Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
LaST-R1: New Physical Reasoning Paradigm Achieves 99.9% Success Rate on LIBERO Benchmark
A collaborative research effort involving Simplexity Robotics, Peking University, and the Chinese University of Hong Kong (CUHK) has introduced LaST-R1, an innovative embodied AI paradigm. This new technology has demonstrated a remarkable 99.9% success rate on the LIBERO benchmark, surpassing the previous benchmark, π0.5, by 22.5% in real-world applications. The research highlights significant advancements in the field of artificial intelligence, showcasing the potential for enhanced performance in practical tasks. The findings were released in October 2023, marking a notable achievement in the ongoing development of AI systems.
AI
From 'Guessing' to 'Calculating': China's First Manifold Topology-Preserving Robot World Model Released
In Chengdu, China, researchers have unveiled an innovative robot world model that significantly improves robots' ability to comprehend and anticipate physical environments. This advanced model utilizes manifold topology preservation, which enhances the spatial intuition and physical reasoning of robots. As a result, these machines can make safer and quicker decisions in dynamic situations. The development marks a significant step forward in robotics, potentially transforming how robots interact with their surroundings and respond to changing conditions.
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CVPR 2026 Showcases How AI Is Powering the Next Era of Robotics Innovation
The 2026 Conference on Computer Vision and Pattern Recognition (CVPR) is set to take place from June 3 to June 7 at the Colorado Convention Center in Denver, Colorado. This premier event, co-sponsored by the IEEE Computer Society and the Computer Vision Foundation, will showcase groundbreaking advancements in artificial intelligence (AI) and robotics, highlighting how these technologies are transforming real-world applications. With a focus on embodied AI, multi-modal AI, and robotic perception, CVPR 2026 will feature workshops, technical paper presentations, and competitions, including the ManipArena Competition, which challenges participants to demonstrate physical reasoning and decision-making in real-world tasks. The conference aims to illustrate the rapid innovation in robotics and automation, with over 75% of the expo dedicated to leading AI and robotics companies that have collectively invested heavily in the field. As the global robotics market is projected to reach $124.37 billion this year, industry leaders will gather to discuss the implications of AI advancements on productivity and human-machine interaction. Grace A. Lewis, President of IEEE CS, emphasized the conference's role in bringing AI's potential to life, showcasing how these technologies are poised to reshape various industries. Media registration for the event is currently open, inviting participants to explore the future of intelligent machines.
Predicting the World Without Future Frames: BeingBeyond Launches Next-Generation Embodied Intelligence Model Being-H0.7
BeingBeyond has introduced its latest innovation, the Being-H0.7 embodied intelligence model, which revolutionizes the approach to video generation. This new model distinguishes itself by eliminating the need for traditional rendering of future frames, allowing for accurate physical reasoning and dynamic predictions. As a result, Being-H0.7 not only cuts down on training expenses but also ensures a high inference speed. This advancement marks a significant step forward in the field of artificial intelligence, promising enhanced efficiency and effectiveness in various applications.
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Japan's Leaders in Robotics and Manufacturing Leverage NVIDIA Cosmos for Physical AI Advancements
NVIDIA has announced that Japan's leaders in physical AI are utilizing the NVIDIA Cosmos™, Isaac™, Metropolis, and Jetson™ platforms to enhance the deployment of intelligent machines across various sectors including manufacturing and robotics. The introduction of Cosmos 3 Edge aims to provide advanced capabilities for real-time reasoning and action prediction in robots, marking a significant step in integrating intelligence into physical systems. This initiative is crucial as Japan's established strengths in robotics and manufacturing position it to lead in the next wave of AI development. Jensen Huang, NVIDIA's CEO, emphasized the unique opportunity for Japan to reinvent modern manufacturing through intelligent technologies, combining its heritage in precision engineering with NVIDIA's advanced platforms. Looking ahead, NVIDIA is expanding the Cosmos Coalition to include Japan's physical AI leaders, enabling collaboration on open world models. This coalition will facilitate the testing and optimization of physical AI systems, potentially transforming operations across various industries such as logistics, healthcare, and construction. No further timeline was disclosed at the time of publication.
Peking University Team Proposes LaST-R1 Framework, Enabling Robots to 'Think and Act' Simultaneously!
Researchers from Peking University and the Chinese University of Hong Kong have unveiled the LaST-R1 framework, a groundbreaking integration of latent reasoning into reinforcement learning. This development, announced recently, aims to enhance the decision-making capabilities of robots by enabling them to not only execute actions but also comprehend and adapt to various physical states. The framework is designed to improve robots' performance in real-world scenarios, addressing the limitations of traditional reinforcement learning methods. By incorporating latent reasoning, the LaST-R1 framework represents a significant advancement in the field of robotics, potentially leading to more intelligent and responsive machines.
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Robots are closing in on human-like judgments, addressing a key challenge in physical AI
Researchers at KAIST have made significant strides in advancing the commercialization of physical AI by creating a groundbreaking technology that allows artificial intelligence to autonomously learn human judgment criteria from a limited number of videos. This development, which emerged from ongoing efforts to enhance AI's adaptability and decision-making capabilities, represents a crucial step toward integrating AI more effectively into real-world applications. The innovation was unveiled recently, highlighting the potential for AI systems to better understand and replicate human-like reasoning in various contexts. By streamlining the learning process, this technology could pave the way for more intuitive and responsive AI solutions across multiple industries, ultimately enhancing user interaction and satisfaction.
Robotics
How Physical AI Is Closing the Gap Between Simulation and the Shop Floor
A new generation of systems is emerging that not only simulates the physical world but also engages in real-time reasoning and actions. This advancement is driven by a sophisticated spatial computing stack that integrates foundation models, AI-generated software, and high-fidelity 3D sensing technologies. These systems aim to enhance interactions with the environment, providing more intuitive and responsive experiences. The development is part of a broader trend in technology aimed at creating smarter, more adaptive solutions across various industries, including gaming, robotics, and virtual reality. As these innovations continue to evolve, they promise to transform how users interact with digital and physical spaces, paving the way for more immersive and effective applications.
NVIDIA Launches Cosmos 3, the Open Frontier Foundation Model for Physical AI
NVIDIA has unveiled its latest innovation, the NVIDIA Cosmos™ 3, a groundbreaking open world foundation model designed for physical AI. This advanced system integrates a mixture-of-transformers architecture that seamlessly combines vision reasoning, world generation, and action prediction into one cohesive platform. The launch, which took place today, marks a significant step forward in the development of artificial intelligence, aiming to enhance the capabilities of AI in understanding and interacting with the physical world. By leveraging this sophisticated technology, NVIDIA seeks to push the boundaries of AI applications across various industries, paving the way for more intelligent and responsive systems.
NVIDIA Expands Open Model Families to Power the Next Wave of Agentic, Physical and Healthcare AI
NVIDIA has unveiled an expansion of its open model families aimed at advancing artificial intelligence in physical and healthcare applications. This announcement, made today, highlights the introduction of new models designed to empower developers and scientists to create intelligent systems capable of reasoning and taking action in complex environments. The initiative reflects NVIDIA's commitment to driving innovation in AI technology, enabling more sophisticated and responsive solutions in various sectors. By providing these advanced tools, the company aims to facilitate the development of AI systems that can effectively address real-world challenges.
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.
Genesis AI launches first general-purpose humanoid robot
Genesis AI, a global leader in robotics, has introduced Eno, its inaugural general-purpose robot. Launched recently, Eno is characterized by its minimalist design, which sets it apart from conventional robotic forms. Powered by GENE, the company's advanced foundation model, Eno is designed to function as a true physical agent, capable of reasoning and performing tasks autonomously. This innovation aims to redefine the capabilities of robots in various applications, reflecting Genesis AI's commitment to pushing the boundaries of technology in the robotics sector.
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Interview with Workr Robotics CEO Ken Macken: ‘Paying for automation by the hour’
Industrial robotics is undergoing a significant transformation, driven by advancements in artificial intelligence, large language models, and embodied AI. This evolution has generated renewed interest in the development of robots capable of understanding, reasoning, and interacting with their physical environments. Notable partnerships, including collaborations between Google DeepMind and Boston Dynamics, have intensified discussions surrounding the potential for more sophisticated general-purpose robots. As these technologies continue to evolve, the industry anticipates a future where robots can perform a wider array of tasks, enhancing their utility across various sectors. The ongoing innovations suggest a promising trajectory for the integration of robotics into everyday life, potentially reshaping industries and improving operational efficiencies.
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Robots Face Challenges in Basic Tasks Despite Advances in Embodied Intelligence
Over the past year, the robotics industry has engaged in a competitive race focused on enhancing the computational power, parameters, and algorithms of robotic 'brains.' While advancements in reasoning capabilities are evident, robots still struggle with basic tasks such as grasping objects or performing precise manipulations. This discrepancy raises questions about the effectiveness of current sensory technologies. The core issue lies in the limitations of robotic perception, which relies heavily on either pure vision or multi-sensor fusion approaches. Multi-sensor fusion, favored by many embodied intelligence manufacturers, combines various sensors to improve robustness and accuracy. However, this method introduces challenges related to data synchronization and processing overhead, hindering the scalability of embodied intelligence. Conversely, pure vision systems, exemplified by Tesla's approach, depend on 2D RGB cameras to reconstruct 3D environments. This method lacks depth information and can falter in challenging visual conditions. Both approaches suffer from the loss of information during data transmission and processing, resulting in robots receiving 'second-hand data' rather than real-time, unified information from the physical world. No further timeline was disclosed at the time of publication.
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General Intuition Achieves $2.3 Billion Valuation with Innovative Robot Training Approach
General Intuition, a New York-based company, has proposed a groundbreaking approach to training robots using millions of hours of gaming footage instead of vast amounts of real-world data. In June 2026, the company completed a $320 million Series A funding round, achieving a valuation of $2.3 billion, led by renowned investor Vinod Khosla. The significance of General Intuition's method lies in its potential to revolutionize how robots learn spatial reasoning and physical intuition. By utilizing gaming data, the company claims to have pre-trained a spatial reasoning model that allows quadruped robots to navigate unfamiliar environments with minimal real-world data, challenging traditional training methods that rely heavily on real-world scenarios. Looking ahead, the success of General Intuition will depend on its ability to validate its technology in diverse real-world environments beyond office settings. The company's vision of creating a 'robot brain' for universal physical AI could redefine the operational frameworks for future robotics, potentially surpassing existing systems like Windows and Android in impact.
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X Square Robot Develops Integrated Stack for General-Purpose Robotics
X Square Robot, a Chinese company focused on embodied AI, is pioneering an integrated stack for general-purpose robots. This stack combines data learning, a world model for predicting physical changes, and an action model that integrates perception, planning, reasoning, and decision-making. The company emphasizes the importance of quality interaction data over sheer quantity, utilizing its Universal Manipulation Interface (UMI) to enhance data collection. The significance of X Square Robot's approach lies in its potential to unify various aspects of robotic intelligence, addressing the fragmented nature of current systems. By prioritizing interaction quality and establishing a closed inspection loop for data validation, the company aims to create a more effective learning environment for robots. This method not only reduces costs but also enhances the reliability of the training data, which is crucial for developing general-purpose robots capable of performing diverse tasks. Looking ahead, X Square Robot's WALL-WM world model represents a shift towards event-based action prediction, allowing for more coherent and context-aware robotic behavior. As the company continues to refine its models and data collection methods, the broader robotics community will be watching for independent validation of its results and the potential implications for the future of general-purpose robotics.
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AI² Robotics Secures $735 Million Funding for Wheeled Humanoid Robots Development
AI² Robotics has successfully raised approximately $735 million in a recent funding round, elevating its valuation to around $2.8 billion. The Shenzhen-based company specializes in wheeled humanoid robots, which feature a humanoid torso and five-fingered hands, offering a unique alternative to traditional bipedal systems. This funding round attracted a diverse group of investors, including government-backed entities and major corporations, highlighting the growing importance of physical AI technology in China. The strategic choice to develop wheeled robots instead of bipedal models allows AI² Robotics to focus on mechanical simplicity and durability, making their robots more cost-effective and easier to deploy in public spaces. With over 34 degrees of freedom and a custom lifting mechanism, the robots are designed for various industrial applications, including logistics, manufacturing, and retail. The company’s proprietary Alpha Brain software enhances the robots' capabilities in real-time spatial reasoning and task planning, positioning them as practical solutions in structured environments. Looking ahead, AI² Robotics aims to further penetrate industrial markets while steering clear of the consumer robotics hype. The company is actively deploying its AlphaBot 2 in practical settings, emphasizing its utility in sectors such as biotech and public service. No further timeline was disclosed at the time of publication regarding future funding or product releases.
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Three Key Challenges Hindering the Development of Advanced Humanoid Robots
The development of humanoid robots, akin to C-3PO, faces significant challenges in reliability, dexterity, and data management. While advancements in AI have improved reasoning capabilities, the physical aspects of robotics remain problematic. Current robots excel in specific tasks but struggle with complex manipulations that require high precision and reliability. These challenges are critical as they impact the deployment of robots in various sectors, including healthcare and manufacturing. For instance, surgical robots like the da Vinci system demonstrate the gap between theoretical intelligence and practical application, where reliability is paramount. The need for robots to perform consistently across millions of cycles is essential for their acceptance in sensitive environments. Looking ahead, the industry must focus on overcoming these bottlenecks to enable broader adoption of humanoid robots. The reliance on a combination of real and synthetic data for training highlights the ongoing need for innovative solutions. No further timeline was disclosed at the time of publication.
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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.
LiberAI: Redefining World Models in AI
LiberAI, a company founded by Tsinghua University alumnus Liu Songming, is making strides in artificial intelligence by developing an innovative physical world model. This initiative aims to enhance AI's predictive capabilities and decision-making processes by fostering a deeper understanding of the physical environment, rather than relying solely on imitation. Recently, LiberAI has attracted significant investment from leading investors, which will support its mission to advance AI's ability to engage in causal reasoning. The company's efforts are positioned to transform how AI interacts with the world, marking a pivotal shift in the technology's evolution.
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Perceptron Mk1 shocks with highly performant video analysis AI model 80-90% cheaper than Anthropic, OpenAI & Google
Perceptron Inc., a Bellevue-based startup founded by former Meta researchers Armen Aghajanyan and Akshat Shrivastava, has launched its flagship video analysis model, Mk1, aimed at revolutionizing how enterprises utilize AI in real-time video processing. Announced today, this innovative model is priced significantly lower than competitors, at $0.15 per million input tokens and $1.50 per million output tokens, making it accessible for large-scale industrial applications. The Mk1 model, developed over 16 months, excels in understanding complex physical interactions and temporal reasoning, outperforming established models like OpenAI's GPT-5 and Google's Gemini 3.1 Pro in various benchmarks. Its unique architecture allows it to process video streams continuously, maintaining object identity and providing precise analysis of dynamic scenes, which is particularly beneficial for sectors such as security, robotics, and marketing. Perceptron aims to position Mk1 as a leader in the "Efficiency Frontier," balancing high performance with cost-effectiveness. The model's capabilities extend to auto-clipping highlights from live sports and enhancing quality control in manufacturing. A public demo site is available for potential users to explore its functionalities. This launch signifies a significant step towards integrating advanced AI into real-world applications, as the company seeks to make "physical AI" as prevalent as its digital counterpart.
Technology
JAKA Robotics nhận được nguồn vốn mới từ các ông lớn trong ngành sản xuất.
JAKA Robotics, a leading player in industrial automation, has successfully completed a new funding round aimed at accelerating the development of its general-purpose intelligent robots. The investment, which involves a Shanghai-based industrial investment fund and global leaders in electronics and automotive manufacturing, will enhance JAKA's research and development efforts in perceptual intelligence, improving the robots' capabilities in sensing, reasoning, and interacting with the physical world. Founded in 2014, JAKA has deployed tens of thousands of robots in nearly 100 countries, earning the trust of over 1,500 industry leaders, including major companies like Toyota, Ford, Schneider Electric, and Flex. In response to the growing demands of the industry, JAKA has strategically repositioned itself for 2025, focusing on general-purpose intelligent robots, which include collaborative robots and integrated intelligent solutions. The company’s collaborative robots, weighing between 1 and 40 kg, continue to evolve, while its intelligent integrated products—such as JAKA Kargo, Khan, Lumi, K1, and S³—have achieved industrial-scale certification in logistics, inspection, and precision assembly. By enhancing cognitive and reasoning abilities, JAKA is transforming robots from task-specific tools into reliable partners capable of adapting to complex environments, making real-time decisions, and collaborating with humans to achieve shared goals. This latest support underscores JAKA's market leadership and the long-term potential of general-purpose intelligent robots as the company transitions perceptual intelligence from the lab to practical applications in manufacturing and services.
JAKA Robotics Secures New Funding Backed by Manufacturing Giants
JAKA Robotics, a leader in industrial automation, has successfully secured a new round of equity funding aimed at enhancing the development of general intelligent robots. The funding, which includes contributions from a Shanghai-based industrial fund and prominent global electronics and automotive manufacturers, will support research and development focused on embodied intelligence, enabling robots to improve their capabilities in perception, reasoning, and interaction with the physical environment. Founded in 2014, JAKA has deployed tens of thousands of robots in nearly 100 countries, serving over 1,500 industry leaders such as Toyota, Ford, and Schneider Electric. In response to evolving industry demands, the company shifted its strategic focus in 2025 towards general intelligent robots, expanding its product offerings to include collaborative robots and advanced embodied intelligence solutions. JAKA's products, including the JAKA Kargo, Khan, Lumi, K1, and S³, have already demonstrated industrial-scale effectiveness in logistics, inspection, and precision assembly. By enhancing robots' perception and reasoning abilities, JAKA aims to transform them from mere task-specific tools into adaptable partners capable of making real-time decisions and collaborating with humans in complex environments. This recent funding round highlights JAKA's leadership in the market and the significant potential of general intelligent robots as the company seeks to transition embodied intelligence from research and development into practical applications in production and service sectors.
Gill Pratt Says Humanoid Robots’ Moment Is Finally Here
In 2012, the U.S. Defense Advanced Research Projects Agency (DARPA) launched the DARPA Robotics Challenge (DRC), a multimillion-dollar competition aimed at advancing disaster robotics. Gill Pratt, the architect of the DRC and now CEO of the Toyota Research Institute (TRI), envisioned the challenge as a catalyst for significant progress in robotics, similar to earlier DARPA initiatives that revolutionized driverless cars. A decade later, Pratt believes humanoid robots are on the brink of a transformative breakthrough, largely due to advancements in artificial intelligence (AI). Pratt notes that while the physical capabilities of humanoid robots have improved, the real change lies in their cognitive abilities. Recent AI developments allow robots to learn tasks through demonstration rather than programming, although data availability remains a challenge. He emphasizes the need for robots to develop deeper reasoning capabilities, beyond mere pattern recognition, to navigate complex real-world scenarios effectively. At TRI, Pratt's team is focusing on "care-receiving robots" to address societal issues like aging and loneliness. He highlights the importance of using robotics to enhance quality of life, particularly for the elderly. However, he cautions against the current hype surrounding humanoid robotics, warning that many advancements are still reliant on basic pattern-matching techniques. Pratt advocates for a balanced perspective to avoid potential disillusionment in the field, drawing parallels to the earlier challenges faced in automated driving.
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Google DeepMind Gives Robots a 'Thinking' Brain with Agentic Gemini 1.5 Models
Google DeepMind has introduced Gemini Robotics 1.5, an advanced AI framework aimed at enhancing the capabilities of robots. This new system allows robots to evolve from merely following commands to becoming 'physical agents' capable of reasoning, planning, and acquiring skills across various hardware platforms, including Apptronik's Apollo humanoid robot. The announcement marks a significant step in the development of intelligent robotics, reflecting the company's commitment to pushing the boundaries of artificial intelligence. By enabling robots to learn and adapt, DeepMind seeks to revolutionize the way machines interact with their environments and perform complex tasks. The unveiling of this framework comes as part of a broader trend in the tech industry to create more autonomous and versatile robotic systems.
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Why this CEO thinks video games make better training data than the internet
Recent discussions in the field of artificial intelligence have highlighted the limitations of large language models, such as ChatGPT and Claude, in achieving artificial general intelligence (AGI). While these models excel in text generation, they struggle with understanding the dynamics of movement through space and time, a critical component for developing generalized intelligence. To address this gap, researchers are exploring the potential of gaming data as a solution. This innovative approach, known as General Intuition, aims to leverage the rich, interactive environments found in video games to enhance AI's understanding of real-world physics and dynamics. By integrating insights from gaming, experts believe they can create more sophisticated models capable of reasoning and adapting in complex scenarios. The exploration of this method is ongoing, with the hope of advancing the field of AGI significantly.
AI Startups AI Funding general intuition physical ai Pim DeWitRobotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
