Helm.ai develops AI perception and path-planning software for ADAS and autonomous driving. Its stack leverages unsupervised and semi-supervised learning to enable scalable vision-based object detection, lane understanding, and sensor fusion without reliance on large-scale manual data labeling.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
On July 2, Microsoft released version 150.0.4078.48 of Microsoft Edge for desktop, introducing support for Google account sign-ins on both Windows and macOS. This update allows users to log in using either a Microsoft or Google account, enhancing accessibility for users. IT administrators can manage this feature through a new policy called 'NonMicrosoftAccountSignInEnabled'. The significance of this update lies in its potential to streamline user experience and broaden the browser's appeal. By allowing Google account integration, Microsoft Edge aims to attract users who prefer Google's ecosystem, thereby increasing its market share. Additionally, version 150 will be the last to support macOS 13 Monterey, as future updates will require macOS 12 Ventura or later. On July 9, OpenAI officially launched its new AI model series, GPT-5.6, following a limited preview. This series includes three tiers: Sol, Terra, and Luna, each optimized for different performance and cost metrics. The rollout of GPT-5.6 is expected to enhance capabilities in various applications, including coding and cybersecurity, with pricing structured to appeal to a wide range of users. No further timeline was disclosed at the time of publication.
Dexmal has introduced its DM0.5 foundation model, Apex universal robot, DexOS operating system, and MaaS platform, aiming to bridge the engineering gap between embodied AI models and practical productivity. This launch marks a significant step in the company's strategy to enhance the application of AI in real-world scenarios, with a focus on improving operational efficiency. The introduction of these products is crucial as they represent a comprehensive approach to integrating AI into various sectors. By addressing the final engineering challenges, Dexmal seeks to enable more seamless interactions between AI systems and physical environments, potentially transforming workflows across industries. The DM0.5 model is designed to optimize performance, while DexOS provides a robust operating framework for managing AI tasks. Looking ahead, Dexmal's three-stage strategy will be pivotal in determining the success of these innovations. The company has not disclosed specific timelines for the rollout of these products, but the focus on enhancing productivity through embodied AI suggests a proactive approach to market demands and technological advancements.
TechnologyWestlake Robotics completed a funding round exceeding 100 million yuan in June 2026, backed by Henan Investment Group's Huirong Fund. This marks the company's third financing round in five months, with total disclosed funding reaching several hundred million yuan. The funding is aimed at advancing their unique dual-pretraining technology, which combines a general brain and a humanoid small brain for improved robotic performance. The significance of this funding lies in Westlake Robotics' differentiated technical approach, utilizing a dual-pretraining model that integrates VLA and world model fusion. Their General Action Expert (GAE) model addresses common issues in humanoid robots, such as stiffness and imbalance, by enabling real-time interpretation of human motion intent. This capability allows a single operator to control multiple Westlake o1 robots simultaneously, reducing deployment and labor costs in applications like logistics inspection and data collection. Looking ahead, Westlake Robotics plans to use the latest funding to further develop their unified embodied large model and accelerate deployment with industrial clients. The company, founded by academic researchers from Westlake University, is positioned to leverage its strong academic background to bridge the gap between laboratory demonstrations and real-world applications. No further timeline was disclosed at the time of publication.
Robotics Embodied Intelligence Automation Logistics AIChinese AI company Robbyant has launched LingBot-Depth 2.0, a next-generation spatial perception model designed to enhance robotic navigation in complex environments. This model builds on the previous LingBot-Depth, utilizing the Masked Depth Modeling technique and trained on 150 million samples, achieving top results in 12 out of 16 depth completion benchmarks. Notably, it reduces depth error by over 50%, improving accuracy in challenging indoor settings. The significance of LingBot-Depth 2.0 lies in its ability to accurately perceive transparent and reflective surfaces, areas where traditional depth cameras often struggle. The model's advancements are attributed to LingBot-Vision, a visual foundation model that employs a unique “boundary structure” pre-training objective, enabling sub-pixel-level boundary localization. Despite being trained on a smaller dataset of 160 million images, it demonstrates robust performance across various robotic vision applications, enhancing object boundary detection and tracking. Looking ahead, Robbyant's collaboration with Orbbec aims to integrate LingBot-Depth 2.0 into new hardware solutions for robotics data collection. The RGB-D EGO device, part of Orbbec’s Robot-Free Data Collection Hardware Platform, will feature a customized version of the model. Future updates are expected to further enhance depth completion and spatial structure understanding, providing a solid foundation for training embodied AI systems in real-world scenarios. No further timeline was disclosed at the time of publication.
AI and RoboticsSoftServe has highlighted the importance of 'virtual gyms' for robotics teams, emphasizing their role in preparing robots for dynamic environments. These high-fidelity simulation environments allow robots to train, fail, and recover safely before real-world deployment, addressing the challenges posed by unpredictable operational conditions. The global robotics market is projected to grow at a 19.6% CAGR from 2026 to 2036, underscoring the need for effective training solutions like virtual gyms to enhance robotic autonomy and performance. The shift from programmed automation to physical AI necessitates that robots adapt to constantly changing environments, which traditional training methods struggle to accommodate. Virtual gyms integrate technologies such as digital twins, reinforcement learning, and sensor modeling to provide a comprehensive training platform. This approach mitigates the risks and costs associated with real-world trials, enabling teams to generate valuable training data in a controlled setting, thus improving deployment success rates. Looking ahead, the adoption of virtual gyms is expected to become a standard practice in robotics development, as they offer a solution to the simulation-to-reality gap. No further timeline was disclosed at the time of publication, but the increasing complexity of robotic tasks suggests that the demand for such training environments will continue to rise as the industry evolves.
Artificial Intelligence Artificial Intelligence / Cognition Autonomous Mobile Robots (AMRs) Development Tools / SDKs / Libraries Industrial Robots LogisticsResearchers from MIT and EPFL have created a flapping robot capable of transitioning between water and air without legs. Weighing approximately 250 grams, the robot features a streamlined body, two flexible wings, and a controllable tail. It can flap its wings at frequencies of up to 6 Hz underwater and 5.2 to 11 Hz in the air, mimicking the behavior of diving birds, as detailed in a recent Science publication. This innovation is significant as it addresses the complex physical challenges of transitioning from water to air, a feat that most diving birds achieve with the aid of their legs. The robot's flexible wings reduce drag and allow for a higher flapping frequency underwater compared to rigid wings. This design not only enhances its swimming efficiency but also aligns with biological observations of diving birds, providing insights into their locomotion strategies. Looking ahead, the research team is exploring optimal wing configurations and has tested various sizes and stiffnesses. Future experiments will focus on the robot's ability to transition from water to air solely through wing flapping, a critical milestone that could reveal more about the mechanics of avian flight and inspire advancements in robotic design. No further timeline was disclosed at the time of publication.
Flapping Robots Aerial Robotics Aquatic Robotics Bio-inspired EngineeringByteDance has conducted extensive testing of its Seedream 5.0 Pro, focusing on three key areas: realism, complex visualization, and design. The results indicate notable improvements in generating infographics and creating user interface mockups, showcasing the platform's enhanced capabilities in these domains. The advancements in Seedream 5.0 Pro are significant for professionals in design and data visualization, as the tool now offers more sophisticated features that streamline the creation of visual content. This improvement can lead to increased efficiency and creativity in producing high-quality graphics and mockups, which are essential in various industries. Looking ahead, it will be important to monitor how ByteDance continues to develop Seedream 5.0 Pro and whether further enhancements will be introduced. No further timeline was disclosed at the time of publication.
AIIn July 2026, a humanoid robot successfully performed the world's first live gallbladder surgery on a pig under the control of a surgeon. This groundbreaking procedure, documented by Nature and featured on the front page of the New York Post, has sparked significant discussions in the tech community about the implications of humanoid robots in surgical settings, particularly regarding remote control and AI capabilities. The significance of this achievement lies in its potential to disrupt the surgical robotics market, which has been dominated by the Da Vinci surgical system for nearly two decades. The Da Vinci system, known for its high costs exceeding $2 million, relies on specialized robotic arms and instruments. In contrast, the humanoid robot's design allows it to utilize standard surgical tools, which could lead to reduced costs and increased accessibility for hospitals. Looking ahead, the successful completion of this surgery marks a pivotal moment for humanoid robots in healthcare. While regulatory hurdles and clinical validation processes remain, the experiment demonstrates that humanoid robots can perform complex surgical tasks. The next challenge will be determining when the costs associated with these robots can be lowered enough for broader adoption by hospitals beyond top-tier institutions. No further timeline was disclosed at the time of publication.
Humanoid Robots Surgical Robotics AI in Healthcare Remote SurgeryOn July 10, Ant Group introduced LingBot-VA 2.0, the first embodied native action model in the industry. This release marks the culmination of their full-stack 2.0 model series, featuring advancements in spatial perception and real-time interaction. The launch has generated significant buzz across international platforms like Reddit and Hugging Face, indicating a strong interest in their technology. The significance of LingBot-VA 2.0 lies in its comprehensive technology stack, which includes LingBot-Depth 2.0 and LingBot-Vision. LingBot-Depth 2.0 enhances depth perception with a training dataset expanded from 3 million to 150 million, achieving top scores in 12 out of 16 benchmarks. Meanwhile, LingBot-Vision introduces a novel pre-training target, improving depth estimation accuracy despite using a smaller dataset compared to competitors. Looking ahead, the next steps for Ant Group involve further collaboration with industry partners, as LingBot-Depth 2.0 has already received professional certification from Orbbec. The company is also focusing on integrating their models into the industry, with no further timeline disclosed at the time of publication for upcoming releases or partnerships.
Robotics AI Machine Learning Computer VisionIn a recent episode of The Robot Report Podcast, Andy Lonsberry, co-founder and CEO of Path Robotics, detailed the company's innovative approach to robotic welding. Based in Columbus, Ohio, Path Robotics utilizes AI to optimize the welding process by identifying torch paths and employing real-time vision guidance. This technology aims to streamline operations in manufacturing environments, addressing longstanding challenges in the industry. The significance of Path Robotics' advancements lies in their application of physical AI to enhance robotic systems. By integrating AI-driven solutions, the company is not only improving the efficiency of welding operations but also expanding the capabilities of robots in complex production settings. The deployment of Boston Dynamics' Spot robots for mobile welding applications in shipbuilding further exemplifies the potential of combining AI with robotics to tackle industry-specific challenges. Looking ahead, the focus will be on the continued integration of AI in robotic systems and the potential for further advancements in welding technology. No further timeline was disclosed at the time of publication, but the ongoing development in this area suggests a promising future for AI-enhanced manufacturing solutions.
Artificial Intelligence Assembly Cameras / Imaging / Vision Controllers Humanoids ManufacturingUnitree wins CSRC approval for China’s first humanoid IPO, Korea unveils ₩312T AI investment, RoboCup 2026 opens in Incheon, and Paris launches Europe’s inaugural Physical AI summit.
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