Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
SpaceX Launches Starmind Project for 1 Million AI Satellites by 2028
SpaceX has officially named its orbital AI infrastructure project 'Starmind,' which aims to deploy a constellation of up to 1 million satellites. This initiative, confirmed by Elon Musk on June 22, 2026, will enable AI inference directly in space, utilizing solar energy rather than terrestrial power sources. The first satellite, designated AI1, was unveiled on June 8, 2026, and is designed to operate in sun-synchronous orbits. The significance of Starmind lies in its potential to overcome the limitations faced by ground-based data centers, such as land, power, and water constraints. By running AI computations in orbit, Starmind can provide a more efficient solution to the growing demand for AI computing power. The project leverages the existing Starlink infrastructure for data transmission, distinguishing its function from Starlink's internet relay capabilities. Looking ahead, SpaceX plans to begin hardware deployment with the AI1 satellite, while full-scale production and deployment of the satellite constellation are targeted for 2028. As of now, no Starmind satellites have been launched, and further engineering challenges remain to be addressed, particularly regarding the scalability of the satellite design.
Siemens et la robotique : comment le géant allemand redéfinit l’usine intelligente
Siemens, the German conglomerate established in 1847, is playing a crucial yet often overlooked role in the transformation of industrial factories, particularly in the realm of robotics. While companies like ABB, FANUC, and KUKA are well-known for manufacturing industrial robots, Siemens focuses on redefining smart factories through its innovative technologies. The company does not produce robots directly but contributes significantly to the automation and efficiency of manufacturing processes. This shift towards smarter, more integrated factory systems is reshaping the landscape of industrial robotics, highlighting Siemens' influence in an area typically dominated by traditional robot manufacturers. The insights into Siemens' impact on industrial robotics were discussed in a recent article featured in Robot Magazine.
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Rockwell, Schneider, Beckhoff : La Guerre des architectures industrielles
In the context of Industry 4.0, the selection of an automation architecture has evolved into a strategic decision that will impact the scalability, cybersecurity, and software agility of manufacturing plants for the next two decades. Rockwell Automation represents the pragmatic strength of the North American approach, while Schneider Electric emphasizes software openness. This shift highlights the growing importance of architecture choices in the industrial sector, as companies navigate the complexities of modern manufacturing environments. The discussion surrounding these architectural strategies underscores the competitive landscape among industry leaders.
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NVIDIA Halos for Robotics: A New Era for Industrial Robot Safety
Recent advancements in industrial robotics have marked a significant milestone in the integration of physical artificial intelligence. Over the past few years, the field has experienced unprecedented growth, evolving beyond mere data analysis and text generation. Now, AI technology is enabling machines to perceive their surroundings, make real-time decisions, and interact directly with their environment. This evolution is exemplified by NVIDIA's latest innovations, which are set to enhance the safety and functionality of industrial robots. As these developments unfold, the landscape of robotics is transforming, paving the way for smarter and more autonomous machines in various industries.
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NVIDIA's Halos for Robotics: A New Era for Industrial Robot Safety
Recent advancements in industrial robotics have marked a significant milestone in the integration of physical artificial intelligence. Over the past few years, the field has experienced unprecedented growth, with AI evolving beyond mere data analysis and text generation. Now, machines equipped with this technology can perceive their surroundings, make real-time decisions, and interact directly with their environment. This transformation is highlighted in a recent article discussing NVIDIA's Halos for Robotics, which emphasizes the new era of safety in industrial robots. The developments signal a shift in how robots operate, enhancing their capabilities and effectiveness in various industrial applications.
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VivaTech 2026: The Year Humanoid Robots Became an Industrial Reality
VivaTech 2026, held at Porte de Versailles in Paris on June 17 and 18, marked its tenth anniversary by highlighting significant advancements in artificial intelligence and the maturation of robotics. The event showcased the growing trend of humanoid robots transitioning into industrial applications, reflecting a global shift in technology. Attendees had the opportunity to witness firsthand the innovations that are shaping the future of robotics, underscoring the industry's evolution and its increasing relevance in various sectors.
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Laser micro-perforation with camera: enhancing reliability in packaging films through industrial vision.
In the contemporary flexible packaging industry, achieving excellence extends beyond aesthetics to become a critical functional requirement. The optimization of permeability has emerged as a fundamental pillar in preserving the freshness of products, where every technical detail plays a vital role in extending shelf life and minimizing food waste. Recent advancements in laser micro-perforation technology, combined with industrial vision systems, are enhancing the reliability of packaging films. This innovative approach not only improves product preservation but also addresses the growing demand for sustainable packaging solutions. The integration of these technologies is transforming how the industry approaches packaging efficiency and effectiveness.
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Pourquoi Tesla mise des milliards sur Optimus ?
SpaceX, the aerospace company founded by Elon Musk, is poised to rival Tesla in the stock market as it continues to gain momentum. While Tesla has long been viewed as the leader in revolutionizing the automotive industry through its electric vehicles and innovative technology, recent developments suggest that SpaceX's advancements in space exploration and technology could shift investor focus. This potential shift comes at a time when Tesla is investing billions into its Optimus project, which aims to further enhance its technological capabilities. As both companies push the boundaries of innovation, the competition between them may redefine their respective positions in the market.
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Alibaba and ByteDance Invest in Embodied Intelligence: What Can Internet Giants Bring to Robotics?
On June 16, Alibaba introduced the Qwen-Robot series, a new line of embodied intelligence models designed to improve robotic capabilities. This launch marks a significant shift in the robotics industry, as Alibaba, alongside ByteDance, transitions from a passive observational role to active engagement in the sector. Both companies are utilizing their extensive resources and expertise to drive innovation in robotics. However, they face ongoing challenges related to hardware development and the commercialization of their products.
Embodied Intelligence Robotics Artificial Intelligence Automation
Leading Internet Giants Invest in Hangzhou's Robotics Company for Innovative Dexterous Hands
Xynova Future, a robotics company based in Hangzhou, has successfully raised hundreds of millions in Pre-A funding, with JD.com leading the investment round and significant backing from major players like Xiaomi. The funding aims to support the company's mission to develop advanced dexterous hands for humanoid robots, a technology designed to enhance the interaction between digital intelligence and real-world applications. This investment marks a significant step in the evolution of robotics, as Xynova Future seeks to innovate and expand the capabilities of humanoid robots in various sectors.
Dexterous Robotics Humanoid Robots Investment in Technology AI Robotics
Google’s new Universal Cart wants to follow you across the entire internet
In response to the evolving shopping habits of consumers, a leading technology company has announced the launch of Universal Cart, a new feature designed to streamline the online shopping experience. Recognizing that shoppers frequently use multiple devices and browse various retailers over extended periods, the initiative aims to simplify the purchasing process by allowing users to manage their shopping carts across different platforms seamlessly. This development comes as part of the company's ongoing efforts to enhance user convenience and adapt to the changing landscape of e-commerce. The Universal Cart is expected to roll out in the coming weeks, providing a unified shopping experience that caters to the modern consumer's needs.
AI Apps Commerce Google Google I/O google io 2026
Project Go-Big: Internet-Scale Humanoid Pretraining and Direct Human-to-Robot Transfer
Figure has unveiled Project Go-Big, an innovative initiative aimed at developing the largest humanoid pretraining dataset in collaboration with Brookfield. This ambitious project is designed to enhance the capabilities of robots, allowing them to learn navigation and manipulation tasks directly from human-generated video content. By achieving zero-shot transfer of skills, Project Go-Big is set to significantly advance the field of humanoid robotics. The announcement comes as the demand for more sophisticated robotic systems continues to grow, highlighting the importance of effective training methods in the evolution of robotics technology.
humanoid robotics machine learning artificial intelligence natural language processing data collection
Digital Twins: Transforming the Factories of the Future
As media attention focuses on humanoid robots and generative artificial intelligence, a less flashy yet equally transformative technology is quietly reshaping the global industry: digital twins. This innovative approach is emerging as a crucial element in the ongoing industrial transformation, offering strategic advantages that may rival those of more visible technologies. The concept of digital twins involves creating virtual replicas of physical systems, enabling companies to optimize operations and improve efficiency. This shift is expected to significantly impact the future of manufacturing, positioning digital twins as a foundational component in the evolution of factories worldwide.
À la une IA Industrie Robotique analyse de données industrielles automatisation industrielle.
Understanding Technological Singularity and Its Impact on Robotics and AI
For decades, technological singularity was more a concept of science fiction than engineering reality. Today, it is a topic of discussion among AI laboratories, industrial giants, investment funds, and robotics companies worldwide. The rapid advancement of generative AI, autonomous robots, foundation models, and AI agents raises a fundamental question: what will happen when machines can enhance their own intelligence faster than humans? The origins of the technological singularity date back to 1965 when British mathematician I.J. Good proposed that an 'ultra-intelligent machine' could trigger an intelligence explosion. In the 1990s, mathematician Vernor Vinge expanded on this idea, suggesting that once a certain level of AI is reached, technological evolution would become unpredictable for humans. Ray Kurzweil later popularized the concept, predicting that artificial general intelligence (AGI) could emerge in the coming decades, leading to continuous self-improvement of systems. Currently, the landscape is shifting rapidly, with large language models, vision-language-action models, and autonomous agents enabling robots to understand natural language instructions, interpret their environment, and learn new tasks without specific programming. Companies like NVIDIA, Google DeepMind, and Tesla are investing billions in developing this new generation of intelligent robots.
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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
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.
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Top 7 AI Agent Platforms for Industrial Manufacturing in 2026
The manufacturing sector is undergoing a significant digital transformation, marked by substantial investments in Internet of Things (IoT) sensors, Manufacturing Execution Systems (MES), industrial analytics, and predictive maintenance solutions over the past decade. This shift has provided manufacturers with unparalleled operational visibility, enabling real-time monitoring of equipment, production lines, quality metrics, and material flows. Despite these advancements, production managers continue to face challenges in optimizing processes and improving efficiency. The integration of these technologies aims to enhance productivity and streamline operations, ultimately driving the industry towards a more data-driven future.
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RoboScience launches Visics, a versatile embodied model for cross-ontology, cross-object, and cross-task applications.
On June 24, RoboScience, a company specializing in embodied intelligence, unveiled its self-developed Visics large model, introducing the innovative VLOA (Vision-Language-Object-Action) architecture. This announcement marks a significant advancement in the field, demonstrating the model's applications in real-world scenarios such as furniture assembly, dexterous grasping, and dynamic assembly lines. The current landscape of embodied intelligence lacks a universally accepted foundational representation unit, which hampers data collection, model learning, and the transfer of knowledge to new contexts. Traditionally, models have focused on replicating specific robotic movements tied to particular tasks, limiting their adaptability to new robots, objects, or environments. Founder and CEO Tian Ye highlighted three major challenges in robotic operations: poor generalization, difficulty in precise manipulation, and cumulative errors in long-range tasks. To address these issues, RoboScience has developed a new foundational representation unit from the ground up. The Visics model employs a dual-engine architecture, consisting of an embodied world model and a universal operation model, each operating independently. The embodied world model utilizes vast amounts of internet video data to learn the physical dynamics of objects, while the operation model translates object trajectories into actionable commands for robots. This layered design enhances the model's generalization capabilities across various robotic platforms and tasks. RoboScience's innovative approach also includes a high-precision simulation engine, RoboMirage, which, combined with automated video data annotation, significantly reduces data acquisition costs. The company aims to build a comprehensive dataset of over 1 terabyte of high-quality manipulation trajectories by 2026. Since its inception, RoboScience has garnered support from multiple investors and established research and production centers in major Chinese cities. The company plans to collaborate with various sectors, including retail and logistics, to standardize robotic products for industrial and commercial applications by the end of this year.
Dan Ives Predicts a Tesla-SpaceX Megamerger. Here’s What Investors Need to Know.
Wedbush analyst Dan Ives has predicted an 80% likelihood of a merger between SpaceX and Tesla within the next year, following SpaceX's recent IPO, which raised $75 billion and achieved a valuation of $1.7 trillion. If the merger occurs, it would unite Elon Musk's two publicly traded companies, creating a combined entity valued at approximately $3.6 trillion, positioning it as the fourth-largest company globally, behind Nvidia, Alphabet, and Apple. Ives suggests that the merger aligns with Musk's broader strategy, particularly in artificial intelligence, as both companies could leverage shared resources and expertise. SpaceX, known for its reusable rockets and Starlink satellite internet service, has seen its stock soar, closing at $169.36 on its first trading day, while Tesla, valued at $1.5 trillion, continues to innovate in electric vehicles and robotics. However, the merger poses challenges due to the differing markets of the two companies. Tesla is focused on the competitive electric vehicle sector, where investors closely monitor performance metrics, while SpaceX primarily operates as a government contractor in the aerospace industry. Despite these hurdles, the potential for collaboration in AI and engineering could make the merger appealing to investors.
Innocean, SBVA launch startup growth platform
Innocean, the advertising and marketing division of Hyundai Motor Group, announced on Monday its collaboration with SBVA, a venture capital firm previously known as SoftBank Ventures Asia. This partnership aims to establish UP 2026, a growth platform focused on fostering collaboration with high-growth startups and exploring new business opportunities. SBVA, affiliated with the SoftBank Group, has a diverse investment portfolio that includes over 100 startups across various sectors such as artificial intelligence, the Internet of Things, and robotics. The initiative reflects Innocean's commitment to innovation and strategic growth in an evolving market landscape.
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China’s Xiaomi unveils robotic arm that enables remote, hands-free home EV charging
Xiaomi, the prominent Chinese technology company, recently unveiled its strategic vision for the future of smart home technology during a press event held in Beijing. This announcement, made on October 15, 2023, highlights the company's commitment to enhancing user experience through innovative products and seamless integration of smart devices. The initiative aims to address the growing demand for interconnected home environments, driven by an increase in remote work and digital lifestyles. By leveraging advancements in artificial intelligence and the Internet of Things, Xiaomi plans to create a more intuitive and responsive ecosystem that simplifies everyday tasks for consumers. During the event, executives showcased a range of new products designed to work harmoniously within this ecosystem, emphasizing the importance of user-friendly interfaces and energy efficiency. The company also outlined its plans for expanding partnerships with other tech firms to enhance compatibility and functionality across various platforms. Xiaomi's vision reflects a broader trend in the tech industry, where companies are increasingly focused on creating smart solutions that cater to the evolving needs of consumers. As the market for smart home devices continues to grow, Xiaomi's proactive approach positions it as a key player in shaping the future of home automation.
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“Entanglement: A Brief History of Human Connection”
In a thought-provoking exploration of human connection, a recent discourse traces the evolution of communication from ancient cave drawings to the digital age. The narrative begins with early forms of storytelling, symbolized by a line etched in stone, and progresses through various historical milestones, including the invention of radio by Nikola Tesla and the development of the internet from ARPANET to the World Wide Web. The discussion highlights how these advancements have transformed the way people interact, emphasizing the importance of community and connection in an increasingly digital world. It reflects on the dual nature of technology, presenting both opportunities for deeper relationships and challenges such as distractions and misinformation. As artificial intelligence begins to engage with human emotions and experiences, the conversation raises questions about the essence of connection in the modern era. It posits that while the mediums of communication may change, the fundamental human desire for connection remains constant. The piece concludes with a call to action, urging individuals to be present and intentional in their interactions, reinforcing that the quality of our relationships ultimately shapes the quality of our lives.
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How SBTI turned MBTI into China’s latest viral meme
A new meme-style personality quiz known as SBTI has rapidly gained popularity on Chinese social media platforms, with users sharing screenshots of their results that feature humorous, slang-laden descriptions. While it may resemble the well-known MBTI framework at first glance, SBTI functions more as a viral internet joke, characterized by its reliance on mood, irony, and online shorthand. This trend began to surge on April 9, capturing the attention of a wide audience eager to engage in lighthearted self-reflection and social interaction through this playful format. The quiz's appeal lies in its ability to resonate with the cultural nuances of online communication, allowing users to connect and share their results in a fun and relatable manner.
On the Cusp
Beyond Cobots: Integrating Robotic Automation with AGVs and IIoT Systems
In recent years, manufacturing has experienced a significant transformation as companies shift from standalone automation to interconnected and flexible systems. JAKA, a leader in collaborative robot technology, has observed this evolution, where production environments are increasingly designed around coordinated robots, autonomous guided vehicles (AGVs), and Industrial Internet of Things (IIoT) platforms. This transition enables automation to adapt dynamically to real production conditions while ensuring safety and flexibility in workplaces that prioritize human interaction. Initially, collaborative robots were embraced for their ability to work safely alongside human operators, facilitating smoother automation processes. As their applications have matured, integrating these robots with AGVs and IIoT systems has become a logical progression. This integration allows for synchronized material handling and processing tasks, enhancing efficiency. IIoT connectivity further supports real-time data exchange, enabling predictive maintenance and improved process visibility, which is crucial for maintaining flexibility in production lines. AGVs play a pivotal role in extending automation beyond fixed workstations. When connected through IIoT infrastructure, these vehicles and robots can share crucial information, reducing idle time and manual interventions while enhancing workflow traceability. This coordination not only boosts operational efficiency but also increases transparency, allowing for continuous optimization and informed decision-making. To facilitate this integrated approach, JAKA has developed the Ai12, a collaborative robot designed for easy deployment through wireless teaching and graphical programming. This technology enhances safety and adaptability, allowing for seamless human-robot interaction. JAKA envisions a future where industrial robotic automation is not merely a collection of isolated machines but a cohesive system that evolves with production demands, fostering smarter and more responsive industrial environments.
AI Is a 5-Layer Cake
Artificial intelligence is increasingly recognized as a transformative force in the modern world, comparable to foundational technologies such as electricity and the internet. As of October 2023, AI has evolved beyond mere applications or specific models, emerging as a critical infrastructure that underpins various sectors and industries. This shift highlights the growing reliance on AI technologies to drive innovation, enhance efficiency, and address complex challenges across different fields. The widespread integration of AI is reshaping how businesses operate and how individuals interact with technology, marking a significant milestone in the ongoing digital revolution.
Douyin pushes further into travel with subsidy campaign, as competition among online platforms across sectors intensifies
Douyin, the Chinese counterpart of TikTok, is significantly enhancing its travel business by introducing a series of promotional initiatives aimed at boosting hotel bookings. The platform is allocating hundreds of millions of RMB in subsidies and has unveiled various discount packages, which include hotel calendar deals, livestream-exclusive vouchers, and brand membership bundles. This strategic move is designed to intensify competition among internet companies across different sectors, reflecting the growing importance of the travel market in the digital economy. By leveraging these promotions, Douyin aims to attract more users and increase engagement on its platform, positioning itself as a key player in the travel industry.
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Mistral AI Introduces Robostral Navigate for Autonomous Robotic Navigation
Mistral AI has launched Robostral Navigate, the first AI model specifically designed for robotic navigation. This marks a significant shift for the French company, which has previously focused on large language models, as it ventures into Physical AI. The goal is to enable robots to understand natural language instructions, interpret their surroundings using a standard RGB camera, and plan routes without relying on complex sensor infrastructures. The introduction of Robostral Navigate is important as it simplifies the navigation process, traditionally reliant on multiple technologies like LiDAR and depth cameras, which are costly and complex to integrate. By utilizing only RGB images and natural language commands, Mistral AI's approach could significantly reduce costs for robot manufacturers. An RGB camera is much cheaper than industrial LiDAR sensors, making this technology more accessible. Robostral Navigate operates on a model with 8 billion parameters, balancing computational power and operational efficiency. This size allows for faster execution on embedded platforms with limited resources, crucial for timely navigation decisions. Mistral AI trained the model on nearly 400,000 trajectories across over 6,000 simulated environments, showcasing its potential for real-world applications. No further timeline was disclosed at the time of publication.
À la une IA Industrie Robotique AMR benchmark R2R-CE
Palettisation automatisée : comment Liebherr booste la productivité
Liebherr-Verzahntechnik GmbH has announced the launch of a new range of modular and scalable palletizing solutions aimed at enhancing industrial productivity. This initiative comes in response to the growing need for optimization in production lines, which has become a strategic priority for manufacturers. The company’s recent communication highlights how these innovative solutions are designed to meet the evolving demands of the industry. By implementing these advanced palletizing systems, Liebherr aims to help businesses streamline their operations and improve efficiency in their manufacturing processes.
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NYU’s Quantum Institute Bridges Science and Application
New York University (NYU) has launched the NYU Quantum Institute (NYUQI) in Manhattan's West Village, positioning itself as a pivotal player in the rapidly evolving field of quantum technology. This initiative aims to harness the dense urban ecosystem surrounding the university, which is home to over 500 tech firms, banks, and hospitals, to accelerate advancements in quantum computing, sensing, and communications. The institute, led by Director Javad Shabani, seeks to break down traditional academic silos by fostering collaboration among physicists, engineers, and computer scientists. This integrated approach is designed to enhance the development of practical quantum solutions, which have been hindered by fragmentation in the field. NYUQI will operate from a newly renovated million-square-foot facility, complemented by a state-of-the-art Nanofabrication Cleanroom in Brooklyn, allowing for real-time testing and refinement of quantum technologies. Recently, New York Senators Charles Schumer and Kirsten Gillibrand secured $1 million in funding to introduce Thermal Laser Epitaxy technology at NYU, marking a significant advancement in the U.S. quantum research landscape. The institute also aims to address the skills gap in the quantum workforce by launching a Master of Science in Quantum Science & Technology program, preparing students to tackle complex challenges in this interdisciplinary field. By leveraging its urban location and fostering collaboration, NYUQI aims to transform theoretical quantum research into practical applications, ultimately contributing to advancements in finance, medicine, and security.
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What is an AMR?
In recent years, the industrial sector has witnessed a significant shift with the increasing adoption of Autonomous Mobile Robots (AMRs) in factories and warehouses. Traditionally, industrial robots were confined to specific production cells and operated behind safety barriers. However, AMRs are now gaining prominence due to their ability to navigate autonomously and transport materials efficiently within facilities. This transition reflects a growing interest among manufacturers in leveraging advanced robotics technology to enhance operational efficiency and streamline logistics processes. As industries seek to optimize their workflows, the integration of AMRs is becoming a crucial component in modern manufacturing and warehousing strategies.
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Tech for Industry Show: Technologies Transforming Industry
On June 23 and 24, 2026, the Tech for Industry exhibition took place in Paris, bringing together a rapidly evolving industrial ecosystem. As companies strive to enhance competitiveness, automate operations, and expedite their digital transformation, the event showcased that the concept of the industry of the future is now a tangible reality. This gathering highlighted the latest technologies that are reshaping the industrial landscape, reflecting the urgent need for innovation in a competitive market.
À la une IA Industrie Robotique automatisation industrielle. automatisation logistique
Advanced Humanoid Forum 2027 to be held in Germany
Germany is pushing to expedite the transition of humanoid robots from laboratory settings to industrial applications. As these robots gain increasing attention in media and announcements from major tech companies, a pressing question arises regarding their large-scale deployment in factories, warehouses, hospitals, and construction sites. This initiative was highlighted at the Advanced Humanoid Forum 2027, which took place in Germany, where industry leaders discussed the future integration of these advanced machines into various sectors. The motivation behind this acceleration is to enhance efficiency and productivity across industries, addressing the growing demand for automation.
À la une IA Industrie Robotique Santé Advanced Humanoid Forum
The startup aiming to place a humanoid in every factory and possibly every home.
In just three years, Figure AI has skyrocketed to a valuation of $39 billion, surpassing many publicly traded automotive manufacturers and becoming the leading humanoid robot producer globally. This remarkable achievement was confirmed in September 2025 during a Series C funding round. The startup aims to integrate humanoid robots into factories and potentially households, reflecting a growing interest in automation and robotics. Figure AI's rapid rise highlights the increasing demand for innovative technologies in various sectors.
À la une IA Industrie Robotique automatisation industrielle IA avenir de la robotique
L’IA physique : le prochain marché que surveille déjà Wall Street
As global attention remains captivated by ChatGPT and generative artificial intelligence, a new wave of innovation is quietly emerging within the laboratories of major tech companies, industrial firms, and investment funds. This development, known as "Physical AI," represents a significant evolution in the field of artificial intelligence. Although still relatively unknown, Physical AI is garnering interest from Wall Street investors, who are closely monitoring its potential market impact. The concept aims to integrate AI with physical systems, potentially transforming various industries and applications. As this technology progresses, it may redefine the landscape of AI and its practical uses in everyday life.
À la une IA Industrie Robotique ABB robotique Amazon robotsRobotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
