in the global AI landscape. These events facilitate knowledge transfer and collaboration among researchers, reinforcing Melbourne's role as a key player in the future of AI and data-driven research.
Australia Artificial-intelligence Research-centers Applied-ai Conferences
Oceaneering Expands Vision™ Platform with Subsea Module for Engineering‑Grade Integrity Visualization
Oceaneering International, Inc. has unveiled Vision™ Subsea, a new module integrated into its cloud-based Vision™ 3D data visualization software platform, developed by its subsidiary GDi. Announced today, this innovative module provides engineers with access to engineering-grade point cloud data collected during remotely operated vehicle (ROV) operations. By offering a measurable and contextual view of subsea asset integrity, Vision™ Subsea enhances the ability to identify anomalies, conduct dimensional checks, and plan interventions effectively. This advancement aims to improve the safety and efficiency of subsea operations, addressing the growing need for precise monitoring and maintenance of underwater infrastructure.
oceaneering gdi vision™ platform subsea module integrity visualization
Application engineering for assembly systems is quietly becoming manufacturing’s biggest competitive edge
In a significant shift within the manufacturing sector, companies are increasingly focusing on application engineering to enhance assembly systems. This evolution is driven by the need for higher productivity and reduced error rates on the factory floor. Leading the charge is Atlas Copco, a prominent player in the industry, which is fully embracing this transformation. The emphasis is now on not just the machines themselves, but also on the engineering that connects and adjusts these machines in real-time to align with operational demands. As factories strive to optimize their processes, the integration of advanced engineering techniques is becoming essential for success in a competitive landscape.
Engineering Manufacturing application engineering assembly line automation assembly systems atlas copco
MIT Develops GIFT Framework to Enhance CAD Design Accuracy Using AI Failures
Researchers 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 Robotics
Jiying Technology Launches First Zero-Shot Generalizable Physics Model for Engineering Simulations
Jiying Technology has unveiled its Jiying 2.0 physics foundation model, which is capable of zero-shot generalization across various geometries, materials, and boundary conditions. This model represents a significant advancement in physics AI, particularly for engineering simulations, and was announced in October 2023. The introduction of the Jiying 2.0 model is crucial as it allows engineers to simulate complex physical scenarios without the need for extensive retraining on specific datasets. This capability can enhance efficiency and reduce the time required for simulations, making it a valuable tool in engineering design and analysis. Looking ahead, industry professionals will be keen to observe how the adoption of the Jiying 2.0 model influences engineering practices and simulation accuracy. No further timeline was disclosed at the time of publication regarding additional features or updates to the model.
Technology
ABB Robotics and Psyonic use human-generated data to advance robotic dexterity
ABB Robotics is partnering with California-based bionics firm Psyonic to enhance robotic gripping and dexterity, addressing a significant challenge in the industry. This collaboration aims to leverage real-world manipulation data derived from human prosthetic use, which could lead to a reduction in engineering time by as much as 30%. The initiative involves integrating the Psyonic Ability Hand with ABB's GoFa robotic arm, creating a more efficient and adaptable solution for various applications. This innovative approach seeks to improve the functionality of robotic systems, making them more effective in handling tasks that require precision and flexibility.
Components Design Engineering abb robotics ai robotics automation news
ABB Robotics and PSYONIC Use Human-Generated Data to Advance Robotic Dexterity
ABB Robotics has partnered with California-based bionics company PSYONIC to enhance robotic dexterity and grasping capabilities by utilizing human-generated data from prosthetic use. Announced on June 16, 2026, this collaboration aims to address the significant challenge of replicating human-like dexterity in industrial robotics, which is essential for the development of Autonomous Versatile Robotics (AVR™). By integrating the PSYONIC Ability Hand with ABB's GoFa™ collaborative robot, the two companies will explore how real-world manipulation data can train robots to perform delicate tasks that are typically difficult to automate. This initiative is expected to reduce engineering time by up to 30% and improve productivity, flexibility, and workplace safety across various industries, including automotive, aerospace, packaging, logistics, and life sciences. Marc Segura, President of ABB Robotics, emphasized the importance of bridging the gap between human and robotic dexterity to enable robots to learn and interact with their environments more intuitively. Dr. Aadeel Akhtar, Founder and CEO of PSYONIC, highlighted that the collaboration will leverage high-fidelity data on movement and grip force to enhance robotic performance in complex tasks. The GoFa™ robot will provide the precision necessary for industrial applications, ensuring consistent execution of intricate movements, which is crucial for handling fragile or irregular objects. This partnership represents a significant step towards advancing physical AI in robotics, allowing for more effective collaboration between humans and machines.
Allient Inc. to Present at Upcoming Webinar on Engineering Thermally-Optimized Joints for Humanoids
A webinar is set to address the significant challenges associated with humanoid joint design, emphasizing the importance of interpreting motor data within a system-level context rather than adhering strictly to standard specifications. Scheduled for an upcoming date, this event will take place online, allowing participants from various locations to engage in discussions. The session aims to provide insights into practical engineering strategies for selecting motors and optimizing performance specifically for humanoid and advanced robotics applications. The focus will be on achieving reliable and thermally efficient performance, which is crucial for the advancement of robotics technology.
BANNER ENGINEERING - Available now at Mouser: vibration monitoring sensors
Banner Engineering has introduced its Q45x sensors, designed to enhance predictive maintenance for industrial equipment by providing high-resolution, three-axis vibration data. These innovative sensors, which are battery-powered and capable of operating for several years without the need for wiring, facilitate easy installation and scalability across various assets. The Q45x sensors utilize integrated high-frequency enveloping (HFE) technology to detect early-stage faults, such as bearing wear and lubrication issues, thereby improving diagnostic accuracy even in noisy environments. With IP67-rated enclosures and wireless connectivity through Sure Cross networks, these sensors ensure reliable condition monitoring in challenging industrial settings while minimizing downtime and simplifying maintenance processes.
Design Around the Data: Sunday Robotics Reveals Why They Built 100 Gloves Before One Robot
In an exclusive interview, Scott Walter, a leader at Sunday Robotics, discussed the company's innovative approach to robotics engineering, emphasizing their "data-first" philosophy that guided the development of their latest robot, Memo. This design strategy prioritizes the training pipeline, ensuring that the robot's capabilities are built around the data it processes rather than adapting the data to fit a pre-existing framework. The insights shared during the interview highlight Sunday Robotics' commitment to leveraging data effectively to enhance robotic functionality and performance. This approach marks a significant shift in how robotics can be developed, aiming to create more efficient and intelligent machines.
Scott Walter Sunday Robotics Memo
As AI Reshapes Global Energy Systems, Melbourne Leads Through Engineering Collaboration
As artificial intelligence (AI) rapidly expands, it is driving a significant increase in global electricity demand, presenting urgent challenges for energy systems. Melbourne, Australia, is positioning itself as a leader in addressing these issues, with a focus on the infrastructure necessary to support AI's growth. By 2035, data centers in Australia are expected to consume up to 11 percent of the nation's electricity, raising concerns about generation and system reliability. The University of Melbourne is at the forefront of this initiative, with interdisciplinary research aimed at developing energy systems that can meet the demands of AI. The Melbourne Energy Institute is exploring how various energy technologies interact, while facilities like the Smart Grid Lab allow for real-time simulations of power systems. This integrated approach is essential for designing resilient and efficient energy systems that can adapt to new patterns of demand. Victoria's advanced energy ecosystem, which includes renewable generation and battery storage, is crucial for balancing digital growth with sustainability. The collaboration between researchers, industry, and policymakers is vital for creating future energy systems that are affordable and resilient. Looking ahead, Melbourne will host the IEEE PES Generation Transmission and Distribution Asia 2027 Conference, bringing together global experts to address the evolving challenges in power systems. This event underscores Melbourne's commitment to fostering international collaboration and innovation in energy solutions, reinforcing its role as a key player in the global energy transition.
Artificial-intelligence Australia Energy-systems University-of-melbourne Ai-data-centers Power-grid
Smooth Motor Advances Across Robotics and Intelligent Automation Industries Through 30 Years of Rapid Engineering Response
As product development cycles shorten and system complexity increases, the industry faces growing demands for efficient validation, long-term reliability, and cost control. This trend has emerged as companies strive to meet the evolving expectations of consumers and stakeholders. The pressure to innovate rapidly while ensuring quality and affordability has prompted organizations to adopt new strategies and technologies. By leveraging advanced data analytics and streamlined processes, businesses aim to enhance their product offerings and maintain competitiveness in a fast-paced market. The ongoing shift underscores the necessity for adaptability and efficiency in an environment where both time and resources are limited.
Into the Omniverse: How Industrial AI and Digital Twins Accelerate Design, Engineering and Manufacturing Across Industries
Companies across various industries are increasingly leveraging industrial AI, digital twins, AI physics, and accelerated AI infrastructure to enhance their design, simulation, and optimization processes. This technological shift allows organizations to refine products, processes, and facilities in a virtual environment before actual construction begins. By adopting these advanced tools, businesses aim to improve efficiency, reduce costs, and accelerate time-to-market for new innovations. The integration of these technologies is seen as a crucial step in staying competitive in a rapidly evolving market, enabling firms to make data-driven decisions and optimize their operations effectively.
All-in-one Engineering Suite for next-level digital manufacturing
The iiQWorks software platform has emerged as a pivotal tool in the automation sector, facilitating comprehensive support for the entire automation process and ensuring efficient data exchange throughout all phases of planning and production. By leveraging digital twin technology, the platform enhances the ease and speed of robot operations. This innovative approach includes features such as offline programming and virtual commissioning, which are designed to align with the principles of Industry 4.0. As industries increasingly adopt these advanced automation solutions, iiQWorks is positioned to play a crucial role in transforming manufacturing processes and improving operational efficiency.
A Novel Global Path Planning Algorithm for Underwater Vehicle Engineering Applications
A recent study published in the Journal of Field Robotics has unveiled significant advancements in robotic technology aimed at enhancing agricultural practices. Researchers from various institutions collaborated to develop a new robotic system designed to improve crop monitoring and management. Conducted over the summer of 2023, the project took place in various agricultural settings across the Midwest, where the team tested the system's capabilities in real-world conditions. The motivation behind this initiative stems from the increasing need for efficient farming solutions that can address labor shortages and optimize resource use. By integrating advanced sensors and artificial intelligence, the robotic system is capable of analyzing soil health, monitoring plant growth, and identifying pest infestations more effectively than traditional methods. The research team employed a series of field tests to evaluate the robot's performance, collecting data on its accuracy and efficiency in various agricultural tasks. The results indicate that the robotic system not only enhances productivity but also reduces the environmental impact of farming practices. This innovative approach represents a significant step forward in the field of agricultural robotics, promising to support farmers in meeting the challenges of modern agriculture while promoting sustainable practices. The findings are expected to influence future developments in the sector, paving the way for broader adoption of robotic technologies in farming.
RESEARCH ARTICLE
MIT and Toyota Develop SceneSmith to Enhance Robot Training with AI-Generated Environments
MIT and the Toyota Research Institute have introduced SceneSmith, a system that utilizes AI agents to create realistic 3D environments for robot training. This innovation addresses the significant challenge of generating diverse simulation content, which is crucial for teaching robots various tasks in a cost-effective manner. The SceneSmith system employs three AI agents, leveraging the advanced vision-language model GPT-5.2, to design intricate indoor scenes. These environments, featuring up to six times more objects than previous methods, allow robots to practice skills in a rich virtual playground, ultimately reducing the need for extensive real-world testing. As the research progresses, the effectiveness of these AI-generated environments will be closely monitored. The team has already demonstrated that robots can successfully navigate and perform tasks in these virtual settings, indicating a promising future for robotic training methodologies. No further timeline was disclosed at the time of publication.
Research Robotics Artificial intelligence Simulation Computer science and technology Machine learning
Managing traffic in space
Associate Professor Richard Linares is addressing the growing challenge of satellite navigation in congested orbits. As the number of satellites in space continues to rise, the risk of collisions increases, making safe navigation crucial for space operations. Linares, an expert in aerospace engineering, is developing innovative strategies and technologies to enhance the safety and efficiency of satellite movements. His work is particularly timely, given the rapid expansion of satellite constellations and the increasing interest in space exploration and commercial ventures. By leveraging advanced algorithms and data analysis, Linares aims to create systems that can predict potential collisions and facilitate safer maneuvering of satellites in crowded orbital paths. This initiative not only aims to protect existing satellites but also to ensure the sustainability of space activities for future generations.
Profile Faculty Satellites Pollution Aeronautical and astronautical engineering automation
DaxAI Robot Secures Major Funding and Unveils Innovations at WAIC 2026
In 2025, Zhu Xiaohu, a prominent partner at Jinsha River Venture Capital, announced a significant exit from humanoid robot companies, causing a stir in the investment community. However, he has now led a new funding round for DaxAI Robot, which has quickly raised hundreds of millions in just one year. This resurgence highlights a renewed confidence in the robotics sector. DaxAI Robot showcased its advancements at WAIC 2026, presenting four major achievements including the DaxBrain-WM (Dualis) world model and a range of all-terrain robotic products. The company emphasizes a holistic approach to embodied intelligence, integrating both cognitive and operational capabilities to enhance robotic performance in real-world applications. Looking ahead, DaxAI Robot's innovative technologies and strategic data engineering practices position it for significant growth in the robotics market. The company's ability to adapt across various environments and its focus on practical applications will be crucial as it navigates future challenges and opportunities in the industry. No further timeline was disclosed at the time of publication.
Robotics AI Embodied Intelligence Consumer Technology
ChipMing Launches Advanced 3D Vision AI Modules at WAIC 2026 in Shanghai
On 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 Technology
Qingyan Precision Secures Funding to Drive Physical AI Infrastructure Development
Qingyan Precision, a spin-off from Tsinghua University, has successfully secured hundreds of millions in its latest funding round to bolster its advancements in physical artificial intelligence. The company is dedicated to revolutionizing automotive testing by developing a comprehensive engineering system that gathers and analyzes real-world data. With more than 2,000 data collection nodes already in operation, Qingyan Precision is positioning itself as a significant contributor to the industrial AI sector. This funding will enable the firm to enhance data-driven decision-making processes within the manufacturing industry, further establishing its role in the evolving landscape of technology and engineering.
Physical AI Industrial Automation Data Infrastructure Engineering Systems
NatPower and Tesla Strike 25 GWh European Battery Storage Deal
NatPower has entered into a multi-year agreement with Tesla to supply and deploy over 25 gigawatt-hours of battery energy storage systems in European markets, with initial projects set for Italy and the United Kingdom. Announced on June 23, 2026, the partnership will see Tesla provide its Megapack technology, along with engineering, procurement, construction services, and energy trading optimization via its Autobidder platform. The projects, which will be owned and operated by NatPower, aim to streamline project development, financing, construction, and energy trading, facilitating large-scale battery deployment. The first phase includes five projects and is part of a larger initiative targeting over 100 GWh of storage capacity. NatPower anticipates that the full program could yield between $4 billion and $5 billion in construction value and generate over $15 billion in revenue over two decades. This agreement underscores the increasing significance of large-scale energy storage in Europe, driven by rising electricity demand, renewable energy integration, and the growth of data centers. As Europe seeks to enhance grid reliability and meet decarbonization goals, substantial storage additions will be necessary in the coming years. Tesla has established itself as a leading supplier of utility-scale battery systems, while NatPower continues to expand its role in energy infrastructure development. The storage assets from this agreement will provide essential grid balancing services and support electricity-intensive customers, including industrial facilities and data centers. NatPower CEO Fabrizio Zago emphasized the shift towards large-scale execution, while Tesla Energy Vice President Mike Snyder highlighted the integration of Tesla's capabilities to expedite battery deployments across Europe.
36Kr Exclusive: Four Key Propositions for ByteDance's AI by 2026
ByteDance is setting ambitious goals for its AI initiatives in 2026, focusing on four key areas. The company aims to enhance world model training, targeting performance levels comparable to Google's leading model, Genie 3, by the end of the year. Additionally, ByteDance plans to maintain its leadership in video models while exploring new avenues like dynamic generation. The company is also committed to strengthening its coding capabilities, emphasizing the importance of data feedback and evaluation to improve agent performance, particularly in office applications. Despite recent advancements, including the launch of Seed 2.0 and Seedance 2.0, ByteDance faces challenges in the world model arena, having entered the field later than competitors. The company established a research group in 2025 to explore visual-language-action models and has since set a clear goal for world model development. However, internal assessments indicate that performance still lags behind global standards by approximately 10%. In parallel, ByteDance is accelerating the commercialization of its Doubao platform, which has seen a surge in daily active users, reaching 200 million. The company plans to introduce paid features and enhance its offerings for professional users, particularly in sectors like finance and law. Doubao's strategy includes differentiating itself in the crowded AI tools market and expanding its presence internationally, with a focus on small language markets. As ByteDance navigates these challenges, it aims to leverage its engineering expertise and data resources to emerge as a leader in the evolving AI landscape.
Robotiq launches AI platform to automate robotic workcell integration
Robotiq has launched IQ, an innovative AI-enabled platform aimed at streamlining the integration of robotic Workcells. This new technology is designed to accelerate the transition from traditional, manual integration processes that rely heavily on expert input to a more automated and efficient system. By capturing unstructured data from automation projects and coordinating engineering workflows, IQ facilitates the creation of validated Workcell designs that reflect actual customer needs and historical data. This advancement addresses the growing demand for scalable solutions in the robotics industry, making it easier for partners to implement effective automation strategies.
Industrial robots News Robotics AI in robotics AI-powered engineering automation integration
China’s new LLM-powered ‘AI brain’ automates satellite surveillance
Chinese aerospace researchers have unveiled an innovative system that utilizes Large Language Models (LLMs) to enhance various aspects of aerospace engineering. This development was announced during a recent conference focused on advancements in aerospace technology, held in Beijing. The researchers aim to improve design processes, streamline communication, and facilitate problem-solving in the aerospace sector through the application of artificial intelligence. The motivation behind this initiative stems from the increasing complexity of aerospace projects, which demand efficient and effective solutions. By integrating LLMs, the researchers hope to harness the power of AI to analyze vast amounts of data and generate insights that can lead to more innovative designs and improved operational efficiency. The system operates by processing extensive datasets related to aerospace engineering, enabling it to assist engineers in generating design concepts, optimizing workflows, and predicting potential challenges. This approach not only aims to reduce the time and resources required for development but also seeks to foster collaboration among engineers by providing a common platform for communication. As the aerospace industry continues to evolve, the introduction of such advanced technologies is expected to play a crucial role in shaping the future of aerospace engineering, making it more adaptive and responsive to the challenges ahead.
Hellbender Secures $12.5M Seed Round to Accelerate Domestic Manufacturing of Physical AI and Launch Its On-Edge Camera Line
A robotics engineering and hardware firm has positioned itself as a key player in the realm of Physical AI by developing a foundational platform that enhances on-edge computer vision capabilities for autonomous systems. This innovative approach utilizes a robust portfolio of intellectual property to advance the field of robotics. The firm aims to revolutionize how autonomous systems perceive and interact with their environments, thereby improving their functionality and efficiency. By harnessing cutting-edge technology and data-driven insights, the company is set to make significant strides in the integration of AI within robotics, paving the way for more sophisticated and capable autonomous solutions.
Startup Wants to Run AI Inference From Space
The rapid growth of large language models is driving a global surge in energy demand for data centers, prompting operators to seek alternative power sources. Among them is Orbital Inc., a Los Angeles-based startup that recently emerged from stealth mode to announce plans for space-based data centers. Backed by venture capital firm Andreessen Horowitz, Orbital aims to utilize solar energy from a constellation of small satellites in low Earth orbit to power AI inference workloads, such as chatbots. Orbital's founder and CEO, Euwyn Poon, emphasizes the limitations of terrestrial energy sources, stating, “There simply isn’t enough capacity here [on Earth], and the only way is up.” The company envisions a network of up to 10,000 satellites, each equipped with GPU server racks powered by solar panels. The first test of this concept is scheduled for 2027, with a prototype satellite launch aboard a SpaceX Falcon 9 rocket. While Orbital's approach aims to reduce launch costs and improve efficiency, it faces significant engineering challenges, including radiation effects on GPUs, thermal management in space, and maintenance difficulties. Experts like Dr. Amit Verma from Texas A&M University caution that the operational feasibility of such systems will depend on the specific applications they support. Despite these hurdles, Orbital plans to finalize its satellite designs by 2026 and establish a manufacturing facility by 2028, with the goal of tapping into major AI firms as customers. Poon remains optimistic about overcoming technical challenges, asserting that their engineering efforts will pave the way for the future of space-based data processing.
Data-center Space Ai Inferencing
Light-activated gel could impact wearables, soft robotics, and more
Researchers at the Massachusetts Institute of Technology (MIT) have made significant strides in the field of ionotronics, a burgeoning area of study focused on the transfer of data through ions. This innovative approach aims to create a seamless interface between electronic devices and biological tissues, potentially revolutionizing how data is communicated within and between living organisms. The advancements were reported recently, highlighting the ongoing efforts to enhance the integration of technology with biological systems. By harnessing the unique properties of ions, the team at MIT is exploring new pathways for data transmission that could lead to breakthroughs in medical devices and bioengineering. This work underscores the importance of interdisciplinary research in bridging the gap between traditional electronics and the complexities of biological functions.
Research Robotics Light Materials science and engineering Wearables Materials Research Laboratory
Sarang Gupta Builds AI Systems With Real-World Impact
Sarang Gupta, a data scientist at OpenAI in San Francisco, has leveraged his childhood curiosity and engineering skills to make significant contributions to the field of artificial intelligence. From a young age, Gupta demonstrated a knack for problem-solving, fixing household items and later developing software solutions, including an online ordering system for a local restaurant. After earning dual degrees in industrial engineering and business management from the Hong Kong University of Science and Technology, he began his career at Goldman Sachs, where he automated trade reconciliation processes, enhancing operational efficiency. In 2020, Gupta earned a master's degree in data science with a focus on AI from Columbia University, where he collaborated on projects that aimed to improve journalism through technology. He then joined Asana as a product data scientist, leading the launch of AI-powered features to enhance user experience. His work gained momentum alongside the rise of generative AI, prompting him to transition to OpenAI in September 2025. At OpenAI, Gupta collaborates with the marketing team to develop data-driven models that optimize customer outreach and measure the effectiveness of various marketing channels. He emphasizes the transformative potential of AI across industries and plans to continue his work in this rapidly evolving field. Gupta, an IEEE member since 2024, values the organization for its resources and networking opportunities, which he believes inspire and enhance his professional journey.
Ieee-member-news Openai Generative-ai Chatgpt Careers Type-ti
How Kodiak uses AI and probabilistic risk assessment to measure autonomous trucking safety
Recent advancements in artificial intelligence are significantly accelerating the development of autonomous driving technology, allowing engineers to innovate at an unprecedented pace. However, the critical challenge remains ensuring that these advancements are paired with robust safety measures. Industry experts emphasize that achieving depth and rigor in safety protocols does not necessarily depend on having the largest budgets or the most extensive vehicle fleets. Instead, the focus is shifting towards extracting precise insights from data to enhance safety standards. As the industry moves forward, the integration of rigorous safety assessments with cutting-edge technology will be essential for the successful deployment of autonomous vehicles on public roads.
Autonomous Vehicles Computing Features Software ai safety automation news
RSS2026: Development of Consensus and China's Role in Embodied Intelligence
The Robotics: Science and Systems (RSS) conference is set to commence in St. Louis this June, marking a significant event in the robotics academic community. Since its inception in 2006, RSS has been known for its selective approach, accepting only about 60 papers annually, and is regarded as a leading indicator in the field of robotics. The 2026 conference will introduce a new focus on embodied intelligence alongside traditional motion planning and operational algorithms. Embodied intelligence has rapidly transitioned from a laboratory concept to an industrial hotspot over the past two years. The integration of large language models with visual models has led to the development of the Vision-Language-Action (VLA) framework, enabling robots to comprehend natural language commands and execute multi-step tasks. This technological pathway has sparked extensive academic debate regarding the reliability of end-to-end Transformer-based strategies in real-world applications versus potential overfitting in datasets. The positioning of embodied intelligence at RSS2026 will be symbolically significant for China. In recent years, international conferences have often viewed Chinese teams as representatives of engineering implementation rather than contributors of original theory. An increase in Chinese academic contributions at RSS this year could indicate a subtle shift in the international academic community's perception of the landscape of embodied intelligence research, highlighting the importance of high-quality theoretical innovation.
Embodied Intelligence Robotics Research Vision-Language-Action AI Robotics Algorithms
Stardust AI Launches Lumo-2: Innovative Robot Action Model for Home Automation
On July 15, Stardust AI introduced its second-generation embodied base model, Lumo-2, which is the industry's first household latent world-action model. This launch includes the physical AI symbiotic agent, Agent Philia, enhancing their full-stack architecture of AI models, embodied operating systems, and rope-driven entities. The company will showcase its 'trinity' multi-scenario implementation solutions at the World Artificial Intelligence Conference in Shanghai from July 17 to 20. Lumo-2 autonomously performs 22 complex household tasks, demonstrating industry-leading capabilities in task range and complexity. This model addresses the challenges faced by robots in open environments, such as the inability to explain actions and the high costs of training complex skills. By predicting future scenarios before generating actions, Lumo-2 aims to overcome these bottlenecks and improve the practical execution of robotic tasks. Looking ahead, Stardust AI plans to enhance the scalability of Lumo-2 by expanding training data diversity and exploring efficient data engineering paradigms. The team is also focused on advancing real-world interactive learning to enable robots to adapt and evolve autonomously in dynamic environments. No further timeline was disclosed at the time of publication.
Household Robotics Physical AI AI Models Robotic Automation
IEEE Honors Robotics Pioneer Toshio Fukuda
Toshio Fukuda has been blazing trails for most of his career. He is considered to be one of the most prolific scholars in robotics, writing more than 2,000 research papers and authoring several books on the field. He’s an influential figure thanks to his pioneering work developing biomedical robotic systems, industrial robots, micro-nano robotics, mechatronics, and AI-driven automation.Fukuda launched one of the first robotics conferences, the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). It is still popular almost 40 years later.Toshio FukudaEmployerEgypt-Japan University of Science and Technology, in Alexandria TitleProfessor and vice president of research Member gradeLife Fellow Alma matersWaseda University, in Tokyo; University of Tokyo An IEEE Life Fellow, he is a professor emeritus in the department of micro-nano systems engineering and a visiting professor at Nagoya University, in Japan, where he taught for nearly 25 years. Currently, he is a vice president of research at the Egypt-Japan University of Science and Technology, in Alexandria, Egypt.Within IEEE, Fukuda has held top volunteer positions including the organization’s highest office: He served as IEEE president in 2020, becoming the first person of Asian descent to hold the role.He’s a former program director of Japan’s Moonshot program, which by 2050 intends to develop advanced AI robots.Born in Japan, Fukuda has been recognized by the country for his contributions to science with two of its highest awards: the Medal of Honor with a purple ribbon in 2015 and the Order of the Sacred Treasure in 2022.IEEE honored him with this year’s Richard M. Emberson Award for “distinguished service advancing the technical objectives of IEEE, especially in the area of robotics.” The IEEE Board-level award is sponsored by the IEEE Technical Activities Board. Fukuda received the award on 24 April at a ceremony in New York City.As a former IEEE president who has served as a master of ceremonies at several of the organization’s major award events, Fukuda noted that he is more accustomed to bestowing awards than receiving them.“It’s very interesting to be on the receiving end,” he says.The journey into robotics researchAs a teenager, Fukuda spent his summer breaks teaching himself how to build things including transistor radios and steam engines.“It was very nice to have a hands-on hobby and make these kinds of things myself,” he says. His experimentation led him to study engineering.He earned a bachelor’s degree in engineering in 1971 from Waseda University, in Tokyo. He says one of his professors there—Ichiro Kato, regarded as the father of Japanese robotics research—was a good mentor who made a positive impact.Fukuda’s research interests were robotics and mechatronics, a field that combines robotics, electronics, computer science, and control systems.He went on to earn a master’s degree and a doctorate in science from the University of Tokyo, in 1971 and 1977. During those years, he also attended Yale, where he conducted research on advanced control theory in 1973.He reflects fondly on his time at Yale: “It was a very nice environment and a kind of free-thinking atmosphere. It motivated me to study more.”“IEEE doesn’t care who you are, what you do, what country you are from, or whether you are male or female. IEEE accepts people who have energy and passion.”While at Yale, Fukuda served as an assistant to his advisor—which led him to consider a career in academia, he says, because he enjoyed the freedom that research work afforded him.But he realized that such freedom comes with a price. University researchers are expected to raise the money that funds their work. He compares researchers to small-business owners who have to bring in money to keep their enterprise afloat.That realization led him to select robotics as his field because he intended to develop technologies useful to industry, he says.After earning his doctorate, he returned to Japan in 1977 to work as a research scientist at the government’s Mechanical Engineering Laboratory, later renamed the National Institute of Advanced Industrial Science and Technology, in Tsukuba.“There was a lot of research going on at the lab, including practical robotics and theory,” he says.He left Japan in 1979 to become a visiting research fellow at the University of Stuttgart, in Germany. During his year there, he studied systems, software problems, and related topics.He returned to Japan and was hired as an associate professor of mechanical engineering at the Tokyo University of Science. He conducted research into practical uses for robots by visiting industrial plants. He decided to develop robots that inspect industrial equipment such as those used in assembly plants, oil refineries, and power stations—places that “can be hostile environments for humans,” he says.His work drew interest from chemical, oil, and utility companies.“I got a lot of money from them for this very practical application, which funded my research,” he says, laughing.Developing popular robotic systemsFukuda grew tired of making those robots, he says, so he switched to creating ones for scientific applications. He developed many techniques, but he probably is best known for his modular, cellular robotic systems (CEBOTs), which he introduced in 1985.He has described how CEBOTs work in numerous papers published in the IEEE Xplore Digital Library.The CEBOT system is composed of a number of autonomous robotic cells that stick together like interlocking Lego plastic bricks, he says.Each cell is a fundamental modular unit that has a function. When a simple task is given, the system can analyze it and generate the structure of the cellular manipulator. The cells connect to and detach from each other through connection mechanisms and cooperate mutually, creating complex structures and configurations.“You start developing from the component-wise to the cell-wise to a small functional unit—and then you come up with clusters that make bigger systems. We can make a society of robot beings like that,” he explained in his oral history published on the Engineering and Technology History Wiki. “It’s a distributed robotic system, a self-organized robotic system, and also an evolutionary robotic system.“It’s also a fault-tolerant robot system because if something is wrong, you just remove those things and make a new one. You keep the system working. That’s a great thing.”Today CEBOTs are used for a variety of tasks such as delivering medication in hospitals, assisting with planting crops, and transporting products in distribution centers. Check out IEEE Spectrum’s Robots Guide for news from the world of robotics.In 1989 Fukuda joined Nagoya University as a professor of mechanical engineering and micro-nano systems engineering. During his 24-year career there, he was director of the university’s Center for Micro-Nano Mechatronics. He developed a long list of technologies at the university, including many for medical applications. He also conducted groundbreaking research into intelligent robotic systems and micro- and nano-robotics.Another technology he is known for is brachiation robots, which he helped develop in 1988. He calls them monkey robots because they’re based on the pendulum-like movement of monkeys swinging from tree to tree. The gravity-based locomotion enables continuous movement.Brachiation robots now are inspecting high-voltage transmission towers and bridges, searching damaged buildings for survivors, and performing maintenance on pipelines and cables.Fukuda retired from the university in 2013 and was named professor emeritus.He didn’t stay retired for long, though. He next held a teaching appointment at Meijo University, in Nagoya, until he left in 2022 to join the Egypt-Japan University.A prominent volunteerHe joined IEEE in 1980 at the encouragement of one of his research advisors, Professor Fumio Harashima, now an IEEE Life Fellow. After attending conferences and reading the organization’s publications, Fukuda says, he looked forward to becoming more involved.“I wanted to know how to organize a conference and how to edit a paper for one of its Transactions,” he says. “I wanted to know what was going on from inside the organization, not just the outside.”In 1988 he was the founding chair and organizer of IROS, in Tokyo. The conference had 330 attendees that year, and was supported by Harashima. Today it is one of the largest and most prestigious conferences on the topic, attracting more than 9,000 people annually. Out of 120,000 conferences, it was the only conference in the Nature Index database for this year, Fukuda says.In 1996 he and other members launched IEEE Transactions on Mechatronics.He was the founding president of the IEEE Nanotechnology Council, which was established in 2002. He is considered a pioneer in nanotechnology research, particularly regarding how it relates to robotics.Over the years, he has held numerous volunteer positions on IEEE editorial boards and committees.He was the 1998–1999 president of the IEEE Robotics and Automation Society, becoming the first non-U.S. member to hold the title.He was director of IEEE Division X (2001–2002 and 2017–2018), which covers intelligent systems, biological engineering, robotics, control systems, and photonic technologies. He served as the 2013–2014 director of IEEE Region 10 (Asia-Pacific).As the 2020 IEEE president, Fukuda saw the organization through the early part of the COVID-19 pandemic. Because of travel restrictions, he realized IEEE should change how it offered its in-person services, specifically educational programs. He encouraged IEEE Educational Activities to develop an online learning platform. The IEEE Learning Network started with just three courses and now offers nearly 2,000 courses, webinars, and learning materials.An award-winning memberThe Emberson Award joins a slew of other recognitions Fukuda has received from IEEE. They include several from the IEEE Robotics and Automation Society: a 2004 Pioneer Award, a 2009 Saridis Leadership Award, and the 2011 Harashima Award for Innovative Technologies. He is also a recipient of the Board-level 2010 IEEE Robotics and Automation Technical Field Award.He says he feels strongly that IEEE should be a diverse organization that is welcoming to all. As IEEE president, he led efforts to devise a diversity, equity, and inclusion program. Several policies, procedures, and bylaws were revised to give members a safe, inclusive place for discourse.“It’s important for IEEE to make everyone feel comfortable,” he says. “DEI programs are important. All people should be equal. IEEE doesn’t care who you are, what you do, what country you are from, or whether you are male or female. IEEE accepts people who have energy and passion.“It accepted me, from the Far East. That’s why I like it.”You can learn more about Fukuda and his career from the oral history conducted by the IEEE History Center.
Robotics Robots Ieee-member-news Type-ti Ieee-awards Toshio-fukuda
Palladyne AI Executes $4.2 Million U.S. Air Force Contract to Advance Swarming Capabilities for Integrated Cross-Domain Operations
Palladyne AI Executes $4.2 Million U.S. Air Force Contract to Advance Swarming Capabilities for Integrated Cross-Domain Operations Visit http://www.palladyneai.com for further information Palladyne AI’s SwarmOS™ platform to support satellite integration, marking a major expansion of its multi-domain autonomy and ISR capabilities across space, air, maritime, and land 07/07/26, 06:15 AM | Mobile Robots, Other Topics | Palladyne AI Corp. Palladyne AI Corp. (NASDAQ: PDYN and PDYNW) ("Palladyne AI"), a developer of artificial intelligence software for robotic platforms in the defense and commercial sectors, today announced that it has executed the previously announced contract awarded by the Air Force Research Laboratory (AFRL) to solve one of the most persistent challenges in modern defense operations—how to make different autonomous systems work together as one coordinated team. The "Hierarchical Adaptive Networked Game-Theoretic Integration of Multiple Echelons (HANGTIME)" contract will address this need. More Headlines A3's Automate 2026 Breaks Records as Demand for Robotics, AI and Automation Grows NVIDIA and Hugging Face Bring New Models and Frameworks to LeRobot for the Open Robotics Community ABB Robotics completes its AI-powered Visual SLAM AMR portfolio with new autonomous forklift UMA Unveils Its Vision for the Next Generation of Humanoid Robots Robbyant Unveils LingBot-Depth 2.0 and LingBot-Vision to Redefine Robotic Spatial Perception Articles Unleash AI Innovation: The Power of NVIDIA RTX PRO 6000 Blackwell Workstation Edition Fueled by PNY-Supplied GPUs Automate 2026 Q&A with DESTACO Automate 2026 Q&A with Roboteon Advances in Robots to See & Interpret within Warehouse Environments Building Resilient Fulfillment Networks with Robotics and Real-Time Logistics Data Today, drones, ships, and satellites often operate largely independently, limiting how quickly warfighters can see and respond to threats. HANGTIME will utilize Palladyne AI's patented SwarmOS™ software platform—the defense variant of the Palladyne™ Pilot embodied AI software—as the baseline technology to bridge that gap, connecting disparate systems so they can share intelligence, adapt to changing conditions, and act in sync across domains, including space, air, maritime, and land. By integrating satellites for the first time, this project also extends Palladyne AI's technology from the ground to orbit, enabling faster, more informed decision-making and coordinated mission execution, turning tactical commanders into strategic commanders by giving them more cross-domain intelligence, surveillance, and reconnaissance (ISR) capabilities than ever before. "Our collaboration with AFRL showcases what's next for autonomous operations," said Ben Wolff, President and CEO, Palladyne AI. "This isn't about replacing humans—it's about giving them sharper, faster insight. By connecting satellite, aerial, and ground systems using the patented SwarmOS embodied AI platform as a foundational technology, we're helping the warfighter make better decisions in real time and stay one step ahead on the battlefield." "The HANGTIME project is a breakthrough that unites high-altitude assets and situational unmanned systems into one coordinated sensor network—delivering a major advantage for the defense industry," said Dr. Denis Garagic, Chief Technology Officer, Palladyne AI. "For the first time, a single AI framework can coordinate assets across multiple domains, including satellites. That means these systems can now think and act together as a team, sharing what they see and learning as conditions change." "The HANGTIME effort represents a critical step in multi-domain autonomy for coordinated execution in challenging environments," said Caleb Williams, Program Manager, AFRL/RIEA. For more information on Palladyne AI and its patented collaborative autonomy software, including SwarmOS, please visit www.palladyneai.com. For more information about AFRL, please visit www.afrl.af.mil. About Palladyne AI Palladyne AI is a U.S.-based technology company developing patented embodied artificial intelligence, collaborative autonomy solutions, advanced avionics, autonomous systems, advanced UAV engineering services, and precision-manufactured components for defense and industrial markets. Palladyne AI delivers secure, American-developed and operated platforms designed to meet the stringent requirements of U.S. government and public-sector customers, including data sovereignty, security, and compliance. Palladyne AI's embodied AI is designed to operate in complex, contested, and high-risk environments, enabling distributed tasking, human-on-the-loop decision-making, degraded-communications resilience, and multi-domain coordination. Its platform-agnostic autonomy stack combines real-time sensor fusion, adaptive AI models, and edge-native orchestration—without vendor lock-in—to support autonomous and collaborative systems across air, ground, maritime, and industrial domains w
Waabi says its AI driver transferred to Volvo autonomous truck without retraining
Waabi says it has demonstrated what it describes as a major advance in autonomous driving by transferring its AI-powered virtual driver from one autonomous truck platform to another without requiring additional training, engineering or new data. The company says its Waabi Driver software was integrated with the Volvo VNL Autonomous truck, developed in partnership with […]
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Small-AI Models Gain Traction Around the World
One morning in 2019, Adebayo Alonge was in a Cape Town hotel room, preparing to demonstrate his startup’s AI answer to a serious problem in African health care: counterfeit medication, which kills thousands of people across the continent every year.The RxScanner is a handheld spectrometer that scans a pill with infrared light, then sends the item’s molecular profile to an AI model equipped with a pharmaceutical database. In seconds, the AI identifies the medication from its molecular profile—or reports that it’s phony.Pharmacies were using the system in more than a dozen countries, including Ghana, Kenya, Myanmar, and Alonge’s native Nigeria. But that morning in South Africa, it didn’t work. “I was shocked,” Alonge says.The spectrometer connected to the AI model—but the data center was 14,000 kilometers away and bandwidth was limited. “Our server was in the United States, and just to get the result of a single scan was taking me over 5 minutes.”So Alonge immediately asked his engineers to shrink the AI model down to a smaller, low-power, unconnected version that could run entirely on his Android phone. They produced it 2 hours later, and that saved the demo.More importantly, the work birthed a new version of his device, which can authenticate a pill in places without broadband, computers, or even reliable electricity. It also turned Alonge into an advocate for this kind of “small AI.”Small AI for Global Health Care AccessSmall AI is a far cry from wealthy nations’ colossal large language models (LLMs), hyperscale data centers, multibillion-dollar investments, and debates about AI consciousness. But for millions of people around the world, the only AI that matters, and often the only kind available, is small. (According to a World Bank Report issued in November, only 0.7 percent of internet users in the world’s poorest countries have used ChatGPT, compared to a quarter of all internet users in the most developed nations.)“Most people are discussing AI from the LLM/generative side. But that needs a lot of computing power, electricity, massive data, and skilled people to manage it,” Ajay Banga, president of the World Bank, said last January at the World Economic Forum, in Davos. “Outside the developed world, other than maybe India and China, very few countries have that combination.”By contrast, small AI can deliver useful, even life-saving services to people in areas that have none of those things, Banga said. In India, where the government’s AI plans call for more development of small AI, many such systems are working for farmers.For example, a drone-based system developed by Bala Murugan and colleagues at the Vellore Institute of Technology, in India, takes photos of cashew plants and quickly identifies those with splotches that indicate disease. All the processing takes place on the drone itself, so there’s no need for a computer on-site, nor for a connection to a central server.Using small language models trained for a specific problem, and sometimes running on cheap, low-power devices, other small-AI implementations have been developed to identify ant infestations in a Uruguayan vineyard, detect the presence of malaria-carrying mosquitoes in a number of nations, and run electrocardiograms from an Arduino device in parts of Brazil that lack access to more complex equipment.“This is the most important area in AI nowadays,” says Marcelo José Rovai, a professor at the Institute of Engineering and Information Systems at the Federal University of Itajubá, in Brazil, who was involved in all three projects. “It’s growing very fast.”Low-Power, Small-AI Models on Devices Small AI models can run on a variety of low-power devices, including [from left to right] an Arduino Nano 33 BLE Sense, a Seeed Wio Terminal, and an Arduino Portenta.Moez AltayebFor Alonge, Rovai, and other advocates, small AI is not just “a promising trend,” as that November World Bank report calls it. It may be, in the long term, the form of AI that will touch the most lives and remain sustainable after some of the giant models become too costly for most users.“I think the future of AI is not like one giant model, at a center. I think it’s millions of small, precise models deployed at the edge, each one solving like a specific problem, a specific context,” Alonge says. This is partly because much of humanity—including people in parts of rich countries as well as the developing world—lives without access to cutting-edge frontier models. But, he says, it’s also because those models are not sustainable.“If someone is not subsidizing it, most people will not be able to afford those models. So those of us who are said to be small-AI developers are the ones who will have to build for the majority of the world,” Alonge says.There is no strict definition of “small AI,” but people often use the term for language models with at most a few billion parameters. (Compare that to cutting-edge models, which can include more than a trillion.) That’s small enough to run directly on a phone or a Raspberry Pi. That’s what allows these applications to run on devices without a connection to a data center and use only a few watts of power, often supplied by a battery or a solar panel.Despite their small footprint, these models aren’t fundamentally different technology from that of gigantic AI models, Rovai says. Many instances of small language models were created the same way the phone-based version of Alonge’s pharmaceuticals scanner was—by “pruning” large models, or removing the parameters that weren’t involved in the task. The result is a system that’s less capable generally but still very good at the specific job it was pruned for, Rovai says. A lighter version of RxAll’s RxScanner spectrometer sends its results to an AI model run locally on a phone to check that a drug’s molecular signature is genuine.RxAllOther small models are created by “distillation.” They are trained to mimic a large model, until their performance approaches that of their “teacher,” Rovai says. In other cases, a larger model’s precision is reduced, for example, so that a model run on 32-bit architecture can run on 8-bit designs. In situations where the machine learning application is being used to classify data or predict patterns (like an ant infestation), it’s trained from the beginning on a small device, not derived from a larger model at all. Running all these small, specialized systems is becoming easier, Rovai says, for two reasons.The first reason is that hardware is getting better and more capable while using less power, he says. This means more and more phones can run small AI—especially those equipped with neural processing units, which are specialized chips that handle AI tasks like facial recognition and changing the brightness, shadows, or contrast in a photo.In 2025, slightly more than a third of all smartphones shipped worldwide were capable of running generative AI, and that figure will reach 45 percent by the end of this year, according to the technology research firm Counterpoint. By the end of next year, slightly more than half of all smartphones will be able to run a small AI model.The second reason Rovai cites is the shrinking footprint of language models. Both Google DeepMind’s Gemma 4 (released in April) and Alibaba’s Qwen 3.5 are “fantastic” for small AI, Rovai says. Both models are “open weight,” meaning users can adjust the connections between parameters to suit their needs. This makes it easy, for example, “to take a lot of data from, say, the milk industry and retrain the model specifically on that,” Rovai says.Rovai illustrated these reasons on a Zoom call, using one of his most recent experiments. Holding up a device, he says, “This is the new Arduino UNO Q—a US $50 device with a Qualcomm chipset. I’m running a language model here, which collects data from sensors and analyzes that data to detect tiny pools of water where mosquitoes might be breeding. It takes 3 watts to run it.”Support for Small-AI DevelopmentConvinced that millions of people are already benefiting from these kinds of applications, the World Bank now actively promotes small AI with grants, mentorship programs, financing, technical advice, and models of government policies that are friendly for small-AI development. For example, in Rwanda, the World Bank is backing a government program to help low-income households get devices that can run AI.All that said, no one claims that large language models are going away entirely. To create a generative AI that can run on a phone or other small device requires the architectural insights, data processing, and results of a larger model, Rovai says. “We need the big models to create these smaller models.” And for all that small AI can benefit people without access to big AI, the technology can’t solve the larger problems of development and digital inequality, Alonge says. Implementing small AI won’t allow nations to escape the challenge of creating an ecosystem to support AI: reliable power, a supply chain that works, and an educational system that develops the talents needed to create AI tools.Though his drug-scanning system can run for days on a phone with no connection, “you still want to be able to enable periodic syncing for updates with new signatures for the medications and analytics,” Alonge says. “And even when you are using batteries, reliable power is important. That phone battery is not going to last forever.”In many parts of the world, the future of small AI isn’t assured, he says. “It works, and many places will eventually need to use it. The question is whether or not the political actors are wise enough to invest in infrastructure to support it long term.”
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Japan Pioneered Humanoid Robots—Can It Now Catch China?
“In the future, the relationship between humans and robots will deepen, and the distinction between them will probably disappear.” This prediction, from one of the attendees at the recent Humanoids Summit in Tokyo, might have been unremarkable had it not come directly from an android that was first introduced to the world 20 years ago. Geminoid HI-6 is the sixth-generation of a robot originally designed in 2006. The mechanical twin of Osaka University professor Hiroshi Ishiguro, Geminoid HI-6 is now equipped with a large language model trained on Ishiguro’s own writings and interviews. It has advanced conversational skills and can even have a chat with its creator, an eerie spectacle. But at the Humanoids Summit, Geminoid was one of the few humanoid robots from Japan, the country that pioneered the form factor.While the event in Tokyo only had about 40 robots on display, Chinese systems outnumbered Japanese by roughly three to one. Some Japanese robotics firms were even using Chinese robots in their own technology demonstrations, something that would have been unthinkable in the recent past—one Japanese engineer described the situation as “sad.” The conference was a stark reminder of how Japan has ceded its early lead in humanoid robot development to overseas competitors, and the challenge it now faces to secure a place in an ecosystem increasingly dominated by general-purpose robots powered by AI. Twenty-five years ago, Japan was turning out groundbreaking humanoids that were showstopping in their abilities, but they were not commercialized as practical machines in any meaningful way. Heavily influenced by science fiction and lacking practical applications, they were mostly expensive technology demonstrations that were eventually mothballed. What Japan retains, however, is robotics design and know-how, which it must leverage to be a key player in the rapidly evolving humanoid ecosystem. Learning to Walk—Then Standing StillTo anyone who has seen recent videos of Chinese humanoids doing kung-fu and synchronized acrobatics, as well as half-marathon races, China’s remarkable progress in the field is nothing new. At the Humanoids Summit, Toyota showed a video of its latest basketball-playing robot, and Honda exhibited its latest robot hand, but the full-scale humanoids on the floor were mostly Chinese–the kid-size K1 machines from Booster Robotics of Beijing were dancing to Michael Jackson tunes. The full-scale G1 humanoid from Unitree Robotics of Hangzhou was also doing demos. “You cannot sell these bipedal systems in Japan for safety and compliance reasons,” says Shuichi Nagao, a frequent visitor to China as CTO of Omakase Robotics, a division of Zeals, a Japanese humanoid robot developer. Omakase was exhibiting a G1 modified with an external PC controller, a dextrous hand, a suction-cup manipulator and a sensor “hat” with an extra speaker, mic and camera. “In China, the government is pushing humanoid development. They didn’t have an industry 20 years ago. The people pushing it are young, in their 20s and 30s. It’s a really different mentality out there,” says Nagao. “Big players in Japan are still looking for use cases for humanoids. In China, they’re already doing mass production and reducing the cost, so other countries can’t compete with them anymore.”Another Japanese company showing off G1 bots was summit sponsor GMO AI & Robotics, a subsidiary of Japanese internet company GMO. It’s using the robots in partnership with Japan Airlines to load and unload cargo containers at Tokyo’s Haneda airport. The cargo project is a trial—like many other humanoid experiments—but the fact that Chinese machines have penetrated so far into Japan’s ecosystem upends a long history. In 1973, scientists at Waseda University in Tokyo built WABOT-1, considered the first full-scale humanoid robot and capable of slow bipedal locomotion, grasping objects and simple communication. It inspired Honda’s groundbreaking Asimo humanoid, but it was never commercialized. Asimo was eventually retired in 2022, the year ChatGPT was released. Two years later, Unitree’s G1 went on sale for US $16,000. China’s High Torque Technology Co. showed off its Mini Pi biped, customized with an anime-inspired head, at Humanoids Summit in Tokyo. The regular version is priced at $3,500. Tim HornyakSupply and DemandJapan’s development of humanoids happened before practical applications or widespread demand were in place, but bad timing is only part of the story—Japan also has a history of developing technologies that might appeal to domestic consumers but not necessarily those overseas. For example, decades after they first appeared, its highly engineered, multifunction toilets have only recently found a following abroad. Japan’s humanoid prowess was partly built on the back of its legendary industrial automation, yet even that stronghold has eroded. Ani Kelkar, a partner from McKinsey & Company in Boston who produces analytical reports about the robotics industry, told the summit audience that while Japan occupied the top spot in the world in manufacturing robot density (the number of multipurpose industrial robots in operation per 10,000 employees) from at least 1994 to 2009, it then slipped to second in 2014, third in 2019 and fifth in 2024. In that year, South Korea was at the top of the leaderboard with a robot density of 1,220 compared to Japan’s 446. The International Federation of Robotics estimates China now has the most operational industrial robots in the world, with around 2 million total units, approximately 4.5 times more than Japan. “The annual installation numbers are impressive too: 54 percent of all robots installed worldwide in 2024 were deployed in China,” the IFR said in a release in April 2026. “I think the loss of Japanese leadership is more to do with the rise of China as a manufacturing powerhouse including for sectors that Japan had high export levels,” Kelkar said in an email interview. “The recovery has not yet happened as Japan ‘missed’ the rapid acceleration in AI for robotics and is now playing catchup.”How Japan Can Adapt Kelkar believes Japan has a US $100 billion opportunity in general-purpose robotics, which are machines that can perform a wide variety of tasks, and it cannot rely on the slower-growing industrial robot market, which is centered on factory machines that do one simple and predictable task like welding car parts. He points to a McKinsey white paper suggesting that while Japan has much of the hardware and technology experience needed to support general purpose robot development, it must change its strategy to capture more share in AI, software, data collection and robotics platforms.Tetsuya Ogata is a professor of engineering and director of the Institute for AI and Robotics at Waseda University, the birthplace of humanoids in Japan. He briefed the summit on how a nonprofit he chairs, the AI Robot Association (AIRoA), is working with Toyota and other members to develop foundational technologies for collaborative use. For instance, AIRoA has collected some 80,000 hours of data on remote operation of mobile manipulators, and Ogata believes it’s the largest dataset of its kind. Using the data, it built and verified Vision-Language-Action (VLA) models, and it has also started data collection for dual-arm mobile manipulation. In an interview, Ogata acknowledged Japan’s struggle to find its place in the changing landscape. “The world of AI is inherently a game of scale,” says Ogata. “Therefore, Japan’s absolute prerequisite is to secure a competitive baseline of scale—in data, computing resources, and talent. Beyond that, what I consider most critical is a mindset shift: rather than trying to hoard scale within a single nation or company, we must grow stronger by collaborating with a diverse ecosystem of domestic and international players.” Specifically, this means creating a ‘collaborative domain’ to address data—the single biggest bottleneck—through industry-wide cooperation rather than data-siloing. By collectively nurturing a pre-competitive, shared data infrastructure and foundation model, individual companies can then compete on top of it with their own applications. “By offering this open ‘data ecosystem’ to the world, we can engage global players and establish a ‘third pole’ alongside the US and China,” says Ogata. “I believe this is how Japan can reclaim its global presence.”In 1999, Japan introduced the world’s first mobile internet services platform. But being first didn’t turn Japan into a smartphone manufacturing or design center—it’s now merely a supplier of parts to other countries who are leading the smartphone industry. If Japan can avoid a repeat of that experience and successfully deregulate, diversity, and commercialize its original humanoid dreams, it stands a better chance of influencing the direction of the industry and reaping billions in value. As automobiles and electronics were pillars of Japan’s industrial strategy in the last century, Japan could make humanoid robots one of its key value generators in the 21st century, an approach that would not only deliver economic benefits but give Japan greater clout in how the industry will evolve. Just like Japanese cars, electronics, and even toilets, Japanese humanoids could stand for craftsmanship and reliability. It’s a legacy that Japan can’t afford to give up.
Japan Robotics Humanoids Humanoid-robots
IEEE Rolls Out Large Language Models Virtual Training Course
Large language models (LLMs) have transitioned from research labs to everyday use in engineering, significantly altering how digital infrastructures are developed and maintained. As technical professionals increasingly rely on LLMs for complex tasks—such as identifying vulnerabilities in source code and converting fragmented discussions into detailed specifications—the demand for expertise in this technology is surging. According to MarketsandMarkets, the LLM technology market is projected to grow by approximately 33% annually through 2030. To effectively utilize LLMs, engineers must move beyond basic interactions and understand the underlying transformer architecture that enables these models to process vast datasets simultaneously. This knowledge is crucial to mitigate risks associated with inaccuracies, often referred to as "hallucinations," and to ensure reliable performance in coding and data handling. Key advancements include integrating LLMs with application programming interfaces (APIs) for direct database connections, addressing hallucination issues through retrieval-augmented generation (RAG), and prioritizing data security by establishing private model instances. Additionally, LLMs automate repetitive tasks, allowing engineers to focus on higher-level design and problem-solving. To bridge the growing knowledge gap, IEEE has launched an online program titled "Large Language Models Demystified," designed to equip technical professionals with a deeper understanding of LLMs. The curriculum covers the evolution of AI technology, transformer architectures, and practical model-building exercises. Participants will earn professional development credits and a digital badge upon completion, enhancing their credentials in this rapidly evolving field. Organizations interested in training their teams can consult with IEEE for tailored enrollment options.
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Robotiq Announced AI-Enabled Platform for Workcell Integration
A new platform has been launched to enhance collaboration among engineering teams by streamlining workflows through effective data capturing and design coordination. This innovative tool is designed to improve efficiency and communication within engineering projects, addressing common challenges faced by professionals in the field. The platform is expected to be particularly beneficial for companies looking to optimize their engineering processes and ensure seamless integration of design and data management. By providing a centralized space for teams to work together, the platform aims to foster better decision-making and project outcomes.
Factory / Analytics
New UgCS 6.0 flight planning software solves a major headache for drone surveyors
SPH Engineering has announced the launch of UgCS 6.0, a significant update to its enterprise drone flight planning platform, aimed at addressing a longstanding challenge faced by drone survey teams operating in extensive mining, oil pipeline, and remote geological sites. The update provides a solution for efficiently dividing large survey areas into manageable flight sections, thereby preventing alignment issues that can compromise data quality. This innovation is expected to enhance the operational efficiency and accuracy of drone surveys, which are crucial for various industries reliant on precise geographical data. The introduction of UgCS 6.0 marks a notable advancement in drone technology, responding to the needs of professionals in the field.
News
US engineers make ‘artificial eyes’ to improve vision in robots, self-driving cars
Researchers at Penn State University have developed an innovative device inspired by the human eye, aimed at enhancing the vision capabilities of self-driving cars. This groundbreaking technology was unveiled recently as part of ongoing efforts to improve the safety and reliability of autonomous vehicles. The device mimics the eye's ability to adapt to varying light conditions, which is crucial for navigating complex environments. The motivation behind this advancement stems from the challenges faced by self-driving cars in low-light situations, where traditional sensors often struggle to provide accurate data. By integrating this eye-inspired technology, the researchers hope to significantly reduce the risk of accidents and improve the overall performance of autonomous systems. This development is part of a broader initiative to advance automotive technology and ensure that self-driving cars can operate effectively in diverse conditions. The research team utilized a combination of advanced materials and optical engineering to create a device that can dynamically adjust its sensitivity, much like the human eye does when transitioning from bright to dim environments. As the automotive industry continues to push towards fully autonomous vehicles, innovations like this are essential for addressing safety concerns and building public trust in self-driving technology. The research findings are expected to contribute to future advancements in vehicle design and functionality, paving the way for safer roads.
Going supersonic! NASA's X-59 jet breaks sound barrier for the 1st time
NASA's X-59 jet successfully broke the sound barrier for the first time on June 5, achieving a top speed of approximately Mach 1.1. This milestone marks a significant advancement in aerospace technology, as the X-59 is designed to explore the potential for quiet supersonic travel. The flight took place during a test mission aimed at gathering data on the aircraft's performance and the impact of supersonic flight on communities below. By developing the X-59, NASA aims to pave the way for future commercial supersonic flights that minimize noise pollution, addressing a major concern that has historically limited supersonic travel. The successful test flight demonstrates the effectiveness of the innovative design and engineering efforts behind the X-59 project.
Aerospace Technology
7 Ways New Engineers Can Flourish in the Age of AI
As new graduates enter the workforce, they are navigating a landscape where artificial intelligence (AI) is essential rather than optional. Successful engineers are learning to leverage AI as a tool rather than viewing it as competition. To remain competitive in this rapidly evolving field, experts recommend several strategies for young professionals. First, mastering fundamental skills in data structures, algorithms, and core programming languages like C++, Java, and Python is crucial. Understanding these basics enables engineers to effectively debug and optimize their work, even when using AI tools. Additionally, engineers should learn to collaborate with AI by crafting clear prompts, reviewing AI-generated code, and using AI to enhance productivity while exercising critical judgment. Building projects that demonstrate comprehensive system design is increasingly important, as employers seek candidates who can define requirements and deliver scalable, maintainable products. Early development of system design skills is also vital, as even junior engineers are expected to discuss responsible AI integration and system reliability. Strong communication skills are essential, as engineers must articulate design choices and collaborate within teams—an area where AI cannot replace human input. Continuous learning and curiosity about industry developments, new tools, and community engagement are also emphasized as key to staying relevant. Finally, engineers are encouraged to think beyond coding, focusing on problem-framing, architectural judgment, and ethical considerations in AI use. For ongoing career insights, professionals can subscribe to the IEEE Spectrum Career Alert Newsletter, which offers biweekly updates on jobs, education, and the engineering workplace.
Ieee-member-news Career-advice Ai Young-professionals Type-ti
Bio-hybrid robotics system ‘listens’ to cyborg insects for collaborative control
Japanese researchers have unveiled an innovative method for controlling cyborg insects, aiming to enhance the understanding of their behavior and capabilities. This groundbreaking development was announced during a recent conference held in Tokyo, where scientists discussed advancements in bioengineering and robotics. The motivation behind this research stems from the potential applications in environmental monitoring and disaster response, where these engineered insects could play a crucial role in collecting data from hard-to-reach areas. The researchers have integrated electronic components into the insects, allowing for remote control and manipulation of their movements. This process involves sophisticated techniques that blend biology with technology, enabling the insects to be guided through various environments. The team believes that by mastering this control, they can create a new class of biohybrid systems that could revolutionize how we interact with the natural world. As the project progresses, the researchers are optimistic about the implications of their work, which could lead to significant advancements in both ecological research and practical applications in urban planning and emergency management. The findings from this study are expected to be published in a leading scientific journal, further contributing to the growing field of cyborg biology.
Light-activated gel could impact wearables, soft robotics, and more
Researchers at the Massachusetts Institute of Technology (MIT) have made significant strides in the field of ionotronics, a burgeoning area of study focused on the transfer of data via ions. This innovative approach aims to create a connection between traditional electronics and biological tissues, potentially revolutionizing the way information is processed and transmitted in various applications. The advancements were announced in October 2023, highlighting the ongoing efforts to enhance the integration of electronic systems with biological environments. By harnessing the unique properties of ions, the team at MIT is exploring new methods to facilitate communication between electronic devices and living organisms, paving the way for future developments in medical technology and bioengineering.
China completes record 537-day deep-sea materials experiment under extreme pressure
China has announced the successful completion of a groundbreaking 537-day deep-sea material corrosion exposure experiment, claiming it to be the first of its kind in the world. Conducted in the South China Sea, the project aimed to assess the durability and longevity of various materials used in marine engineering and construction. The initiative is part of China's broader efforts to enhance its capabilities in deep-sea exploration and technology, driven by the increasing demand for sustainable and resilient infrastructure in challenging underwater environments. Researchers monitored the materials' performance and degradation over the extended period, providing valuable data that could inform future developments in maritime engineering. This achievement underscores China's commitment to advancing its scientific research and technological prowess in the field of marine sciences.
LG CNS enters physical AI race to coordinate rival robots
LG CNS, the IT services division of LG Group and a leading systems integrator in South Korea, has introduced a groundbreaking software platform designed to manage fleets of robots from various manufacturers under a unified control system. This launch took place on Thursday and addresses a longstanding challenge in the robotics industry that typically required extensive custom engineering for coordination. The new platform, named PhysicalWorks, consists of two key components: one module focuses on training robots utilizing simulation and video data, while the other facilitates real-time task assignment and reassignment across diverse robot fleets. This innovative solution aims to streamline operations and enhance efficiency in environments where multiple robotic systems operate concurrently.
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