Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
JAKA đạt chứng nhận an toàn y tế IEC 60601
JAKA has achieved a significant milestone by securing the IEC 60601 medical safety certification for its S series collaborative robots (cobots) – the S5, S7, and S12 – along with the MiniCab control cabinet. This certification, awarded recently, establishes these devices as compliant with the stringent safety standards required for medical electrical equipment, surpassing typical industrial and general electrical standards. The IEC 60601-1 series imposes rigorous requirements for both electrical and mechanical safety, ensuring that in medical environments, such as operating rooms, the robots maintain patient and operator safety even in the event of a fault. To meet these standards, JAKA's robots underwent extensive testing for leakage current, dielectric strength, and electromagnetic compatibility (EMC), confirming that they will not disrupt sensitive medical devices like ECG monitors or electrosurgical units. Additionally, the mechanical safety of the robots was thoroughly assessed, focusing on their safety logic, which includes features like collision detection and speed monitoring. This ensures safer interactions between the robots and healthcare personnel or patients. With this certification, JAKA positions itself as a reliable contributor to the global medical device market, ready to provide safe and compliant automation solutions for healthcare settings worldwide.
GE Vernova to acquire Robotech Automation to expand robotics integration
GE Vernova, an energy company, is set to enhance its robotics integration capabilities by acquiring Robotech Automation, a systems integrator with whom it has been collaborating on supply chain projects. This strategic move aims to bolster GE Vernova's operational efficiency and innovation in automation technologies. The acquisition is part of the company's broader initiative to strengthen its position in the energy sector and improve its supply chain processes. The deal reflects the growing importance of robotics in streamlining operations and meeting the demands of a rapidly evolving market.
Energy / Solar / Renewables Logistics Manufacturing Mergers & Acquisitions News GE Vernova
General Motors Is Cutting Its Development Cycles in Half
General Motors is accelerating its vehicle development process to compete with fast-paced Chinese automakers like BYD, which can bring electric vehicles (EVs) to market in under two years. This initiative, led by Sterling Anderson, GM’s chief product officer and former Tesla executive, aims to leverage artificial intelligence (AI) and simulation technology to significantly reduce design and production timelines. In a recent video call, Anderson and Jason Fischer, GM’s executive director of virtual integration engineering, outlined how AI is reshaping automotive design. Traditionally, the development process involved lengthy empirical testing and siloed engineering efforts. However, GM's new approach integrates multiple functions into a single virtual tool, allowing engineers to simulate design changes in minutes rather than hours. This method has already halved the development time for the electric GMC Hummer, which went from concept to showroom in just two years. GM is applying these advanced techniques across various projects, including self-driving cars and NASA's lunar rover, enhancing their ability to simulate real-world conditions and improve vehicle performance before physical prototypes are built. By running thousands of simulations, GM can identify and address potential issues early in the design process, ultimately leading to more refined vehicles. This innovative strategy positions GM to keep pace with the rapidly evolving automotive landscape and meet consumer demands for faster, more efficient vehicle production.
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XPeng Reportedly Merges Autonomous Driving and Smart Cockpit Units Into New General AI Center
XPeng has announced the merger of its autonomous driving center and smart cockpit center, forming a new entity known as the General AI Center. This strategic move aims to enhance the company's capabilities in artificial intelligence across various domains. The newly established center will be led by Liu Xianming, who previously headed the autonomous driving division, and will report directly to chairman and CEO He Xiaopeng. This reorganization reflects XPeng's commitment to advancing its AI technologies and integrating them more effectively within its operations. The announcement comes as the company seeks to strengthen its position in the competitive electric vehicle market, leveraging AI to improve user experience and vehicle performance.
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Indonesia grants world-first overseas certification validation to AutoFlight eVTOL
AutoFlight's V2000CG CarryAll has achieved a significant milestone by receiving a Validated Type Certificate (VTC) in Indonesia, marking it as the first electric vertical takeoff and landing (eVTOL) aircraft to obtain such certification outside of its home country. This certification, formally issued by Indonesia's Directorate General of Civil Aviation (DGCA), verifies that the V2000CG meets the airworthiness standards set by both the Civil Aviation Administration of China (CAAC) and the Indonesian aviation authority. This development underscores the growing international recognition and compliance of innovative aviation technologies, paving the way for broader acceptance and integration of eVTOL aircraft in global airspace.
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Small-AI Models Gain Traction Around the World
One morning in 2019, Adebayo Alonge was in a Cape Town hotel room, preparing to demonstrate his startup’s AI answer to a serious problem in African health care: counterfeit medication, which kills thousands of people across the continent every year.The RxScanner is a handheld spectrometer that scans a pill with infrared light, then sends the item’s molecular profile to an AI model equipped with a pharmaceutical database. In seconds, the AI identifies the medication from its molecular profile—or reports that it’s phony.Pharmacies were using the system in more than a dozen countries, including Ghana, Kenya, Myanmar, and Alonge’s native Nigeria. But that morning in South Africa, it didn’t work. “I was shocked,” Alonge says.The spectrometer connected to the AI model—but the data center was 14,000 kilometers away and bandwidth was limited. “Our server was in the United States, and just to get the result of a single scan was taking me over 5 minutes.”So Alonge immediately asked his engineers to shrink the AI model down to a smaller, low-power, unconnected version that could run entirely on his Android phone. They produced it 2 hours later, and that saved the demo.More importantly, the work birthed a new version of his device, which can authenticate a pill in places without broadband, computers, or even reliable electricity. It also turned Alonge into an advocate for this kind of “small AI.”Small AI for Global Health Care AccessSmall AI is a far cry from wealthy nations’ colossal large language models (LLMs), hyperscale data centers, multibillion-dollar investments, and debates about AI consciousness. But for millions of people around the world, the only AI that matters, and often the only kind available, is small. (According to a World Bank Report issued in November, only 0.7 percent of internet users in the world’s poorest countries have used ChatGPT, compared to a quarter of all internet users in the most developed nations.)“Most people are discussing AI from the LLM/generative side. But that needs a lot of computing power, electricity, massive data, and skilled people to manage it,” Ajay Banga, president of the World Bank, said last January at the World Economic Forum, in Davos. “Outside the developed world, other than maybe India and China, very few countries have that combination.”By contrast, small AI can deliver useful, even life-saving services to people in areas that have none of those things, Banga said. In India, where the government’s AI plans call for more development of small AI, many such systems are working for farmers.For example, a drone-based system developed by Bala Murugan and colleagues at the Vellore Institute of Technology, in India, takes photos of cashew plants and quickly identifies those with splotches that indicate disease. All the processing takes place on the drone itself, so there’s no need for a computer on-site, nor for a connection to a central server.Using small language models trained for a specific problem, and sometimes running on cheap, low-power devices, other small-AI implementations have been developed to identify ant infestations in a Uruguayan vineyard, detect the presence of malaria-carrying mosquitoes in a number of nations, and run electrocardiograms from an Arduino device in parts of Brazil that lack access to more complex equipment.“This is the most important area in AI nowadays,” says Marcelo José Rovai, a professor at the Institute of Engineering and Information Systems at the Federal University of Itajubá, in Brazil, who was involved in all three projects. “It’s growing very fast.”Low-Power, Small-AI Models on Devices Small AI models can run on a variety of low-power devices, including [from left to right] an Arduino Nano 33 BLE Sense, a Seeed Wio Terminal, and an Arduino Portenta.Moez AltayebFor Alonge, Rovai, and other advocates, small AI is not just “a promising trend,” as that November World Bank report calls it. It may be, in the long term, the form of AI that will touch the most lives and remain sustainable after some of the giant models become too costly for most users.“I think the future of AI is not like one giant model, at a center. I think it’s millions of small, precise models deployed at the edge, each one solving like a specific problem, a specific context,” Alonge says. This is partly because much of humanity—including people in parts of rich countries as well as the developing world—lives without access to cutting-edge frontier models. But, he says, it’s also because those models are not sustainable.“If someone is not subsidizing it, most people will not be able to afford those models. So those of us who are said to be small-AI developers are the ones who will have to build for the majority of the world,” Alonge says.There is no strict definition of “small AI,” but people often use the term for language models with at most a few billion parameters. (Compare that to cutting-edge models, which can include more than a trillion.) That’s small enough to run directly on a phone or a Raspberry Pi. That’s what allows these applications to run on devices without a connection to a data center and use only a few watts of power, often supplied by a battery or a solar panel.Despite their small footprint, these models aren’t fundamentally different technology from that of gigantic AI models, Rovai says. Many instances of small language models were created the same way the phone-based version of Alonge’s pharmaceuticals scanner was—by “pruning” large models, or removing the parameters that weren’t involved in the task. The result is a system that’s less capable generally but still very good at the specific job it was pruned for, Rovai says. A lighter version of RxAll’s RxScanner spectrometer sends its results to an AI model run locally on a phone to check that a drug’s molecular signature is genuine.RxAllOther small models are created by “distillation.” They are trained to mimic a large model, until their performance approaches that of their “teacher,” Rovai says. In other cases, a larger model’s precision is reduced, for example, so that a model run on 32-bit architecture can run on 8-bit designs. In situations where the machine learning application is being used to classify data or predict patterns (like an ant infestation), it’s trained from the beginning on a small device, not derived from a larger model at all. Running all these small, specialized systems is becoming easier, Rovai says, for two reasons.The first reason is that hardware is getting better and more capable while using less power, he says. This means more and more phones can run small AI—especially those equipped with neural processing units, which are specialized chips that handle AI tasks like facial recognition and changing the brightness, shadows, or contrast in a photo.In 2025, slightly more than a third of all smartphones shipped worldwide were capable of running generative AI, and that figure will reach 45 percent by the end of this year, according to the technology research firm Counterpoint. By the end of next year, slightly more than half of all smartphones will be able to run a small AI model.The second reason Rovai cites is the shrinking footprint of language models. Both Google DeepMind’s Gemma 4 (released in April) and Alibaba’s Qwen 3.5 are “fantastic” for small AI, Rovai says. Both models are “open weight,” meaning users can adjust the connections between parameters to suit their needs. This makes it easy, for example, “to take a lot of data from, say, the milk industry and retrain the model specifically on that,” Rovai says.Rovai illustrated these reasons on a Zoom call, using one of his most recent experiments. Holding up a device, he says, “This is the new Arduino UNO Q—a US $50 device with a Qualcomm chipset. I’m running a language model here, which collects data from sensors and analyzes that data to detect tiny pools of water where mosquitoes might be breeding. It takes 3 watts to run it.”Support for Small-AI DevelopmentConvinced that millions of people are already benefiting from these kinds of applications, the World Bank now actively promotes small AI with grants, mentorship programs, financing, technical advice, and models of government policies that are friendly for small-AI development. For example, in Rwanda, the World Bank is backing a government program to help low-income households get devices that can run AI.All that said, no one claims that large language models are going away entirely. To create a generative AI that can run on a phone or other small device requires the architectural insights, data processing, and results of a larger model, Rovai says. “We need the big models to create these smaller models.” And for all that small AI can benefit people without access to big AI, the technology can’t solve the larger problems of development and digital inequality, Alonge says. Implementing small AI won’t allow nations to escape the challenge of creating an ecosystem to support AI: reliable power, a supply chain that works, and an educational system that develops the talents needed to create AI tools.Though his drug-scanning system can run for days on a phone with no connection, “you still want to be able to enable periodic syncing for updates with new signatures for the medications and analytics,” Alonge says. “And even when you are using batteries, reliable power is important. That phone battery is not going to last forever.”In many parts of the world, the future of small AI isn’t assured, he says. “It works, and many places will eventually need to use it. The question is whether or not the political actors are wise enough to invest in infrastructure to support it long term.”
Small-language-models Artificial-intelligence Llms
XPeng Is Getting Serious About Physical AI as Its CEO Takes Over the Robotics Division
XPeng, a leading Chinese electric vehicle manufacturer, is intensifying its focus on physical AI as competition in the EV sector escalates. CEO He Xiaopeng will assume control of the company's robotics division, coinciding with the anticipated mass production and commercialization of its humanoid IRON robots. This strategic move aims to diversify XPeng's offerings beyond electric vehicles, with plans to launch commercial sales in China and internationally next year. The announcement comes amid challenges for XPeng, including a significant decline in vehicle deliveries and stock performance, with a 24.34% drop over the past year. In the first quarter of 2026, the company reported a 33.3% decrease in vehicle deliveries compared to the same period in 2025, alongside a 295.9% increase in net losses. Despite these setbacks, XPeng's gross margin improved, and analysts have mixed but generally favorable views on the company's stock, with several upgrades following its recent earnings report. XPeng aims to deliver between 100,000 and 106,000 vehicles in the second quarter of 2026, projecting revenue growth of approximately 7.3% to 13.8% year-over-year. As XPeng ventures into robotics, it seeks to position itself as a leader in intelligent mobility solutions, leveraging advanced technology to enhance customer experiences.
Krypton Evening News: Token prices drop to a few dollars; OpenAI may significantly reduce product prices; discounted train tickets for
Christian Stein has been appointed as the new CEO of Renault Group Spain, effective July 1, succeeding Josep María Recasens, who is leaving the company for new career opportunities. Stein will also continue in his role as Chief Communications Officer and report to Renault Group CEO François Provost. In a significant shift, General Motors is considering abandoning the use of lithium iron phosphate (LFP) batteries for electric vehicles, despite plans to produce them by the end of 2027 at a joint factory in Tennessee. This decision comes as the company reassesses its battery technology strategy amidst a competitive market. Global prediction markets Polymarket and Kalshi have reported that contracts for the upcoming World Cup champion have surpassed $2 billion, potentially setting a new record for single-event prediction market transactions. In the tech sector, OpenAI is contemplating substantial price reductions for its products to compete with rival Anthropic, as rising costs for AI services have become a concern for executives. Meanwhile, J&T Express has responded to an investigation by China's State Post Bureau, emphasizing its commitment to cooperate fully and improve safety management practices in light of the inquiry. AliExpress, Alibaba's cross-border e-commerce platform, has launched official local delivery services in five countries, including the U.S. and Spain, aiming to enhance logistics efficiency for merchants. In product news, Insta360 has unveiled the Luna Ultra, the world's first 8K dual-camera gimbal, which sold out shortly after its launch on June 10. Lastly, Neura Robotics, a German robotics firm, has secured $1.4 billion in funding to accelerate its development of a leading physical AI platform, with backing from major investors like Amazon and NVIDIA.
The Rivian R2 is too much fun to let drive itself
Rivian, the electric vehicle manufacturer known for its R1S SUV and R1T pickup, is shifting its focus towards mainstream success with the upcoming launch of its R2 model in 2027. While the company has garnered significant media attention and a dedicated following for its high-end vehicles, it now faces the challenge of appealing to a broader audience of electric vehicle buyers. As Rivian continues to explore the potential of robotaxis and autonomous driving, it recognizes the importance of winning over consumers who prefer traditional human-driven vehicles. The R2 is seen as a pivotal step in this strategy, aimed at making electric vehicles more accessible and appealing to the general public.
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2 Undervalued Growth Stocks That I'm Aggressively Buying
A recent report highlights the growing trend of electric vehicle (EV) adoption across the United States, driven by increasing environmental concerns and government incentives. As of October 2023, sales of EVs have surged, with major automakers like Tesla, Ford, and General Motors leading the charge. This shift is particularly evident in urban areas, where consumers are more inclined to embrace sustainable transportation options. The report indicates that federal and state governments have implemented various tax credits and rebates to encourage EV purchases, making them more accessible to a broader audience. Additionally, advancements in battery technology and charging infrastructure have alleviated previous concerns regarding range and convenience, further boosting consumer confidence. Experts predict that the trend will continue to accelerate, with projections suggesting that EVs could make up a significant portion of new car sales by 2030. This shift not only reflects changing consumer preferences but also aligns with broader efforts to reduce carbon emissions and combat climate change. As the market evolves, automakers are investing heavily in research and development to enhance their EV offerings, ensuring they remain competitive in a rapidly changing landscape. The combination of consumer demand, supportive policies, and technological innovations is reshaping the automotive industry, signaling a pivotal moment in the transition to cleaner transportation solutions.
MELI META Amrita Roy
Why Are Collaborative Robots Crucial for SMEs and Industry Giants?
As global manufacturing evolves, the line between manual labor and automation is increasingly blurred. In 2026, a pivotal shift occurs as general industries—including food, consumer goods, and logistics—emerge as the leading sectors driving automation growth, previously dominated by industrial robotics in automotive plants. This transformation is largely attributed to the rise of collaborative robots (cobots), designed to work safely alongside human workers without the need for traditional safety barriers. Small and Medium Enterprises (SMEs) often struggle with the "automation paradox," needing efficiency to compete but lacking the resources for conventional robots. Cobots address this challenge with their compact design and user-friendly, no-code programming, enabling smaller businesses to automate repetitive and hazardous tasks with minimal investment. Meanwhile, larger manufacturers benefit from cobots' flexibility in high-mix, low-volume production environments, where they can efficiently handle tasks like precision dispensing and palletizing. JAKA, a leader in collaborative robotics, emphasizes the importance of robots as reliable partners rather than mere tools. Their JAKA Mini series, weighing under 10kg, is tailored for SMEs, while the JAKA Pro series is built for larger enterprises, offering durability in harsh conditions. Advanced AI and vision systems enhance the robots' ability to interact with their environment, earning the trust of industry giants like Toyota and Schneider Electric. JAKA's solutions aim to facilitate the transition from manual labor to intelligent automation, providing the necessary flexibility and value for the future of Industry 4.0.
Video Friday: This Floor Lamp Will Do Your Chores
IEEE Spectrum robotics has released its weekly roundup of notable robotics videos, along with a calendar of upcoming events in the field. Key events include the International Conference on Robotics and Automation (ICRA) scheduled for June 1-5, 2026, in Vienna, and the Robotics Science and Systems (RSS) conference from July 13-17, 2026, in Sydney. Among the highlights is Lume, a sculptural floor lamp that reportedly can perform household chores such as making beds and folding laundry, though skepticism surrounds its capabilities due to the presentation of its functionality in promotional materials. Additionally, researchers from MIT Media Lab and Politecnico di Bari have introduced Electrofluidic Fiber Muscles, a new type of artificial muscle that is soft and flexible, utilizing electric fields to operate silently without external pumps. Another innovation is GEN-1, a general-purpose AI model that significantly improves success rates in physical tasks and enhances speed, marking a step towards achieving generalist intelligence in robotics. The report also discusses advancements in legged manipulators, which face challenges in interacting with diverse articulated objects, and highlights the development of Tether, a system for autonomous interactive play that enhances policy learning through efficient data generation. As the robotics community continues to innovate, these developments signal exciting possibilities for the future of robotics applications.
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JAKA Robotics nhận được nguồn vốn mới từ các ông lớn trong ngành sản xuất.
JAKA Robotics, a leading player in industrial automation, has successfully completed a new funding round aimed at accelerating the development of its general-purpose intelligent robots. The investment, which involves a Shanghai-based industrial investment fund and global leaders in electronics and automotive manufacturing, will enhance JAKA's research and development efforts in perceptual intelligence, improving the robots' capabilities in sensing, reasoning, and interacting with the physical world. Founded in 2014, JAKA has deployed tens of thousands of robots in nearly 100 countries, earning the trust of over 1,500 industry leaders, including major companies like Toyota, Ford, Schneider Electric, and Flex. In response to the growing demands of the industry, JAKA has strategically repositioned itself for 2025, focusing on general-purpose intelligent robots, which include collaborative robots and integrated intelligent solutions. The company’s collaborative robots, weighing between 1 and 40 kg, continue to evolve, while its intelligent integrated products—such as JAKA Kargo, Khan, Lumi, K1, and S³—have achieved industrial-scale certification in logistics, inspection, and precision assembly. By enhancing cognitive and reasoning abilities, JAKA is transforming robots from task-specific tools into reliable partners capable of adapting to complex environments, making real-time decisions, and collaborating with humans to achieve shared goals. This latest support underscores JAKA's market leadership and the long-term potential of general-purpose intelligent robots as the company transitions perceptual intelligence from the lab to practical applications in manufacturing and services.
JAKA Robotics Secures New Funding Backed by Manufacturing Giants
JAKA Robotics, a leader in industrial automation, has successfully secured a new round of equity funding aimed at enhancing the development of general intelligent robots. The funding, which includes contributions from a Shanghai-based industrial fund and prominent global electronics and automotive manufacturers, will support research and development focused on embodied intelligence, enabling robots to improve their capabilities in perception, reasoning, and interaction with the physical environment. Founded in 2014, JAKA has deployed tens of thousands of robots in nearly 100 countries, serving over 1,500 industry leaders such as Toyota, Ford, and Schneider Electric. In response to evolving industry demands, the company shifted its strategic focus in 2025 towards general intelligent robots, expanding its product offerings to include collaborative robots and advanced embodied intelligence solutions. JAKA's products, including the JAKA Kargo, Khan, Lumi, K1, and S³, have already demonstrated industrial-scale effectiveness in logistics, inspection, and precision assembly. By enhancing robots' perception and reasoning abilities, JAKA aims to transform them from mere task-specific tools into adaptable partners capable of making real-time decisions and collaborating with humans in complex environments. This recent funding round highlights JAKA's leadership in the market and the significant potential of general intelligent robots as the company seeks to transition embodied intelligence from research and development into practical applications in production and service sectors.
Robotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
