Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
First Stock in Visual Embodied Intelligence Launched: A Scene-Driven Company Goes Public
Ruiwei Technology, recognized as the first stock in visual embodied intelligence, made its debut on the Hong Kong Stock Exchange on July 8. Although the company's share price experienced a minor decline, the initial public offering (IPO) garnered significant attention, being oversubscribed by an impressive 3,646 times. This overwhelming demand reflects strong investor interest in the company's innovative approach to artificial intelligence. Ruiwei Technology specializes in practical AI applications, particularly within the airport sector, and is committed to transforming AI from merely an intelligence assistant into a productivity assistant. The company's product development strategy is uniquely tailored to meet the specific needs of various industries, positioning it as a forward-thinking player in the tech landscape.
Visual Intelligence AI Applications Robotics Airport Technology
Two Years of Rigorous Testing Across 52 Scenarios: Embodied Intelligence Redefines Visual Navigation Technology
As embodied intelligence moves from laboratory settings to practical applications, researchers are addressing a significant challenge: enabling mobile agents to navigate effectively without relying on satellite signals. A recent exploration into modular visual navigation technology reveals promising advancements that have been validated in extreme environments. This innovative approach enhances the capabilities of various robotic applications, paving the way for more robust and versatile navigation solutions in real-world scenarios. The development of this technology is crucial as it aims to overcome the limitations posed by traditional navigation systems, particularly in areas where satellite signals are unreliable or unavailable.
Visual Navigation Robotics Autonomous Drones Sensor Technology
Gaoyang Team's Breakthrough: Point-VLA Solves the Ultimate Challenge of Embodied Intelligence with a Single Visual Box!
The Gaoyang team from Qianxun Intelligent has unveiled Point-VLA, an innovative method designed to improve the accuracy of robot instructions through the use of a visual bounding box. This advancement is particularly significant as it enhances the success rate of robotic operations in complex environments, achieving a remarkable 92.5% success rate. The introduction of Point-VLA marks a notable step forward in robotics technology, addressing the challenges faced by robots in navigating and performing tasks in intricate settings.
Robotics Embodied Intelligence Visual Recognition AI
ABB Robotics completes Visual SLAM AMR range with autonomous forklift launch
ABB Robotics is expanding its Autonomous Mobile Robotics (AMR) portfolio with the launch of the Flexley Stack F712, creating a complete interoperable ecosystem across all major Visual SLAM AMR types. Combining autonomous forklifts, tugs and movers on one platform, ABB Robotics enables customers to automate a broader range of material-handling and intralogistics processes. Offering market-leading […]
Material handling News Warehouse robots abb robotics ai AMR Studio
ABB Robotics completes its AI-powered Visual SLAM AMR portfolio with new autonomous forklift
ABB Robotics completes its AI-powered Visual SLAM AMR portfolio with new autonomous forklift Visit http://go.abb/robotics for further information -The new Flexley Stack F712 extends ABB Robotics’ AI-powered Visual SLAM technology to autonomous forklifts, enabling pallet transport and high-density storage. -Customers can now deploy mixed fleets of Visual SLAM-powered tugs, movers and forklifts on a common navigation, fleet management and software platform. -Powered by ABB Robotics' AMR Studio, the portfolio enables up to 20% faster commissioning while ensuring seamless interoperability and safe, reliable operation. 07/07/26, 07:10 AM | Industrial Robotics, Mobile Robots | ABB Inc. ABB Robotics is expanding its Autonomous Mobile Robotics (AMR) portfolio with the launch of the Flexley® Stack F712, creating a complete interoperable ecosystem across all major Visual SLAM AMR types. Combining autonomous forklifts, tugs and movers on one platform, ABB Robotics enables customers to automate a broader range of material-handling and intralogistics processes. Offering market-leading accuracy, the F712 is designed for demanding material handling, end-of-line storage and warehouse operations across industries including automotive manufacturing, helping increase efficiency, flexibility and scalability. 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 Palladyne AI Executes $4.2 Million U.S. Air Force Contract to Advance Swarming Capabilities for Integrated Cross-Domain Operations 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 "Across intralogistics operations, businesses are being asked to process greater volumes in less time, while working with increasingly limited resources," said Marc Segura, President, ABB Robotics. "They are under pressure to move goods faster and with greater flexibility, while labour availability is becoming a critical constraint. As part of our journey to more autonomous and versatile robotics (AVRTM), we have combined advanced vision, mobility and intelligence in the Flexley Stack F712 forklift AMR, completing our scalable, AI-powered AMR portfolio." F712 is versatile, capable of handling multiple load types and sizes - including open and closed pallets, containers or racks- up to 2,000 kg and reaching heights of 8.5 meters. The Flexley Stack AMR F712 joins the Flexley Tug and Flexley Mover in ABB Robotics' growing Visual SLAM AMR portfolio. Applications include intralogistics tasks such as warehouse storage and retrieval, as well as line supply, end-of-line handling, body- and press-shop and drive-in and light buffer in the automotive and industries sector. Unlike conventional AMR forklifts on the market, F712 uses Visual SLAM to map and navigate its environment, eliminating the need for pre-installed infrastructure like markers or reflectors. The AI-enabled Visual SLAM supports the autonomous decisions required to operate in complex, dynamic warehouse operations with a market-leading positional accuracy of ±10 mm. Together with AMR Studio®, this shortens commissioning times by up to 20 percent and creates a versatile and reliable system that can adapt instantly when a warehouse or production floor layout changes. Certified to the latest ISO and ANSI safety standards, Flexley Stack F712 can safely operate at class-leading speeds of up to 1.7 m/s while loaded. F712 is fully integrated with AMR Studio and is VDA5050 compatible, enabling seamless integration with ABB Robotics' Visual SLAM AMRs and existing systems within a unified project. This makes it easy to manage complex projects and integrate different types of mobile robots. The no-code, drag-and-drop software suite supports rapid setup, fleet coordination, traffic management and real-time visualization, allowing ABB Robotics' tugs, movers and forklifts to operate together in the same layout for scalable turnkey automation projects. ABB Robotics as one of the world's leading robotics companies, is the only company with a comprehensive and integrated AI-powered portfolio covering robots, cobots and Autonomous Mobile Robots (AMRs), designed and orchestrated by our value-creating software. We help companies of all sizes and sectors - from automotive to electronics and logistics - to outperform by becoming more resilient, flexible and efficient. ABB Robotics is at the forefront of developing and commercializing a new generation of Autonomous Versatile Robotics
How World Models and VLA Can Be Implemented: Insights from Top Experts in Embodied Intelligence
At the 2026 Zhangjiang Embodied Intelligence Supply Chain Conference, a roundtable discussion brought together leading experts in robotics to explore the critical role of world models in embodied intelligence. The event highlighted various industry challenges, particularly the necessity for robust data infrastructure and the integration of visual-language-action models with world models. Experts emphasized that high-quality data and innovative technological solutions are essential for advancing the field. The conference served as a platform for addressing these pressing issues, aiming to foster collaboration and drive progress in robotics and artificial intelligence.
Embodied Intelligence World Models Robotics Data Infrastructure AI Integration
Invitation to the 2026 Zhangjiang EAI Conference on Embodied Intelligence
The 2026 Zhangjiang EAI Conference is set to delve into the evolution from visual models to physical interactions within the realm of embodied intelligence. Scheduled to take place in Zhangjiang, the conference will focus on significant advancements in world models and physical AI, alongside discussions on how to effectively integrate real-world data to improve robotic capabilities. The event seeks to connect theoretical technology with practical industrial applications, particularly addressing the challenges faced when deploying robots in dynamic environments. This initiative aims to foster innovation and collaboration among experts in the field, ultimately enhancing the functionality and adaptability of robotics in various sectors.
Embodied Intelligence Physical AI World Models Robotics Data Integration
Zhejiang University Team Creates Visual Reasoning System That Lets Robots 'Think With Their Eyes' — 22x Faster Than Text
A team of researchers from Zhejiang University, in partnership with Cornell University, the National University of Singapore, and Xidian University, has unveiled an innovative visual reasoning system named VisualThink-VLA. This advanced technology allows robots to process visual information directly, enabling them to "think with their eyes" instead of relying on traditional language-based reasoning. The system boasts a remarkable speed enhancement, operating 22.8 times faster than conventional text-based methods, while also achieving greater accuracy. This development marks a significant advancement in the field of robotics and artificial intelligence, potentially transforming how machines interpret and interact with their environments.
Technology
Interview with Oakfruit: Moving Beyond VLA to Instinct-Driven Intelligence
In a recent interview, Oakfruit Robotics addressed the significant challenges confronting the embodied intelligence sector, particularly highlighting the constraints of the Visual-Language-Action (VLA) model. The company introduced an innovative approach known as 'Instinct-Driven' technology, which seeks to improve robotic autonomy and operational intelligence. This advancement is expected to facilitate mass production and expand the application of robotics across various industries, potentially transforming how robots interact with their environments and perform tasks. The insights shared by Oakfruit Robotics underscore the need for evolution in robotic technology to meet growing demands and enhance functionality.
Embodied Intelligence Robotics AI Technology Automation
Former Meituan delivery tech chief starts a venture for an "restaurant world model" in the era of embodied intelligence.
AtomBite.AI, a company specializing in embodied intelligence, has secured a multi-million dollar seed funding round led by InnoTech Venture Capital, with participation from the Tsinghua Alumni Seed Fund and notable individual investors. This funding will primarily support the development of embodied world models for the restaurant industry and the implementation of core products. The company's founding team, which includes Dr. Wang Dong, a former technical lead at Meituan's food delivery division, aims to address inefficiencies in restaurant kitchens, particularly in the packaging and delivery processes that still heavily rely on manual labor. As global food delivery orders continue to rise, AtomBite.AI identifies the kitchen as a promising application area for embodied intelligence, given its universal demand and clear return on investment for businesses. The team plans to create a "World Action Model" tailored for the restaurant sector, emphasizing the integration of visual and tactile feedback to enhance robotic operations. Their approach focuses on developing a system that learns from real-world interactions rather than relying solely on generalized models. Currently, AtomBite.AI is targeting the packaging and transfer stages of food delivery, which are prone to errors and have quantifiable value. The company anticipates deploying its packaging model in commercial kitchens by 2026, with plans to expand into more complex kitchen operations and broader service industry applications in the future.
AI-powered visual inspection using robots
GFT Technologies has unveiled an innovative AI-driven solution designed for automotive production, which integrates visual inspection with intelligent control of robotic systems. This advancement aims to enhance quality assurance processes within the industry, leveraging artificial intelligence to improve efficiency and accuracy in manufacturing. The announcement highlights GFT's commitment to advancing technology in automotive production, showcasing how AI can transform traditional inspection methods through automation.
Allgemein Künstliche Intelligenz & maschinelles Lernen Lösungen Robot Vision & Inspection
The Death of VLAs: Unraveling the True Challenges of Embodied Intelligence
At the Sequoia AI Summit, NVIDIA's Jim Fan made headlines by declaring that "VLA is dead," igniting a conversation about the shortcomings of visual-language models in the realm of embodied intelligence. This statement highlights the growing recognition within the tech community of the necessity for enhanced physical capabilities in AI systems. The discussions at the summit emphasized the importance of developing world models that can better address the limitations currently faced by visual-language models. As the field of artificial intelligence continues to evolve, experts are calling for innovative solutions to improve the integration of visual and physical understanding in AI applications.
Embodied Intelligence Visual-Language Models World Models Robotics AI Technology
Dexbotic 2.0: Advancing Embodied Intelligence with PyTorch
Dexbotic 2.0 has been enhanced into a robust framework aimed at advancing embodied intelligence, specifically tackling significant challenges in the integration of Visual Language Agents (VLA) and Reinforcement Learning (RL). This upgraded framework is instrumental in training the DM0 model, which has recently achieved the top position in the RoboChallenge rankings, demonstrating its superior capabilities in executing complex real-world robotic tasks. The development reflects ongoing efforts to improve robotic intelligence and performance, marking a significant milestone in the field.
Embodied Intelligence Robotic Framework Deep Learning AI Models
Transforming Embodied Intelligence: Pure Vision Technology Reshapes Navigation in Extreme Environments
Embodied Intelligence is addressing the challenges of navigation in extreme environments where satellite signals are unavailable. The company has introduced a modular pure vision navigation technology that has been successfully validated in 52 real-world scenarios. This innovative solution is set to enhance the operational capabilities of various robotic applications, allowing them to navigate complex terrains more effectively. The development comes at a crucial time as industries increasingly rely on autonomous systems for tasks in remote or signal-deprived locations. By leveraging advanced visual processing techniques, Embodied Intelligence aims to provide reliable navigation solutions that can adapt to diverse operational conditions.
Robotics Navigation Technology AI Autonomous Systems
YouTime Technology Secures Hundreds of Millions in Series B Funding, Expanding from L4 Visual Autonomous Driving to Humanoid Robots
YouTime Technology, a company focused on L4 low-speed autonomous driving, has successfully raised hundreds of millions of RMB in a Series B funding round, with Qianhai Ark leading the investment. This funding, finalized recently, aims to facilitate the company's transition to embodied intelligence and advance the development of multimodal AI agents. Additionally, the capital will enhance the visual navigation capabilities of their humanoid robots, positioning YouTime Technology for significant growth in the autonomous driving sector.
Autonomous Driving Humanoid Robots AI Technology Computer Vision
Say Goodbye to Data Scarcity and Selection Challenges! Xinbai Te Unveils Comprehensive Data Collection Solutions for Embodied Intelligence
The 3rd China Embodied Intelligence and Humanoid Robotics Industry Conference is set to take place on April 18, where Xinbai Te Technology will unveil its partnership with UR Robotics. This collaboration aims to present a comprehensive robotic data collection solution, highlighting advancements in visual perception, motion teaching, and tactile control. The event promises to showcase the latest innovations in the field, reflecting the growing interest and investment in robotics and artificial intelligence technologies.
Robotic Data Collection Embodied Intelligence Collaborative Robots AI Technology
Physical Intelligence Finds 'Emergent' Bridge Between Human Video and Robot Action
A $5.6 billion startup has announced a breakthrough in artificial intelligence, revealing that sufficiently large robot models can autonomously learn to comprehend human video. This development has the potential to address a significant data bottleneck that has long plagued the industry. The startup's findings, which were shared recently, highlight the capabilities of advanced machine learning techniques in enhancing the understanding of visual content. By leveraging large-scale models, the company aims to improve the efficiency and effectiveness of AI systems in processing and interpreting video data, paving the way for more sophisticated applications in various fields. This innovation could transform how machines interact with visual information, ultimately leading to more intuitive and responsive AI technologies.
Data Collection Physical Intelligence embodied-ai
Fourier Intelligence unveils the “Care-bot” GR-3, its first full-sized companion humanoid robot
On Wednesday, Chinese robotics company Fourier Intelligence unveiled its inaugural full-sized humanoid robot, the “Care-bot” GR-3, designed for interactive companionship. The robot, which stands 165 cm tall and weighs 71 kg, boasts 55 degrees of body freedom, allowing for a wide range of movements. The GR-3 is equipped with a comprehensive sensory interaction system that combines auditory, visual, and tactile modules, enhancing its ability to engage with users. This launch marks a significant step in the development of robots aimed at providing companionship, reflecting the growing interest in robotics for personal and social applications.
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SLAMCORE SECURES $14M, BACKED BY INVESTORS INCLUDING ROCKWELL AUTOMATION, TO SCALE VISUAL AI ACROSS INTRALOGISTICS
Slamcore has successfully raised its total funding to $40 million, showcasing significant market growth by deploying its technology in over 30 facilities and scaling to hundreds of units within just two years. The company’s innovative Slamcore Aware and Alert solutions leverage proprietary artificial intelligence and stereo camera technology to enhance site safety and improve fleet efficiency. Notably, these advancements do not necessitate costly modifications to existing facilities or additional infrastructure. By effectively tracking vehicles in diverse industrial environments, Slamcore is amassing extensive datasets that are essential for developing the next generation of Physical AI.
Robot Talk Episode 154 – Visual navigation in insects and robots, with Andrew Philippides
In a recent conversation, Claire engaged with Andrew Philippides, a Professor of Biorobotics at the University of Sussex, to explore insights from the behaviors of ants and bees that could enhance robot navigation systems. Philippides, who co-directs the Centre for Computational Neuroscience and Robotics as well as the be.AI Leverhulme Doctoral Centre for Biomimetic Embodied AI, emphasized the potential of studying these social insects to inform the development of more efficient and adaptive robotic technologies. The discussion highlighted how the intricate navigation strategies employed by ants and bees can inspire innovative approaches to solving complex challenges in robotics. This dialogue took place at the University of Sussex, a hub for advanced research in robotics and artificial intelligence, underscoring the institution's commitment to interdisciplinary collaboration and the application of biological principles in technological advancements.
Emerson Accelerates Edge Ecosystem for Real-Time Enterprise Operations Intelligence
Emerson, a prominent player in the global automation sector, has unveiled its latest innovation, DeltaV™ Live Enterprise View, aimed at enhancing real-time control system visualization beyond traditional control room boundaries. This new application, launched recently, is designed to provide secure access to critical operational data, enabling users to monitor and manage industrial processes more effectively from various locations. By leveraging advanced technology, Emerson seeks to empower industries with improved decision-making capabilities and operational efficiency, addressing the growing need for flexible and remote access in today’s fast-paced industrial environment.
Review of Essential Generic Technologies for Visual Perception in Underground Coal Mine Robots
A recent study published in the Journal of Field Robotics highlights advancements in autonomous robotic systems designed for agricultural applications. Researchers from various institutions conducted experiments to evaluate the efficiency and effectiveness of these robots in crop monitoring and management. The study, released in early October 2023, took place in diverse agricultural settings, showcasing the robots' capabilities in real-time data collection and analysis. The motivation behind this research stems from the increasing need for sustainable farming practices and the demand for improved crop yields amidst growing environmental challenges. By integrating advanced sensors and artificial intelligence, the robotic systems demonstrated significant potential in reducing labor costs and enhancing precision in farming operations. Through a series of field tests, the researchers assessed the robots' performance in various tasks, including soil analysis, pest detection, and irrigation management. The findings indicate that these autonomous systems can operate efficiently under different weather conditions and terrains, offering a promising solution for modern agriculture. The study underscores the importance of innovation in addressing food security and environmental sustainability, paving the way for further developments in agricultural robotics.
RESEARCH ARTICLE
DAS‐SLAM: A Novel Visual‐Inertial SLAM System in Dynamic Environments Integrating Object Detection Network and Scene Flow Technology
A recent study published in the Journal of Field Robotics explores the advancements in robotic technology and its applications in various fields. Researchers from leading universities conducted the study to assess how these innovations can enhance efficiency and safety in industries such as agriculture, construction, and disaster response. The findings, released in early October 2023, highlight the potential of autonomous robots to perform tasks that are hazardous for humans, thereby reducing risks and improving productivity. The research team utilized a combination of field tests and simulations to evaluate the performance of different robotic systems in real-world scenarios. Their work emphasizes the importance of integrating artificial intelligence and machine learning to enable robots to adapt to dynamic environments. As industries increasingly seek automation solutions, this study provides valuable insights into the future of robotics and its role in transforming traditional practices. The motivation behind this research stems from the growing demand for innovative technologies that can address labor shortages and enhance operational capabilities. By showcasing successful implementations of robotic systems, the study aims to encourage further investment and development in this rapidly evolving field. The implications of these findings could lead to significant changes in how industries approach tasks that require precision and safety, ultimately paving the way for a more automated future.
RESEARCH ARTICLE
Slamcore secures $14 million funding from investors including Rockwell Automation
Slamcore, a company specializing in spatial intelligence software, has successfully secured $14 million in a recent funding round, attracting notable investors such as ROKStar Ventures, a subsidiary of Rockwell Automation, a leader in industrial automation and digital transformation. This latest investment elevates Slamcore's total funding to $40 million, with previous support from prominent backers including Toyota Ventures and Interwoven Ventures. The funding aims to enhance Slamcore's development of innovative technologies that improve spatial awareness and automation capabilities across various industries.
Financials & Investments News Software ai funding AI software amrs
Ant Group Launches Open Source LingBot-Vision: A Breakthrough in Robotic Vision Technology
Ant Group's Robbyant has introduced the LingBot-Vision model, a groundbreaking visual perception technology designed for robots. This innovative model, which operates with just 1.1 billion parameters, significantly outperforms traditional systems in depth estimation and object boundary recognition. By enhancing robots' ability to comprehend intricate environments, LingBot-Vision represents a major leap forward in the field of embodied intelligence. The technology has been made available as open-source, fostering further advancements and collaboration within the robotics community.
Robotic Vision Depth Perception AI Technology Open Source Embodied Intelligence
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
Glass crashes slashed? Ant Group embodied AI unit claims breakthrough in robot sensing
Robbyant, the embodied artificial intelligence arm of Chinese fintech giant Ant Group, launched a new vision model that it claims can help robots overcome a long-standing challenge: accurately perceiving glass, mirrors and transparent objects. The unit of Hangzhou-based Ant Group on Tuesday unveiled its next-generation spatial perception model, LingBot-Depth 2.0, alongside a new foundational visual model called LingBot-Vision, as AI labs race to equip machines with the “brains” required to...
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
Tsinghua alumni launch AI startup, securing hundreds of millions in angel funding for the automotive industry.
Embodied intelligence company Guangxiang Technology has successfully secured hundreds of millions in angel funding, with significant participation from leading investors including Zhuhai Technology Industry Group, Xingsheng Capital, and several others. Founded in April 2025 through a collaboration between Tsinghua University's Vehicle and Transportation Institute and its AI Institute, Guangxiang aims to advance the development of its physical native base model and commercialize embodied intelligent robots for industrial applications. The company's founder and CEO, Zhang Tao, previously led the spatial perception engine at Amap, while co-founder Professor Li Shengbo is a renowned expert in reinforcement learning and autonomous driving. The team, which includes members from major tech firms like Alibaba and Huawei, is focused on a unique technological approach that diverges from mainstream visual-language-action models. Guangxiang's flagship product, the Phi-Bot X1, was launched in June 2026 and is designed for industrial environments. The robot has demonstrated impressive capabilities, completing a full welding operation on an automotive production line without errors during a 21.5-hour continuous run at the 2026 ATC exhibition. The company plans to expand its applications in the automotive sector, targeting the remaining 30% of automation gaps that traditional methods cannot address. Zhang envisions a robust market for automotive production line robots, estimating a potential market size of around 100 billion yuan in China. Guangxiang Technology is committed to refining its products and scaling operations, with a focus on real-world applications and continuous feedback to enhance its offerings.
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
Tactile Data Competition Begins: Qianjue's Gripper Transforms Robot Training
Qianjue Robotics has unveiled the XTac UMI G1, a groundbreaking wearable multi-modal data collection gripper aimed at addressing the challenges of embodied intelligence in robotics. The introduction of this innovative device comes in response to the industry's pressing need for high-quality tactile data, which is essential for training robots to perform complex tasks in real-world environments. By capturing detailed interaction data, the XTac UMI G1 seeks to bridge the existing gap between visual data and physical interaction, thereby enhancing the capabilities of robots. This development marks a significant step forward in improving robotic performance and adaptability in various applications.
Tactile Data Collection Robot Training Embodied Intelligence Robotics Technology
General Intuition in talks to raise $300M at around $2B valuation
A startup specializing in artificial intelligence is leveraging Medal's extensive dataset, which comprises 2 billion videos annually sourced from 10 million active users each month. This initiative aims to enhance the training of embodied AI and world models, utilizing the rich variety of visual content available. The training process incorporates data collected up until October 2023, allowing the AI systems to develop a more nuanced understanding of real-world scenarios and interactions. By harnessing such a vast and diverse dataset, the startup seeks to push the boundaries of AI capabilities, ultimately contributing to advancements in technology that can better interpret and interact with the world around us.
AI Fundraising ai agent Exclusive general intuition world models
Tsinghua University and Shouyi Technology Launch EgoEMG Dataset for Hand Pose Estimation
Researchers from Tsinghua University and Shouyi Technology have unveiled the EgoEMG dataset, marking a significant advancement in the field of hand pose estimation. This innovative dataset is the first of its kind to publicly integrate electromyography (EMG), visual, depth, and motion data, providing a comprehensive resource for studying hand movements. Released in October 2023, the dataset aims to enhance embodied intelligence by offering precise data on hand operations. Its development is expected to facilitate progress in robotic dexterity through multimodal learning techniques, ultimately bridging existing gaps in the understanding of human-like manipulation in robotics.
Hand Pose Estimation EMG Technology Multimodal Data Robotics Artificial Intelligence
Interview with Wang Zhongyuan: VLA will survive, but world models are the future.
In recent months, the concept of "World Model" has gained significant traction within the AI and robotics sectors, driven by underlying industry anxieties. As AI technology has rapidly evolved over the past two years, limitations in embodied intelligence have become apparent, revealing that while robots can recognize objects, they struggle to understand physical interactions and causal relationships. The World Model aims to bridge this gap by enabling robots to learn the laws of the physical world. At the forefront of this exploration is Wang Zhongyuan, the director of the Beijing Academy of Artificial Intelligence, who identifies four distinct paths in the development of World Models. These include language-centered models, pixel-centered models, 3D structure-centered models, and visual representation-centered models. The Beijing Academy is pioneering a fifth approach that integrates language and visual data into a unified latent space representation, allowing for more complex interactions and predictions. Wang emphasizes that the World Model's potential lies in its ability to enhance embodied intelligence, enabling robots to understand and predict physical interactions over time. He envisions a future where World Models serve as the foundational brain for robots, capable of complex reasoning and decision-making in real-world scenarios. However, he cautions that achieving this goal will require significant advancements in data collection and model training, with a timeline of three to five years anticipated for substantial progress. As the field continues to evolve, the competition will focus on the ability to create models that accurately reflect the complexities of the physical world.
NVIDIA and LG Group build AI factory to train robots and power future mobility
Researchers and engineers are advancing the next frontier of artificial intelligence, focusing on the development of machines capable of movement, visual perception, and autonomous decision-making. This initiative, which has gained momentum in recent months, aims to enhance the functionality and adaptability of AI systems across various sectors, including healthcare, transportation, and robotics. The push for these advancements is driven by the increasing demand for intelligent systems that can operate in dynamic environments and perform complex tasks without human intervention. By integrating advanced sensors and machine learning algorithms, developers are working to create AI that not only processes information but also interacts with the physical world in real-time. This evolution in AI technology is taking place in research laboratories and tech hubs around the globe, with significant contributions from universities, private companies, and government agencies. As these entities collaborate, they are exploring innovative applications that could revolutionize industries and improve everyday life. The ongoing research is expected to culminate in prototypes and pilot programs by early 2024, showcasing the potential of these intelligent machines. As the field progresses, ethical considerations and safety measures are also being prioritized to ensure responsible deployment and integration into society. The ultimate goal is to create AI systems that enhance human capabilities and contribute positively to various aspects of life.
Robots learn to anticipate chaos, but still fail to read a decidedly human signal
Researchers at Cornell University are exploring the integration of artificial intelligence into robotics to enhance social intelligence, enabling robots to interpret facial expressions, anticipate human needs, and interact effectively within societal contexts. In a recent study, the team evaluated vision language models (VLMs)—AI systems capable of processing and generating both visual and linguistic data. The research focused on assessing these models' ability to predict outcomes in tense scenarios depicted in short videos, such as a toddler precariously carrying an overflowing mug of coffee. This investigation aims to advance the development of robots that can better understand and respond to human emotions and behaviors, ultimately improving their functionality in everyday environments.
Robotics
Jumping spider’s layered retina drives design of low-power 3D camera for AR and robotics
A team of engineers has conducted an in-depth study of the vision capabilities of jumping spiders, leveraging this unique biological model to inspire innovative technological advancements. This research, which took place over several months, aims to enhance the design of visual systems in robotics and artificial intelligence. By examining the spiders' exceptional ability to perceive depth and motion, the engineers have developed new algorithms that could significantly improve the performance of machines in complex environments. The findings were presented at a recent conference focused on biomimicry and robotics, highlighting the potential for nature-inspired solutions to address modern technological challenges. This interdisciplinary approach not only showcases the intricate relationship between biology and engineering but also opens new avenues for creating smarter, more adaptive robotic systems.
Tsinghua PhD Team Secures Nearly $15 Million Seed Funding with Innovative Instinct-Driven Technology
Oak Fruit Robotics, a startup founded by a team of nine PhD graduates from Tsinghua University, has successfully secured nearly $15 million in seed funding. This funding will support the company's innovative approach to robotics, which they describe as 'instinct-driven' technology that seeks to challenge conventional visual-linguistic attention (VLA) methods. The company aims to enhance robotic capabilities specifically in flexible manufacturing environments by emphasizing the difference between operational and linguistic intelligence. This new funding round marks a significant step in their mission to revolutionize the industry.
Embodied Intelligence Robotics Flexible Manufacturing AI Technology
NVIDIA Launches Alpamayo 2 Super Open Reasoning Model for Robotaxis
NVIDIA has unveiled its latest advancement in artificial intelligence, the Alpamayo 2 Super, a sophisticated vision language action model featuring 32 billion parameters. This new model is part of the expanding Alpamayo family, which includes a range of open AI models, simulation frameworks, and physical AI datasets designed to enhance safety in level 4 autonomous systems. The announcement was made today, showcasing NVIDIA's commitment to pushing the boundaries of AI technology. The Alpamayo 2 Super aims to improve the capabilities of AI in understanding and interacting with complex visual and linguistic inputs, thereby facilitating more advanced applications in various industries. This development reflects NVIDIA's ongoing efforts to lead in the AI space by providing robust tools for researchers and developers.
The Secret Weapon Behind Humanoid Robots' Graceful Dance Officially Released
Chingmu Visual has recently unveiled Project Decode, a groundbreaking initiative in the realm of embodied intelligence. This project is designed to facilitate the collection of high-quality, structured real-world data, which is crucial for improving the functionality of humanoid robots. By addressing the challenges associated with data capture and usability, Project Decode aims to enhance the operational capabilities of these advanced machines. The launch represents a significant step forward in the integration of sophisticated data systems into robotics, potentially transforming how these technologies interact with their environments.
Embodied Intelligence Data Collection Humanoid Robots AI Training Motion Capture
Bees Inspire Navigation! This Small Flying Robot Uses a 42KB 'Brain' to Fly 600 Meters Home
Researchers at Delft University of Technology have unveiled Bee-Nav, an innovative navigation strategy for flying robots, drawing inspiration from the natural navigation abilities of bees. This lightweight system enables the robot to successfully return home after traveling a distance of 600 meters, utilizing a compact 42.3KB neural network. The breakthrough combines path integration with visual memory, enhancing the robot's capability for long-distance navigation. This development marks a significant advancement in robotics and artificial intelligence, potentially paving the way for more efficient autonomous navigation systems in various applications.
Flying Robots Navigation Technology AI Robotics Machine Learning
Turning surroundings into a 'virtual screen' could help machines see better in 3D
Researchers have unveiled new insights into how the human brain processes complex visual scenes, particularly in bustling urban environments. This study, conducted by a team of neuroscientists, highlights the brain's remarkable ability to create a three-dimensional representation of dynamic surroundings, such as busy city streets during rush hour. The findings were presented at a conference in October 2023, where experts gathered to discuss advancements in cognitive neuroscience. The motivation behind this research stems from the need to understand how our brains navigate and interpret the myriad of stimuli encountered in everyday life. By examining how the brain calculates distances and identifies objects of various shapes and sizes, the researchers aim to enhance our understanding of visual perception and its implications for fields such as robotics and artificial intelligence. The study utilized advanced imaging techniques to observe brain activity in real-time, revealing the intricate processes that occur as individuals engage with their environments. This groundbreaking work not only sheds light on human cognition but also opens avenues for developing technologies that mimic these processes, potentially improving navigation systems and enhancing user experiences in complex visual settings.
Robotics
Yuejiang and OptoReach Form Strategic Partnership to Accelerate the Application of 'One Brain, Multiple Bodies' Embodied Industrial Solutions
Yuejiang Technology and OptoReach have entered into a strategic cooperation agreement to advance integrated embodied industrial solutions. This partnership, announced recently, seeks to leverage advanced robotics and AI visual technologies to improve the application of embodied intelligence within the manufacturing sector. By combining their expertise, the two companies aim to innovate and enhance operational efficiencies in industrial processes, reflecting a growing trend towards automation and intelligent systems in manufacturing.
Industrial Robotics AI Visual Technology Embodied Intelligence Smart Manufacturing
Humanoid robot gets curved OLED display head with new tech to increase efficiency
LG has introduced an innovative curved OLED face display specifically designed for humanoid robots, showcasing the company's commitment to advancing robotic technology. The announcement was made during a recent technology expo in Seoul, where LG Display highlighted the display's potential to enhance human-robot interaction. This development aims to improve the emotional connection between robots and users, addressing the growing demand for more lifelike and engaging robotic companions. The display features advanced visual capabilities, allowing for expressive facial animations that can convey a range of emotions. By integrating this technology, LG seeks to position itself at the forefront of the robotics industry, responding to the increasing interest in automation and artificial intelligence. The new display is expected to play a significant role in various applications, from customer service robots to personal assistants, further bridging the gap between humans and machines.
From Demo to Deployment, Where Robotics Actually Fails
Recent advancements in robotic vision have highlighted a significant gap in achieving true autonomy in unstructured environments: the need for tactile intelligence. Experts emphasize that while robots can effectively process visual information, the ability to 'feel' pressure and tension is crucial for reliable object handling. This capability is essential for various applications, including agricultural harvesting and medical device operation. As the field progresses, researchers are focusing on integrating tactile sensors and feedback mechanisms to enhance robots' interaction with their surroundings, ultimately aiming to bridge this critical gap in robotic functionality.
South Korea's first AI film hits theaters. But is it watchable?
In a near-future setting where artificial intelligence is integrated into everyday life, an AI-driven robot police officer targets a child it predicts will become a criminal. This premise forms the basis of "I'm Popo," which is being promoted as the first South Korean feature film created entirely with AI-generated visuals. The film, directed by Kim Il-dong, a webtoon artist making his debut in feature filmmaking, showcases a narrative that intertwines technology and societal issues. The script was crafted by Kim, who also managed the AI prompts used to generate the film's visuals. While the film utilizes AI for its imagery, it features professional voice actors for character dialogues. The story unfolds as a grieving father challenges the algorithm's judgment in court, raising questions about the implications of predictive policing and the role of AI in shaping human destinies.
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Engineering Collisions: How NYU Is Remaking Health Research
New York University (NYU) is revolutionizing academic research through its newly established Institute for Engineering Health, which focuses on addressing disease states rather than adhering to traditional academic disciplines. This innovative approach encourages collaboration among experts in various fields, including immunology, engineering, and artificial intelligence, to tackle specific health challenges, such as allergic asthma. Under the leadership of Jeffrey Hubbell, NYU's vice president for bioengineering strategy, the institute has already seen promising outcomes, such as the development of a startup that creates devices for detecting airborne pathogens and navigation technology for visually impaired subway riders. Hubbell advocates for a shift from a conventional drug-inhibition model to one that promotes beneficial biological pathways, necessitating a new breed of researchers who possess interdisciplinary skills. To foster this environment, NYU is constructing a science and technology hub in Manhattan, designed to facilitate collaboration among diverse disciplines. This initiative aligns with the university's strategy of organizing around "grand challenges" rather than traditional academic silos, as emphasized by Juan de Pablo, the executive dean of the Tandon School of Engineering. The institute also emphasizes a proactive approach to translating research into practical applications, conducting "translational exercises" to map potential pathways from discovery to deployment. This comprehensive strategy aims to accelerate innovation in science and technology, positioning NYU as a leader in addressing complex health issues through collaborative, cross-disciplinary research.
Type-sponsored Nyu-tandon Health Clinical-trials Data-science Nyu
Mimic Robotics Open-Sources "mimic-video" Recipe to Accelerate Video-Action Models
Mimic Robotics, a company based in Zurich, has unveiled its innovative "pixel-to-action" architecture, which is designed to transform the current landscape of artificial intelligence by moving away from traditional static vision-language models. This release, which includes both the code and accompanying research, marks a significant shift towards utilizing dynamic video-based foundations. The initiative aims to enhance the capabilities of AI systems, enabling them to better interpret and respond to visual information in real-time. By sharing this technology, Mimic Robotics seeks to foster advancements in the field and encourage further exploration of video-based AI applications.
Mimic Robotics Europe open-source ETH Zurich
Boston Dynamics and Google DeepMind Teach Spot to Reason
Boston Dynamics has announced that its quadruped robot, Spot, is now equipped with Google DeepMind’s Gemini Robotics-ER 1.6, a high-level embodied reasoning model designed to enhance the robot's usability and intelligence for complex tasks. This development, revealed today, marks a significant advancement in the commercial deployment of legged robots, particularly in industrial inspections, where Spot will autonomously identify hazardous debris, read gauges, and utilize vision-language-action models for better environmental understanding. The collaboration aims to improve how robots interpret and interact with their surroundings, addressing the challenges of ensuring that robotic actions align with human reasoning. Marco da Silva, vice president of Spot at Boston Dynamics, emphasized that the new capabilities will allow Spot to autonomously navigate real-world challenges more effectively. Despite the progress, experts acknowledge ongoing challenges in achieving seamless human-robot interaction. Carolina Parada from Google DeepMind noted that while the Gemini model enhances visual recognition, it currently lacks integration with other sensory data, such as touch, which is crucial for reliable object manipulation. As part of the deployment, customers using Spot for inspections will need to share operational data with Boston Dynamics to further refine the technology. The introduction of Gemini Robotics-ER 1.6 is seen as a step toward creating safer and more reliable robots capable of performing everyday tasks, with the potential to apply these advancements to other robotic platforms in the future.
Boston-dynamics Spot-robot Google-deepmind Inspection-robots Quadruped-robots
These AI-powered guide dogs don't just lead, they talk
Researchers at Binghamton University, State University of New York, have developed an innovative talking robot guide dog system designed to assist visually impaired individuals. This groundbreaking technology utilizes large language models to not only determine the safest routes but also to provide real-time feedback to users as they navigate their surroundings. The system aims to enhance the independence and safety of those who rely on guide dogs, addressing the communication gap that exists between traditional guide dogs and their owners. By integrating advanced artificial intelligence, the researchers hope to revolutionize the way visually impaired individuals interact with their environment, making travel more accessible and secure.
RoboticsRobotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
