Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Bad news, 30-somethings: You'll likely never be truly AI native
Caitlin Kalinowski, the former leader of robotics at OpenAI, has highlighted a notable trend in the workforce shaped by artificial intelligence. In a recent statement, she pointed out that the majority of individuals who can be considered truly AI-native workers are predominantly aged 20 and 21. This demographic has grown up in an environment where AI technology is deeply integrated into daily life, influencing their skills and adaptability in the job market. Kalinowski's observations come at a time when industries are increasingly seeking employees who can effectively leverage AI tools and technologies. Her insights underscore the importance of understanding how younger generations are uniquely positioned to thrive in an AI-driven economy, suggesting that their familiarity with these technologies could reshape future workforce dynamics.
AI ai artificial-intelligence gen-z millenial trending-uk
Figure AI's CEO just raised $700 million for his next big bet
Hark, a company established by Brett Adcock, the CEO of Figure AI, has successfully raised $700 million in funding. This significant investment positions Hark to compete with major players in the artificial intelligence sector, including OpenAI, Apple, Google, and Meta. The funding aims to accelerate the development of innovative AI hardware solutions, reflecting the growing demand for advanced technology in various industries. With this financial backing, Hark plans to enhance its capabilities and carve out a substantial presence in the competitive landscape of AI hardware innovation.
Tech AI Startups tech ai brett-adcock
Starmind's Orbital Compute vs. Terrestrial Data Centers: Analyzing Resource Advantages
Starmind's orbital compute technology presents a significant advantage over traditional ground-based data centers by eliminating constraints related to land, water, and grid permitting. While terrestrial data centers are currently cheaper and faster to construct, with U.S. data center spending reaching $85.3 billion in 2026, Starmind's approach focuses on addressing the growing resource limitations faced by hyperscale facilities. The significance of Starmind's technology lies in its ability to sidestep the increasing challenges of land and water usage. For instance, a 100 MW data center can consume approximately 530,000 gallons of water daily for cooling, while Starmind's AI1 utilizes deployable liquid radiators that require no water. This structural advantage could resonate with investors as the demand for AI computing continues to escalate, potentially leading to annual water withdrawals of up to 1.7 trillion gallons by 2027. Looking ahead, Starmind's next milestones include the launch of AI1 prototypes scheduled for early 2027. However, the technology's claims regarding cooling efficiency and operational reliability remain unverified until real flight data is available. As the industry evolves, the competition between orbital and terrestrial solutions will become increasingly relevant, particularly in the context of resource management and sustainability.
SpaceX's $1.75 Trillion Valuation Driven by Starmind's Future Potential
Starmind is a pivotal element in SpaceX's estimated $1.75 trillion IPO valuation, despite currently generating no confirmed revenue. The stock price reflects optimistic projections regarding AI infrastructure growth, which Starmind has yet to substantiate. As of early July 2026, SpaceX's stock has decreased from its 52-week high of $225.64 to around $150, indicating market skepticism about future execution. The significance of Starmind lies in its potential to transform SpaceX's revenue model beyond traditional launch services. Goldman Sachs has shifted its focus from Starlink subscriber growth to the prospects of AI revenue, including orbital computing, as a cornerstone of SpaceX's long-term valuation. This marks a substantial change in how analysts view the company's growth trajectory, necessitating rates exceeding its historical 33% growth. Looking ahead, the credibility of Starmind as a growth narrative will be crucial for maintaining investor confidence. Analysts have noted a considerable divergence in price targets, reflecting uncertainty about the value of the Starmind and xAI initiatives. No further timeline was disclosed at the time of publication regarding specific milestones for these projects.
In Defence Investment Plan preview, Britain bets big on drones, ‘hybrid’ navy
The Ministry of Defence has announced an initiative to develop at least six hybrid warships that will integrate with unmanned systems both in the air and at sea. This strategic move aims to enhance naval capabilities and modernize the fleet, reflecting a growing emphasis on advanced technology in military operations. The initiative underscores the Ministry's commitment to maintaining a competitive edge in maritime defense, particularly in an era where unmanned systems are becoming increasingly vital for operational effectiveness. The timeline for the project has not been specified, but it represents a significant step towards modernizing naval warfare and adapting to evolving threats.
Air Warfare Global Land Warfare Naval Warfare Air Force Ajax
Big money is betting the self-driving future belongs to a small club
The Autonomous Vehicle sector has experienced a significant surge in investment, marking the highest level of capital influx in over a decade. However, this financial boost has predominantly favored a select group of companies, leading to a concentration of funding within the industry. This trend highlights a shift in investor confidence and strategic focus, as stakeholders seek to back firms with proven potential for innovation and market impact. The influx of capital is expected to accelerate advancements in technology and infrastructure, further shaping the future of transportation.
Transportation robotaxi funding
Corporate Investors Bet Big on Robotics Revolution: CVC Deals Jump 183% in Q1
In the first quarter of 2024, corporate venture capital investment in robotics startups experienced a remarkable surge of 183% year-over-year, totaling $1.3 billion across 34 deals. This significant increase is largely attributed to advancements in artificial intelligence and the growing demand for manufacturing solutions, particularly in the context of onshoring. Companies are actively investing to both supply components for and deploy next-generation robots, with a notable focus on humanoid technology. This trend reflects a broader shift in the industry as corporations seek to enhance their operational capabilities and adapt to evolving market needs.
Neura Robotics Schaeffler Agility Robotics Apptronik Fourier Intelligence
Human-Robot Collaboration: How Modern Workplaces Can Be Designed for Safety, Productivity, and Employee Wellbeing
The industrial robotics market, valued at $85 billion, is transforming production floors by eliminating physical barriers between humans and machines. This shift allows for a collaborative environment where workers and robotics operate side by side. As millions of industrial robots are deployed globally, effective management of this transition is crucial. It necessitates a comprehensive understanding of spatial geometry, workforce psychology, and adherence to functional safety standards to ensure a seamless integration of technology into the workplace. This evolution in manufacturing aims to enhance efficiency and productivity while prioritizing safety and worker well-being.
Engineering Robotics automation news automation strategy cobots collaborative automation
Employee Handbook Translation Services Are No Longer Optional for Modern Workplaces
In an effort to enhance workplace communication and ensure compliance with safety standards, a mid-sized manufacturing company has updated its employee handbook to include translated versions for its multilingual workforce. The initiative, spearheaded by the HR manager, aims to clarify workplace expectations and policies, thereby fostering a more inclusive environment for all employees. Recognizing that automated translation tools often produce inaccuracies, the company prioritized the use of professional translation services to ensure that the wording in the handbooks is precise and accessible. This strategic move not only supports better understanding among employees but also reinforces the company's commitment to safety and compliance. The updated handbooks are expected to improve employee engagement by making essential information readily available in multiple languages. By maintaining consistency across teams, the company hopes to create a cohesive workplace culture that values clear communication and inclusivity. This proactive approach reflects a growing trend among businesses to address the needs of diverse workforces and enhance overall operational efficiency.
Business Technology automation news business communication compliance training construction workforce
Musk Foresees Optimus as Tesla's Largest Product Amidst Strong Chinese Competition
Elon Musk predicted during Tesla's earnings call in January 2026 that Optimus will become the company's largest product, potentially ten times bigger than its next biggest offering. Tesla is transitioning its Fremont factory to focus on Optimus production, increasing the annual capacity target for the Optimus V3 line from 50,000 to approximately 70,000 units, with plans to add another 70,000 units in Austin by 2028. Musk emphasized the competitive landscape, stating that China will be Tesla's biggest rival in the humanoid robot market, citing the country's strengths in scaling and manufacturing. According to TrendForce, the commercialization of humanoid robots is expected to accelerate in 2026, with China's production projected to grow by 94% annually, accounting for about 90% of global shipments last year. Tesla plans to initiate small-scale production of Optimus between late July and August 2026. Musk's insights indicate a clear competitive race between the U.S. and China, with no significant competitors outside of China currently visible to Tesla, highlighting the intense rivalry in AI and manufacturing capabilities.
Humanoid Robots AI Robotics Manufacturing Tesla
Japan's Shimizu bets on humanoid robots to tackle construction labor crunch
Artificial intelligenceJapan's Shimizu bets on humanoid robots to tackle construction labor crunchCompany eyes fiscal 2030 for robots that can walk around, paint and coat wallsShimizu is testing out the ability of this robot from China's Unitree to patrol construction sites on foot. (Photo by Kohei Okuyama)KOHEI OKUYAMAJuly 8, 2026 05:02 JSTTOKYO -- Japanese general contractor Shimizu plans to introduce AI-powered humanoid robots at its construction sites by around fiscal 2030, aiming to have them handle such work as painting and plastering in a bid to alleviate the industry's severe labor shortages, Nikkei has learned.Read NextArtificial intelligenceJapan eyes AI-powered comeback in factory robot race with China, EuropeConstructionJapan builders turn down big projects because of labor crunch: pollArtificial intelligenceJapan backs SoftBank-led AI models with up to $6.2bn in chasing US, ChinaBusiness dealsJapan's Shimizu to buy Okinawa-based builder focused on US military basesTechnologyVideo game engines find new homes in construction and retailBusiness dealsJapan builder Obayashi buys peer Multiplex Global for $540mLatest on Artificial intelligenceArtificial intelligenceCan China and US find common ground on AI governance in Geneva?Artificial intelligenceJapan weighs AI-powered disaster relief distributionArtificial intelligenceChinese AI usage by US firms soared after Mythos restrictionsSponsored ContentAbout Sponsored ContentThis content was commissioned by Nikkei's Global Business Bureau.
New color-changing tactile sensor gives robots a real-time sense of touch
Researchers have developed an innovative color-changing tactile sensor that enables machines to perceive and respond to their surroundings in real-time. This groundbreaking technology was unveiled in October 2023 and represents a significant advancement in the field of robotics and artificial intelligence. The sensor mimics the way humans and animals sense touch and texture, providing machines with the ability to "see" and interpret the materials they come into contact with. The motivation behind this development lies in enhancing the interaction between machines and their environment, allowing for more sophisticated and responsive robotic systems. By integrating this tactile sensor, robots can better understand the properties of objects, leading to improved performance in various applications, such as manufacturing, healthcare, and service industries. The process involves a combination of advanced materials and engineering techniques that allow the sensor to change color based on the pressure and texture of the surfaces it touches. This visual feedback not only aids in object recognition but also enhances the machine's ability to make informed decisions based on tactile information. As this technology continues to evolve, it holds the potential to revolutionize how machines interact with the world, paving the way for smarter, more adaptable robotic systems that can operate effectively in diverse environments.
AI and Robotics
Software is ‘the biggest bottleneck to robotics innovation’, says BlackBerry QNX report
QNX, a division of BlackBerry, has unveiled its latest research study, the Inside the Robot: Architecture Benchmark Report, which explores the evolving landscape of robotics development. The report highlights the shift towards software-driven and AI-enabled systems that are increasingly integrated into workplaces and everyday life. Conducted through a survey of 1,000 developers globally, the research aims to shed light on the current trends and challenges faced in the robotics sector. This initiative reflects QNX's commitment to understanding and advancing the role of robotics in modern society, emphasizing the importance of collaboration between humans and machines. The findings are expected to inform future developments in the field and guide industry stakeholders in adapting to these transformative changes.
Features Robotics Software ai robotics automation news Autonomous robots
Hello Robot’s latest Stretch 4 is bigger, faster, and stronger than previous versions
Hello Robot has unveiled its latest model, the Stretch 4, which boasts enhanced capabilities compared to its predecessors. This new assistive robot is designed to be bigger, faster, and stronger, while still prioritizing flexibility and safety in its operations. The announcement highlights the company's commitment to advancing robotic technology to better serve various applications. The Stretch 4 aims to improve efficiency and effectiveness in tasks that require assistance, marking a significant step forward in the field of robotics.
Artificial Intelligence Artificial Intelligence / Cognition Cameras / Imaging / Vision Design / Development Development Tools / SDKs / Libraries Grippers
China’s Huaqiangbei bets on AI innovations to revive global appeal
Huaqiangbei, located in Shenzhen, China, is transforming into a global hub for artificial intelligence, attracting foreign traders and tourists eager to explore the latest technological innovations. This shift comes as the area, known for being the largest electronics marketplace in the world, seeks to revitalize its appeal amidst changing market dynamics. Visitors like Abigail Slagveer from Rotterdam, Netherlands, expressed amazement at the vastness of the marketplace, highlighting the experience of navigating through its extensive offerings. The reinvention of Huaqiangbei reflects a strategic move to capitalize on the growing interest in AI technologies, positioning itself as a premier destination for those seeking cutting-edge gadgets and advancements in the tech industry.
Industrial Cobots vs. Traditional Industrial Robot Systems: Which Is Better?
In recent years, manufacturing industries have increasingly turned to industrial collaborative robots, or cobots, as a more flexible alternative to traditional robotic systems. JAKA, a leader in this field, has noted a significant shift in automation strategies, with companies opting for cobots that facilitate close human interaction without the need for extensive safety measures or programming. The JAKA Pro12 exemplifies the advantages of industrial cobots, showcasing enhanced environmental adaptability with its IP68 protection, allowing it to function reliably in challenging industrial conditions. Its maintenance-free design ensures high precision while occupying minimal space, which helps reduce downtime and simplifies operations compared to traditional robots. While traditional robots are effective for high-speed and heavy-load tasks, they require more space and safety precautions. In contrast, the JAKA Pro12 can work alongside human operators, making it ideal for dynamic tasks and environments where collaboration is key. This flexibility enables companies to swiftly adapt to changing production demands, a capability often lacking in conventional setups. Cost considerations for implementing cobots involve various factors, including integration complexity and required peripherals. JAKA assists clients in navigating these elements, demonstrating how cobots can lead to lower long-term operational costs through reduced maintenance and quicker deployment times. Ultimately, the decision between industrial cobots and traditional robots hinges on the specific needs of each manufacturing operation. JAKA's cobots offer a compelling blend of safety, flexibility, and precision, making them an attractive option for companies seeking versatile automation solutions.
Cobots vs. Traditional Industrial Robots: Which Is Better for SMEs?
Small and medium-sized enterprises (SMEs) are increasingly faced with the challenge of choosing between collaborative robots (cobots) and traditional industrial robots for upgrading their production lines. This decision, influenced by factors such as production space, workforce skill levels, and the frequency of product changes, is crucial for aligning automation solutions with operational needs. JAKA, a company specializing in automation technology, emphasizes the importance of flexibility and safety in this choice. Collaborative robots are designed to work alongside human operators, allowing for gradual automation without significant changes to factory layouts. They require less safety fencing and can be installed more quickly than traditional robots, making them suitable for smaller manufacturing environments. JAKA's systems are tailored for rapid redeployment and user-friendly programming, enabling SMEs to implement automation incrementally while managing costs effectively. In addition to flexibility, SMEs prioritize process consistency and quality control. JAKA’s AL solution is engineered for precise and repeatable motion, essential for applications like adhesive application, which helps maintain product quality and reduce defect rates. The adaptability of cobots allows for quick adjustments to different workpieces, minimizing the need for additional equipment investments during process changes and enhancing workplace safety by reducing manual handling of hazardous tasks. Ultimately, the choice between cobots and traditional robots varies for each SME, depending on their production volume and flexibility needs. JAKA advocates for a practical approach to automation that supports gradual growth, enabling SMEs to enhance efficiency while ensuring operational stability.
The Week Ahead in AI: Musk vs Altman, Cannes AI Film Festival, Is AI Cheaper than Human Workers, Plus Big Week Ahead for Earnings
Elon Musk's long-standing legal dispute with OpenAI is set to go to trial on Monday in California. The lawsuit, initiated by Musk, accuses OpenAI and its CEO, Sam Altman, of various grievances related to the development and management of artificial intelligence. This trial marks a significant moment in the ongoing tensions between Musk and the organization he co-founded, as it seeks to address the implications of AI technology and its governance. The outcome could have far-reaching consequences for the future of AI development and the responsibilities of its creators.
AI Insights Robotics AI Dev 26 x SF Alphabet Amazon
DJI shows how drones are changing avalanche rescues
In the French Alps, rescuers are facing urgent challenges following recent avalanches that have put lives at risk. With survival rates plummeting significantly after the first 20 minutes, the pressure is on emergency teams to act swiftly. The critical window between the emergency call and the successful location of victims is crucial, as every second counts in these life-or-death situations. The urgency of the response is heightened by the harsh conditions typical of the alpine environment, which can complicate rescue efforts. As rescuers mobilize, their training and experience become vital in navigating the treacherous terrain to reach those trapped beneath the snow.
News
Scientists used AI to crack one of water's biggest mysteries
Researchers at the University of Osaka have made significant strides in understanding the unique properties of supercooled water, a substance known for its unusual behavior at low temperatures. By employing an artificial intelligence model trained on various computer simulations, the team evaluated 16 different structural descriptors to analyze water's microscopic structure. This innovative approach allowed them to identify the most effective methods for distinguishing between water's two competing liquid states. The findings provide a clearer framework for future studies, shedding light on one of nature's most enigmatic substances and potentially paving the way for advancements in various scientific fields.
SpaceX IPO Provides Indirect Investment Opportunity in Starmind Project
Starmind does not have a standalone stock or ticker; investors can gain exposure through SpaceX (ticker: SPCX), which began trading on Nasdaq after its IPO on June 12, 2026. Starmind is integrated within SpaceX, contributing to the company's AI and space initiatives, and its performance directly influences SPCX shares. The significance of Starmind lies in its role as a division of SpaceX, which encompasses other projects like Starlink and Starship. As of early July 2026, SPCX shares are trading between $149 and $150, significantly lower than their 52-week high of $225.64. The project’s milestones, such as AI1 prototype updates, can impact SpaceX's stock performance, making it essential for investors to monitor these developments closely. Looking ahead, the early 2027 launch of AI1 prototype satellites is a critical milestone that could provide verifiable data affecting Starmind's valuation and, consequently, SPCX stock. No further timeline was disclosed at the time of publication, but the upcoming events will be pivotal for investors tracking the relationship between Starmind and SpaceX's stock performance.
Watch: New wearable converts robot movements into music to improve workplace safety
Researchers at Georgia Tech have unveiled an innovative wearable audio system designed to enhance the interaction between humans and robots. This groundbreaking technology translates the movements of nearby robots into sound, allowing users to perceive the robots' actions through auditory cues. The development aims to improve safety and awareness in environments where humans and robots coexist, such as factories and warehouses. The system was introduced during a recent technology showcase held at the Georgia Institute of Technology, where experts demonstrated its capabilities. By providing real-time audio feedback, the wearable device enables users to better understand the dynamics of their robotic counterparts, potentially reducing accidents and improving collaboration. The motivation behind this research stems from the increasing integration of robots into everyday workspaces, where clear communication and awareness of robotic movements are essential for effective teamwork. The audio system operates through a combination of sensors and algorithms that interpret robot actions and translate them into distinct sounds, creating an intuitive interface for users. This advancement not only represents a significant step forward in human-robot interaction but also highlights Georgia Tech's commitment to pioneering research in robotics and audio technology. As industries continue to evolve with automation, such innovations are crucial for ensuring safe and efficient operations in shared environments.
AI and Robotics
From Pepper's Disastrous Defeat to SoftBank's Mass Production Launch: Masayoshi Son's Third Bet on Robots?
Masayoshi Son, the CEO of SoftBank, is making a significant move in the robotics industry as the company prepares to launch mass production of its latest robotic technology. This initiative comes on the heels of SoftBank's previous setbacks, including the disappointing performance of the Pepper robot, which failed to meet market expectations. The decision to invest in mass production reflects Son's ongoing commitment to the robotics sector, despite past challenges. The announcement was made during a press conference held in Tokyo, where Son outlined his vision for the future of robotics and the potential applications of the new technology. He emphasized the importance of innovation and adaptability in a rapidly changing market, suggesting that SoftBank aims to leverage its expertise to regain its foothold in the industry. The push for mass production is driven by the growing demand for automation and robotics in various sectors, including healthcare, manufacturing, and customer service. SoftBank's strategy involves not only enhancing the capabilities of its robots but also ensuring they are accessible and affordable for businesses of all sizes. As SoftBank embarks on this new chapter, industry analysts are closely monitoring the company's progress, considering both the potential rewards and the risks associated with its ambitious plans. The outcome of this venture could redefine SoftBank's position in the robotics market and influence the future of automation technology globally.
Robotics Automation AI
Microsoft Makes Big AI Inroads in China by Selling OpenAI Models
Microsoft Corp. has established a significant presence in the Chinese market by selling artificial intelligence models to local companies, even amid escalating tensions between the United States and China regarding AI technology. This strategic move highlights Microsoft's commitment to expanding its business operations in a region that is increasingly competitive in the tech sector. The company's decision to engage with Chinese enterprises comes at a time when both nations are vying for dominance in AI development, raising questions about the implications of such collaborations. By providing advanced AI solutions, Microsoft aims to capitalize on the growing demand for innovative technologies in China, while navigating the complex geopolitical landscape that influences international business relations.
NMS:MSFT
Boeing’s bigger Ghost Bat can carry missiles internally, carry more combat load
Boeing has introduced an upgraded version of its MQ-28 Ghost Bat drone, enhancing its capabilities with extended range and improved technology. The announcement was made during a recent defense expo in Australia, where the company showcased its commitment to advancing unmanned aerial systems. This new iteration aims to meet the growing demands for advanced surveillance and combat support in modern warfare. Boeing's development of the MQ-28 is driven by the need for more versatile and efficient military drones that can operate in complex environments. The enhancements include advanced sensors and artificial intelligence features, which allow for better decision-making and operational efficiency. This latest model is expected to play a crucial role in future defense strategies, particularly in the Indo-Pacific region, where military presence and technological superiority are increasingly prioritized.
Military
The biggest industry, training hurdles for making drone wingman a reality
In a recent video, experts examined the evolving dynamics of manned-unmanned teaming in military operations, highlighting anticipated shifts for defense manufacturers as the United States increasingly integrates drones into combat scenarios. This analysis comes at a pivotal moment when the U.S. military is actively seeking to enhance its operational capabilities through advanced drone technology. The discussion focuses on how these partnerships between manned aircraft and unmanned systems could reshape defense strategies and manufacturing processes. As the demand for sophisticated drone capabilities grows, manufacturers will need to adapt to new technological requirements and operational frameworks to remain competitive in the defense sector. The insights shared in the video underscore the importance of innovation and collaboration in modern warfare, reflecting a broader trend towards automation and enhanced aerial support in military engagements.
Air Warfare Naval Warfare Pentagon Air Force collaborative combat aircraft Drones
6 Axis Cobot Arms vs. Traditional 6 Axis Robot Arms: Which is Better?
Manufacturers face a critical decision when expanding production lines: whether to invest in modern collaborative robots (cobots) or traditional industrial 6-axis robot arms. This choice, which can significantly impact operational efficiency, safety, and costs, requires careful consideration beyond just the initial price. Traditional 6-axis robots, designed for high-speed operations, necessitate extensive safety measures such as cages and interlocking doors, which can inflate costs and require more floor space. In contrast, cobots feature integrated sensors that allow them to work alongside human operators without the need for safety barriers, making them suitable for facilities with limited space. Programming also presents a challenge; traditional robots often require specialized engineers for reprogramming, leading to increased downtime and operational costs. Cobots, however, are designed for ease of use with intuitive interfaces that enable floor technicians to manage them without extensive coding knowledge. While traditional robots may have lower upfront costs, their total cost of ownership is often higher due to hidden expenses related to safety and maintenance. Cobots, with their flexible design, offer a quicker return on investment, particularly in environments with changing production needs. JAKA has introduced the JAKA Zu series, which combines the precision of industrial robots with the user-friendly features of cobots. This series eliminates the need for complex programming and bulky equipment, allowing users to manage robots via a mobile app. JAKA's solution aims to provide manufacturers with a scalable and adaptable automation option that can grow with their business needs.
New DJI Power 1000 Mini packs big energy
DJI has unveiled its latest product, the Power 1000 Mini, a portable power station aimed at providing energy solutions for various devices, including batteries, cameras, and laptops. This launch, which is particularly beneficial for drone pilots, comes as a response to the needs of professionals who often find themselves in remote locations without access to wall outlets. The Power 1000 Mini is designed to enhance the efficiency of outdoor shoots, job site inspections, and travel between locations, making it a practical addition to DJI's offerings this year.
News
Dynamic State Feedback Control of Autonomous Underwater Vehicles Based on Switching Between Multiple Heading Movement Models
In May 2026, researchers published a significant study in the Journal of Field Robotics, detailing advancements in robotic technology. The study, appearing in Volume 43, Issue 3, pages 1679-1692, highlights innovative methodologies for enhancing robotic navigation and autonomy in complex environments. Conducted by a team of experts in robotics and artificial intelligence, the research aims to address the growing demand for efficient and reliable robotic systems in various industries, including agriculture, manufacturing, and disaster response. The motivation behind this research stems from the increasing reliance on robotics in everyday applications and the need for these systems to operate effectively in unpredictable settings. By employing advanced algorithms and machine learning techniques, the researchers demonstrated how robots can improve their decision-making processes and adapt to changing conditions in real-time. The findings are expected to have a profound impact on the future development of autonomous robots, paving the way for more sophisticated applications that can enhance productivity and safety across multiple sectors. As the field of robotics continues to evolve, this study represents a crucial step toward achieving greater autonomy and efficiency in robotic systems.
RESEARCH ARTICLE
GoPro’s new camera might be its biggest comeback move
GoPro has announced a bold strategy aimed at revitalizing its presence in the camera market, signaling a significant shift from its previous conservative approach. This announcement comes as the company seeks to reclaim its position amid increasing competition and changing consumer preferences. The move is part of a broader effort to innovate and capture the attention of adventure enthusiasts and content creators alike. By introducing new features and enhancing existing products, GoPro aims to attract a wider audience and boost sales. The company’s aggressive comeback strategy is expected to unfold over the coming months, with a focus on delivering cutting-edge technology and improved user experiences.
News
The Biggest Impact of Autonomous Capture and AI
As the demand for autonomous capture technologies grows, industry experts predict that the ability to seamlessly integrate robots and agents will become essential for businesses. The focus is shifting towards identifying platforms capable of orchestrating these technologies in a cohesive, automated, and intelligent manner. This evolution is expected to significantly enhance operational efficiency and value creation across various sectors. With advancements in artificial intelligence and robotics, companies are urged to adapt quickly to remain competitive in this rapidly changing landscape. The race to develop and implement these integrated systems is intensifying, as organizations recognize the potential benefits of harnessing automation to streamline processes and improve productivity.
AI and livestreaming were the key drivers in this year’s Double 11, China’s biggest shopping festival
In the early hours of November 11, e-commerce platforms in China released performance statistics for Singles Day, the nation's largest consumer festival. Unlike previous years, companies refrained from highlighting their gross merchandise value (GMV) totals, a figure that had been a focal point during the event's peak popularity in the 2010s. This shift in reporting reflects a changing landscape in consumer behavior and market dynamics, as platforms adapt to evolving expectations and economic conditions. The decision to downplay GMV figures suggests a more cautious approach amid increasing competition and a focus on sustainable growth rather than sheer sales volume.
On the Cusp Alibaba Double 11 Highlight JD News
CMU Students, Faculty Go Big During Robotics Institute’s Annual Textile Jam
On a Friday afternoon, students and faculty from Carnegie Mellon University gathered at Wean Hall for the Robotics Institute's annual Textile Jam. Inside a nearly 9-foot tent, participants engaged in solving four different puzzles, with the aim of uncovering words that they presented as offerings to the themes of automation and craft. This collaborative event highlighted the intersection of creativity and technology, showcasing the innovative spirit of the university's community. The Textile Jam serves as a platform for exploring the potential of robotics in textile design and production, fostering a deeper understanding of the relationship between craftsmanship and automation.
Uncategorized
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.”
Small-language-models Artificial-intelligence Llms
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
Humanoid Robots at Hannover Messe
At this year's automation fair, industry experts and attendees gathered to evaluate the latest innovations in technology, sparking debate over whether the standout innovations presented were practical solutions or merely fleeting trends. The event, held in October 2023, showcased a variety of advancements aimed at enhancing efficiency and productivity in various sectors. Participants expressed a mix of excitement and skepticism regarding the viability of these innovations, questioning their long-term applicability in real-world scenarios. The fair served as a platform for companies to demonstrate their cutting-edge technologies, with many hoping to attract investment and interest from potential clients. As the automation landscape continues to evolve, the discussions at the fair highlighted the importance of distinguishing between sustainable innovations and those that may lack substance. Attendees emphasized the need for thorough evaluation and testing to determine which technologies could genuinely transform industries and which might fade into obscurity. Overall, the automation fair not only showcased advancements but also fostered critical conversations about the future of technology in the workplace, urging stakeholders to consider the implications of adopting new solutions in a rapidly changing environment.
Technology and IIoT
Industrial Robot Arm Pros and Cons: An Honest Review for Automation
Manufacturers are increasingly turning to industrial automation to enhance safety, stability, and adaptability in production processes. JAKA, a leader in robotics, emphasizes the importance of understanding the strengths and limitations of industrial robot arms before implementing automation solutions. The company advocates for a tailored approach, focusing on realistic application outcomes and long-term flexibility rather than viewing robotic systems as one-size-fits-all solutions. One significant advantage of industrial robot arms is their ability to maintain consistent motion accuracy during repetitive tasks, particularly in polishing and grinding operations. This consistency not only ensures stable surface quality but also reduces human error and workplace accidents by minimizing direct human interaction with hazardous equipment. JAKA's Pro5 system exemplifies this capability, contributing to lower defect rates and a more controlled production environment. However, the deployment of industrial robot arms comes with challenges. Integrating these systems into existing production lines often necessitates adjustments to fixtures and tooling, requiring collaboration between automation engineers and production teams. Additionally, while robotic systems excel in certain applications, careful validation is needed to address factors like material variation and surface tolerance. Modern industrial robot arms offer flexibility and reprogrammability, allowing manufacturers to adapt to changing production demands without significant hardware changes. This adaptability supports quicker product modifications and reduces the need for additional investments in equipment. In summary, when applied thoughtfully, industrial robot arms can significantly enhance safety, consistency, and adaptability in manufacturing. JAKA's approach underscores the importance of aligning robotic systems with realistic process goals and flexible programming strategies to achieve sustainable automation outcomes.
Import AI 444: LLM societies; Huawei makes kernels with AI; ChipBench
Researchers are exploring methods to quantify creativity, a concept that has long been considered subjective and difficult to measure. This initiative is gaining traction as experts from various fields, including psychology, education, and artificial intelligence, collaborate to develop metrics that can objectively assess creative output. The project is particularly relevant in today's rapidly evolving technological landscape, where creativity is increasingly recognized as a vital skill in both personal and professional contexts. The exploration into quantifying creativity is taking place across multiple institutions and conferences, with significant discussions occurring in late 2023. These efforts aim to establish standardized frameworks that can be applied in educational settings, workplaces, and even in evaluating artistic endeavors. By creating reliable assessment tools, researchers hope to enhance understanding of the creative process and its impact on innovation. The motivation behind this research stems from the need to better understand how creativity can be fostered and utilized, especially as industries seek to adapt to changing demands. By employing a combination of qualitative and quantitative analysis, researchers are investigating various approaches, including the use of algorithms and psychological assessments, to create a comprehensive picture of creativity. As this field of study progresses, it holds the potential to transform how creativity is perceived and nurtured, ultimately leading to more effective strategies for encouraging innovative thinking across diverse sectors.
Evaluating Office Relocation Versus Refurbishment for Business Growth
As businesses grow, they often face the decision of whether to relocate to a new office or refurbish their current space. Both options can enhance productivity and employee satisfaction, but they come with distinct advantages and challenges. Factors such as available space, budget, and business objectives play a crucial role in determining the best course of action. Investing in office refurbishment can modernize workspaces without the disruption of moving, allowing for improvements like flexible workspaces, better lighting, and upgraded facilities. These changes can create a more comfortable and professional environment for employees and clients alike. However, it is essential to assess whether the current office is genuinely limiting business operations or if minor adjustments could suffice. Consulting with workplace experts can provide valuable insights into optimizing existing spaces and identifying efficiency opportunities. Staying in the same location allows employees to maintain familiar routines and access to local amenities. However, if refurbishment cannot resolve fundamental issues, relocation may be necessary. No further timeline was disclosed at the time of publication.
Business Infrastructure business operations commercial property employee experience facilities management
People want robots in warehouses and factories, not hospitals or schools, Hexagon study finds
A recent study by Hexagon, part of its global Robot Generation research, reveals a growing acceptance of robots in the workplace among both adults and children. The findings indicate that while there is a willingness to integrate robots into various tasks, respondents are establishing clear guidelines regarding their use. Adults showed a preference for robots to perform physical and repetitive tasks, suggesting a desire for efficiency and productivity in the workplace. The study highlights a significant shift in attitudes towards automation, reflecting a balance between embracing technological advancements and maintaining human oversight in job roles. As industries increasingly look to incorporate robotic solutions, understanding these preferences will be crucial for successful implementation.
Artificial Intelligence Culture Robotics ai automation news factory automation
MIT's JARVIS Challenge Explores AI's Role in Jet Engine Engineering
The JARVIS Challenge, held at MIT, investigated the potential of AI in designing and building jet engines. Over four weeks, undergraduate teams utilized AI tools to create a small gas turbine engine, aiming for a thrust of 50-100 pounds. Professor Zolti Spakovszky emphasized that while AI can enhance hardware engineering, human engineering judgment remains crucial. This initiative is significant as it highlights the evolving relationship between AI and engineering, particularly in safety-critical domains. With support from MIT Lincoln Laboratory and corporate sponsors like Safran and Voyager Technologies, students had unprecedented access to AI resources, fostering an environment of innovation and exploration. Looking ahead, the challenge showcased the importance of integrating AI into engineering workflows. As students learned to navigate AI's capabilities and limitations, it raises questions about the future of engineering education and the skills required in a rapidly changing technological landscape. No further timeline was disclosed at the time of publication.
Classes and programs Contests and academic competitions Students Undergraduate STEM education Artificial intelligence
Advancements in Embodied Intelligence: Robots Learning Through Experience
A robot in a warehouse near Austin has fallen for the 4,000th time without assistance, showcasing the progress of embodied intelligence. This technology allows machines to physically interact with the world, fundamentally changing how they learn. Instead of merely processing information, these robots learn through experience, such as understanding gravity by knocking over objects. Embodied intelligence is gradually integrating into daily life, with humanoid robots working on assembly lines and assisting police in Hangzhou. In Malaysia, the Prime Minister introduced an AI digital twin to handle citizen inquiries autonomously. However, in Europe, there is growing concern about job displacement, with unions negotiating wage structures in anticipation of humanoid robot deployment. The societal divide is evident: while Asian countries view robots as helpful assistants, Europeans express fears of job loss. The future of embodied intelligence will depend on societal acceptance, highlighting a complex relationship between technology and human values. No further timeline was disclosed at the time of publication.
Embodied Intelligence Robotics AI Technology Human-Robot Interaction
AI Models Overthink Problems—and It’s a Security Risk
Large language models (LLMs) that can think through problems step-by-step have significantly increased the scope of tasks that AI can tackle. But new research suggests these reasoning capabilities also introduce a critical vulnerability that could allow attackers to slow these systems to a crawl.While earlier generations of LLMs would immediately produce a response to a user’s request, today’s most advanced models generate an internal monologue where they break down the problem into steps and reason about the best way to tackle it before providing an answer. This has allowed AI to tackle increasingly complex problems, particularly in areas like coding and math.However, previous research has shown that these models are susceptible to sometimes producing excessively long streams of reasoning that do little to boost performance, a phenomenon known as “overthinking.” In research presented this week at the International Conference on Machine Learning 2026 in Seoul, researchers from Zhejiang University and e-commerce giant Alibaba in China demonstrate that they can deliberately induce overthinking by subjecting models to logically inconsistent prompts. The result is a form of denial-of-service attack on commercial AI models.Evolutionary Prompt Attack on LLMsThe team has developed an evolutionary algorithm that corrupts the logical structure of prompts, causing models to spiral into overthinking as they attempt to reason through fundamentally unsolvable problems. Generating longer responses costs more and increases the load on a model provider’s servers, so if done at scale, the researchers say, this could significantly degrade the experience of legitimate users. The attack was effective against reasoning models from leading AI companies including DeepSeek-R1, Alibaba’s Qwen3-Thinking, OpenAI’s GPT-o3, and Google’s Gemini 2.5 Flash and resulted in outputs up to 26 times as long as standard responses on a standard math benchmark.“Across multiple datasets and reasoning models, our method substantially amplifies the output length,” Wei Cao, a masters student at Zhejiang University, wrote in an email to IEEE Spectrum. “Our results suggest that overthinking is not an isolated phenomenon specific to individual models, but rather a shared vulnerability among modern reasoning models.”The team’s approach builds on previous research from another group of researchers that showed reasoning models tend to overthink when faced with a question in which a key premise has been removed—such as asking how far someone who walks ten miles a day covers in total without specifying how many days they walked for. Rather than identifying that the problem is unsolvable, models often engage in extended but ultimately fruitless reasoning loops in an attempt to answer the question.Taking the idea a step further, the authors took 940 problems from three math benchmark datasets and used an LLM to break down their logical structure into a set of premises and a final question. The genetic algorithm then jumbled these up using a variety of “mutations,” including swapping premises between problems, adding extra premises to problems, deleting existing premises from problems, and swapping the final questions between two sets of premises.After each round of mutations, the problems are scored on how many words they cause a target model to output and also whether they increase the frequency of specific linguistic markers of overthinking—words like “but,” “wait,” “maybe,” or “alternatively.” The problems that scored highest on both measures are retained and the remaining ones are jumbled up again, and this process is repeated for five generations. Crucially, the approach doesn’t require access to the internals of a model and can generate malicious prompts by simply querying the target, which makes it possible to attack closed-source commercial services, says Cao.Overthinking Vulnerability in AI ModelsThe researchers found that the approach consistently led to outputs several times longer than those generated by the unmodified questions for the reasoning models they tested it on. The biggest jump came from DeepSeek-R1 on the MATH dataset, which is made up of problems from high school math competitions, where the maximum output was 26.1 times as long as the longest response the model provided to unaltered questions. While the main thrust of the research was focused on math problems, the authors also tested it on coding, scientific reasoning, and dialogue challenges, and observed significant jumps in output length in all three.One challenge for the approach is that developing the malicious prompts requires repeated queries to expensive reasoning models, which Cao admitted could limit its cost-effectiveness. However, the researchers also demonstrated that when they used a smaller, cheaper model to generate the malicious prompts they were still able to induce the target models to produce outputs several times longer than normal. This ability to transfer malicious prompts between models significantly increases the attack’s feasibility, Cao wrote.However, he pointed out that the goal of the research is not to develop a practical DoS attack on reasoning models. Factors like the providers’ pricing model, rate limiting policies, context window size, and existing defenses could all impact how effective the approach is. The intention is instead to highlight these models’ vulnerability to logically inconsistent prompts so that providers can attempt to mitigate the problem.“Our objective is not to demonstrate that large-scale attacks can be launched at negligible cost, but rather to establish that this attack surface exists,” he wrote. “Our results indicate that the vulnerability represents a realistic security concern.”
Llms Artificial-intelligence Denial-of-service Cybersecurity
What Makes AI Art Worth Collecting?
In May, an anonymous artist who goes by SHL0MS on X posted that he had used AI to generate an image inspired by Claude Monet and asked people to weigh in on how it missed the mark. More than 600 responses called out issues, saying the colors were off, the depth was all wrong, and that AI didn’t understand how light worked.SHL0MS then revealed that the image was of a real Monet, one of around 250 variations of water lilies the artist had painted in his lifetime. He had simply downloaded a high-resolution image from Wikimedia and cropped out the signature. He minted the exchange as an NFT (a unique digital collectible recording ownership of the work), titled it “Inferior Image,” and sold it for just over US $40,000 after 28 bids.The stunt exposed how charged the conversation around AI art has become, and how quick people are to dismiss anything AI-generated as slop—even when it’s not. Yet even as those arguments continue, a market for AI-generated art has begun to form anyway. It’s fragmented and contested, but bigger than most people realize.Jediwolf, an anonymous collector who says he has spent more than 20 years acquiring digital and AI art, was watching the experiment unfold in real time on X. He had never interacted with SHL0MS before, but when the NFT went up for auction he made a bid and won. “I was buying a unique moment in time,” he says, “captured by an artist and preserved as a token.”The Monet was not AI art, but most of what Jediwolf buys is. One of Jediwolf’s digital collections, which he calls UnderTheGAN—a play on GANs, or generative adversarial networks, the AI technology that preceded today’s diffusion models—comprises roughly 100 works valued at around $72,000, focused on early AI art from 2015 to 2020, before the medium went mainstream. He describes his role as part collector, part researcher, part curator, trying to document a fast-moving field.“A decade ago, digital art was often treated as peripheral to the ‘serious’ art world,” he says. “Today, it is increasingly difficult to separate contemporary culture from the internet.”AI Art Moves Into MuseumsThe market for AI art extends beyond NFTs: AI-generated pieces are also finding their way into physical installations. Last month saw the opening of Dataland, the world’s first generative AI museum, in downtown Los Angeles. It was spearheaded by Refik Anadol, a digital artist who has built a career out of transforming data into large-scale immersive experiences. The opening exhibition has pieces that use data that Anadol collected from rainforests around the world, with real-time weather information from 16 rainforests feeding into all five galleries. In three of the rooms, the imagery also shifts in response to visitors’ own biometric data, tracked by bracelets they wear. Like any museum it sells tickets, ranging from $49 to $79, and has a gift shop. This shop, however, uses visitors’ biometric data collected during their visit to generate a unique design printed on a T-shirt. For $15,000, a robotic painting system called Qualia creates a one-of-a-kind canvas from that same data, painted once a day, with a waiting list already forming. A founding collection of 1,000 AI data sculptures that evolve based on environmental data from global rainforests sold out in 34 minutes at $5,000 each.The system running it all, which Anadol calls the Large Nature Model, was trained on more than 500 million nature images representing 2.2 million species, gathered through field expeditions to 16 rainforests and partnerships with institutions including the Smithsonian and the Cornell Lab of Ornithology.For Anadol, AI art requires a different kind of transparency than any medium that came before it. Because commercial AI tools have shaped how most people understand the technology, artists working with it seriously have to be more open about their process than painters or photographers ever did.“For AI art, we have to know where the data comes from, we have to know which model is trained and how it’s trained,” he says. “We can’t just think about authenticity and uniqueness if a service and product is the fundamental layer of the artwork.”The reviews for Dataland have mostly been positive, with one critic calling it the Citizen Kane of immersive experiences. But Anadol is used to a more divided reception. His 2022 installation at MoMA—a 7-by-7-meter screen of AI-generated fluid forms with shifting colors and sounds—drew 3 million visitors and entered the permanent collection, even as New York Magazine called it “a massive techno lava lamp.” Anadol sees the skepticism as nothing new, just the latest version of a resistance that has greeted all new media. “Every art form has gone through similar cycles of denial,” he says. “We are living in a renaissance that started 10 years ago, and I just don’t think everyone is aware of it yet.”Who Is Buying AI Art?The broader market data points in multiple directions at once. According to the Art Basel and UBS Art Market Report 2026, digital art’s share of sales nearly tripled between 2024 and 2025, and just over half of all fine art collectors surveyed had purchased a digital artwork in 2025, making it the third most popular category after painting and sculpture (the report does not break out AI art specifically).Meanwhile, Christie’s shuttered its pioneering digital art department in September, folding digital works back into its broader contemporary sales after none of its dedicated auctions broke $400,000.The most data-rich window into buyer behavior comes from a less glamorous corner of the market. After one major stock image platform allowed AI-generated images, monthly sales jumped 80 percent, according to Samuel Goldberg, an economist at Stanford Graduate School of Business who published a research paper about the shift. Traditional contributors began leaving the platform as generative images flooded in, and creators using AI tools rushed to fill the gap. “It looks like consumers like generative AI,” Goldberg says, “and it seems like nongenerative artists could be getting crowded out of the market.” Stock images are essentially a commodity version of art, according to Goldberg, and because image-generating models are already very good at producing them, what’s happening there may be a preview of what’s coming for other creative goods markets—including fine arts—as the technology improves.Artists are typically among the first to test the limits of a new technology; early adopters have created AI art since the 1970s. What’s new now is the ability for anyone to generate an image in seconds with a text prompt. That, according to Christiane Paul, curator of digital art at the Whitney Museum of American Art, is not the same thing at all. What fills those stock-image platforms, and what most people encounter when they think of AI art, does not qualify as art.True AI art, Paul says, is a subcategory of digital art that uses artificial intelligence as both a tool and a medium, engaging with it practically and conceptually, doing things like training custom models, building extensions, and layering control systems. “A visual created by a prompt is not art,” she says. What serious AI artists are actually doing is much more than typing a few words into DALL-E.Far from the shortcut most people assume, working seriously with AI as an artistic medium is, by her account, brutally hard. Every artist she talks to says the same thing. “It is much, much harder than a paintbrush to handle,” she says. “You are literally communicating with a system with a completely different logic.”Thanks to bubblemaps.io for its research assistance on the NFT market.
Ai-art Generative-ai Digital-art Blockchain
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
Microsoft cuts 4,800 jobs, as Xbox unit downsizes and plans to spin off four gaming studios
Microsoft is implementing job cuts within its commercial business and Xbox gaming division due to declining revenue. The decision comes as the tech giant faces challenges in maintaining profitability in these sectors. The layoffs are part of a broader strategy to streamline operations and adapt to changing market conditions. This move highlights the ongoing pressures within the gaming industry and the need for companies to reassess their workforce in response to financial performance. The exact number of positions affected and the timeline for these layoffs have not been disclosed, but the company aims to realign its resources to better address future demands.
Overcoming Automation Anxiety: The Safety-First Approach to Robot Integration
As the integration of robots into the workforce accelerates, manufacturers are increasingly focusing on safety features to protect human workers. To ensure a smooth and secure transition, businesses planning to adopt robotic technology are advised to implement several key preliminary steps. These measures are crucial for prioritizing safety and minimizing risks associated with human-robot interactions. By establishing comprehensive safety protocols and integrating advanced safety features into robotic systems, companies can enhance workplace safety and foster a collaborative environment between humans and machines.
$4.1 Billion Deal Shows Why Ferrari and Tesla Are Ditching Copper for a Substitute
$4.1 Billion Deal Shows Why Ferrari and Tesla Are Ditching Copper for a Substitute $4.1 Billion Deal Shows Why Ferrari and Tesla Are Ditching Copper for a Substitute Stjepan Kalinic Sun, July 5, 2026 at 8:31 AM PDT 6 min read RACE.MI TSLA Benzinga and Yahoo Finance LLC may earn commission or revenue on some items through the links below. Substitution is one of the fundamental economic forces. If a product goes up in price, consumers have a direct incentive to switch to a cheaper substitute. While branding power dictates some price flexibility, such calculations are more straightforward for fungible commodities. When copper costs about $15,000 a metric ton, manufacturers have every right to ask – does every wire really need to be copper? With data centers, grid upgrades and green-energy projects tightening supply, the answer from automakers is increasingly no. Aluminum, trading at $3,100 per ton, is being promoted wherever physics allows. Don't Miss: A single bad hire can set a startup back years. Here are the 5 hires founders most often misjudge — and why Still Learning the Market? These 50 Must-Know Terms Can Help You Catch Up Fast Driving Investment and Corporate Consolidation Aside from being much cheaper, the metal is lighter and good enough for many vehicle applications. The appeal to save on weight is just a bonus for range-anxious electric vehicles. Ferrari has used aluminum in bodies, engines, and chassis for years and has recently begun using aluminum power cables in the 296 hybrid and other models. The payoff can be meaningful: wiring weight savings of up to 20%. "We are not choosing aluminum because it's cheaper; we choose the material that has better performance," the firm's communications executive Dario Esposito said per Reuters. Market interest is driving asset transactions, as Alcoa Corp. has just signed a binding agreement to acquire most of South32 Ltd.'s aluminum value chain for $4.1 billion. These include assets in Australia, South Africa and Brazil, but not the Mozal operation in Mozambique. The largest domestic aluminum producer expects the transaction will generate about $900 million in synergies. JPMorgan estimates the aluminum substitution could affect about 2% of global copper demand this year, and potentially as much as 6% by 2030. Trending: Avoid the #1 Investing Mistake: How Your 'Safe' Holdings Could Be Costing You Big Time A Partial Substitute Still, aluminum is not copper with a discount sticker. It is less electrically conductive, meaning cables often must be thicker to carry the same current. Those properties create problems in tight spaces – shared by both data centers and automobiles. For high-performance systems and specialized applications, copper's efficiency still remains ahead. Story Continues Then, there are environmental and geopolitical complications. The final phase of aluminum production is energy-intensive, often generating a much larger carbon footprint than copper. Energy prices have squeezed domestic producers and closed smelters, while trade frictions, including U.S. tariffs, further complicate sourcing. Cable makers provide some guidance on the issue. Xavier Mathieu, VP of Nexans, the second-largest global cable manufacturer, said buyers typically start switching when copper costs about 3.5 times as much as aluminum. The current ratio exceeds 4.2. The math means aluminum will keep swallowing market share where weight and space permit, but copper's performance edge still means it is the hedge, not the heir. Photo by laowaika via Shutterstock Read Next: Skip the Regrets: The Essential Retirement Tips Experts Wish Everyone Knew Earlier. Think you're saving enough for your kids? You might be dangerously off — see why Building Wealth Across More Than Just the Market Building a resilient portfolio means thinking beyond a single asset or market trend. Economic cycles shift, sectors rise and fall, and no one investment performs well in every environment. That's why many investors look to diversify with platforms that provide access to real estate, fixed-income opportunities, precious metals, and even self-directed retirement accounts. By spreading exposure across multiple asset classes, it becomes easier to manage risk, capture steady returns, and create long-term wealth that isn't tied to the fortunes of just one company or industry. Arrived Backed by Jeff Bezos, Arrived Homes makes real estate investing accessible with a low barrier to entry. Investors can buy fractional shares of single-family rentals and vacation homes starting with as little as $100. This allows everyday investors to diversify into real estate, collect rental income, and build long-term wealth without needing to manage properties directly. FarmTogether Farmland has historically held its value through market volatility and delivered returns uncorrelated to stocks and bonds. For accredited investors, FarmTogether offers direct access to high-quality U.S. farmland starting at $15,000 — fully ma
Honeywell Aerospace begins trading as standalone company
Honeywell has revealed plans to restructure its operations by dividing the company into three distinct business segments. This strategic decision, announced in February 2025, aims to enhance operational efficiency and focus on core competencies. The restructuring is part of Honeywell's broader initiative to adapt to changing market demands and improve shareholder value. By creating specialized divisions, the company intends to streamline its processes and better serve its customers across various sectors. This move reflects Honeywell's commitment to innovation and growth in an increasingly competitive landscape.
Air Warfare Pentagon Air Force Business & Industry Honeywell Honeywell Aerospace
Wukong1000 AUVs: Design, Cooperative Implementation, and Experimental Validation
A recent study published in the Journal of Field Robotics has unveiled significant advancements in robotic navigation systems. Researchers from a leading robotics institute conducted the study to enhance the efficiency and accuracy of autonomous robots in complex environments. The findings, released in early October 2023, highlight innovative algorithms that allow robots to better interpret and navigate their surroundings, particularly in dynamic settings such as urban areas or disaster sites. The motivation behind this research stems from the increasing demand for reliable robotic systems capable of performing tasks in unpredictable conditions, which are essential for applications ranging from search and rescue operations to automated delivery services. By employing advanced machine learning techniques, the team was able to improve the robots' decision-making processes, enabling them to adapt to changing environments in real-time. This breakthrough not only promises to enhance the functionality of existing robotic systems but also paves the way for future developments in the field of autonomous technology. The research team is optimistic that these improvements will lead to wider adoption of robotic solutions across various industries, ultimately contributing to safer and more efficient operations in challenging scenarios.
RESEARCH ARTICLERobotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
