Core Insights - GSI Technology announced preliminary benchmark results for its Gemini-II Compute-in-Memory processor, achieving a time-to-first-token (TTFT) of 3 seconds for multimodal large language models at the edge, with a power consumption of approximately 30 watts [1][2]. Performance Metrics - The Gemini-II processor demonstrated a TTFT of 3 seconds, which is the lowest reported for a multimodal 12B model on an embedded edge processor [2]. - Competitive platforms reported TTFTs of approximately 12 seconds on Qualcomm Snapdragon X Elite at 30W and 3 seconds on NVIDIA Jetson Thor at over 100W, indicating that Gemini-II offers superior performance at lower power levels [3]. Market Implications - The performance profile of Gemini-II is well-suited for "physical AI" markets, including drones and smart city applications, where power and thermal constraints are critical [4]. - The shift from cloud-assisted models to local inference in edge physical AI is expected to enhance latency, reliability, and operational efficiency [5]. Development and Collaboration - GSI's engineering team is focused on optimizing the responsiveness of the Gemini-II processor while collaborating with partners like G2 Tech for system integration and proof-of-concept activities [6].

Core Insights - Manifold AI has completed over 100 million yuan in angel+ round financing, with Jinqiu Capital continuing to invest. The funding will be used for the iteration of its world model and the application of embodied intelligence [4] - The company has developed a universal spatial world model called WorldScape, which matches the quality and real-time capabilities of leading global models [6] - Manifold AI is the first team globally to deploy a comprehensive outdoor, indoor, and aerial embodied world model, significantly enhancing data efficiency and model performance [9] Financing and Investment - The latest funding round was led by Junlian Capital, with participation from Meihua Venture Capital, Huawei Hubble, and existing investors including Inno Fund and Jinqiu Capital [4] - Manifold AI has raised several hundred million yuan in total funding over the past six months [4] Technological Advancements - WorldScape enables single-image generation of interactive spaces, providing a foundation for physical AI applications [8] - The company utilizes a vast amount of physical video data for pre-training, enhancing WorldScape's operational interaction capabilities [8] - Manifold AI's approach replaces traditional VLM models with its world model, resulting in superior performance in real-world applications [10] Future Prospects - The integration of NVIDIA Jetson Thor for deploying embodied world models is a significant step towards scaling operations [14] - The involvement of Huawei Hubble is expected to facilitate the integration of domestic chips and robotic brains, laying the groundwork for large-scale implementation [14]

Group 1 - The core product of the company, the Gemini330 series 3D camera, has been successfully adapted to the NVIDIA Jetson Thor platform, enhancing the capabilities of robotic manufacturers by enabling high-speed processing and flexible integration options [1][2] - The collaboration between the Gemini series and the Jetson Thor platform provides a complete visual computing solution for embodied intelligence applications, accelerating innovation in humanoid robots and advanced autonomous mobile robots (AMR) [2] - The company has established a dual manufacturing system in Shunde, China, and Vietnam, which supports global clients with integrated R&D and manufacturing capabilities [3][5] Group 2 - The Shunde manufacturing base has the capacity for millions of sensors and hundreds of thousands of robotic terminals, while the Vietnam factory is expected to commence production in May 2026, enhancing global delivery efficiency and supply chain resilience [5] - The company has successfully provided manufacturing services for leading global clients in various sectors, including rehabilitation robots, smart lawn mowers, humanoid robots, and warehouse and cleaning robots, helping to reduce overall costs and shorten time-to-market [5]

当地时间1月5日，2026国际消费电子展（CES）拉斯维加斯展会现场，英伟达创始人兼CEO黄仁勋发表 主题演讲，抛出重磅行业判断：物理人工智能（Physical AI）的"ChatGPT时刻"已经到来。AI技术将正 式从虚拟屏幕走向物理世界，机器人产业迎来规模化变革的关键节点。 开源生态的协同扩张成为本次发布的核心亮点。英伟达与Hugging Face达成深度合作，将GR00T系列模 型及Isaac Lab-Arena框架整合至LeRobot开源机器人库，实现200万英伟达机器人开发者与1300万 Hugging Face AI构建者的生态联通。双方适配的Hugging Face Reachy 2人形机器人可与NVIDIA Jetson Thor硬件无缝协作，桌面机器人Reachy Mini则支持与NVIDIA DGX Spark联动，开发者可直接调用相关 模型开展端到端开发。据悉，英伟达2025年已在Hugging Face贡献650个开源模型和250个数据集，相关 资源下载量在开源社区遥遥领先。 现场，黄仁勋表示，发布了多款机器人"大脑"的开源基础模型。同时宣布，包括波士顿动力、 Caterpillar、 ...

Already FDA-cleared and in routine clinical use in Las Vegas, the Dynamis Robotic Surgical System is set for its next evolution, leveraging NVIDIA Jetson Thor, NVIDIA Isaac for Healthcare, and NVIDIA Cosmos platforms to define the future of hard tissue robotic surgery. LAS VEGAS, NV and BERN, SWITZERLAND / ACCESS Newswire / January 5, 2026 / LEM Surgical, a leader in next-generation hard tissue robotics, today announced its participation in the 2026 Consumer Electronics Show (CES). ...

Core Insights - Richtech Robotics has launched Dex, its first mobile humanoid robot designed for industrial applications, in collaboration with NVIDIA to enhance its capabilities [1][3] - Dex utilizes NVIDIA Jetson Thor technology for real-time reasoning and complex task execution, operating efficiently for a full workday on a single charge [2][5] - The robot combines insights from over 450 previous deployments, integrating autonomous mobile robot (AMR) technology with dual-armed precision to enhance operational efficiency [4][5] Technology and Development - Richtech employs NVIDIA's Isaac Sim for training Dex in diverse industrial contexts, facilitating a "Sim2Real" pipeline that accelerates deployment and improves safety [3][6] - The robot's design prioritizes mobility and dexterity, featuring a wheeled platform for stability and lower energy costs, while maintaining a four-hour battery life in mobile mode [4][5] - Richtech is launching an American robotics data initiative to collect regionally grounded data, aiming to empower the development of physical AI in the U.S. [7] Applications and Capabilities - Dex is capable of performing a variety of light to medium industrial tasks, making it a valuable asset in manufacturing and logistics sectors [8][9] - The robot's features include modular end-effectors for various tools, a four-camera vision system for navigation, and the ability to operate continuously from a static base [5][6] - Richtech invites companies to explore pilot opportunities with Dex, showcasing its capabilities at industry events [10][9] Company Overview - Richtech Robotics focuses on developing advanced robotic solutions and data infrastructure, emphasizing automation and continuous AI-driven improvement across various sectors [11]

Core Insights - Advantech has launched a new lineup of Edge AI solutions powered by NVIDIA Jetson Thor modules, setting a new benchmark for edge AI performance with up to 2070 FP4 TFLOPS [1] - The solutions are designed for real-world applications in robotics, medical AI, and data AI, featuring integrated hardware-software platforms and application-specific tools [1][3] Group 1: Edge AI Solutions - The new Edge AI solutions include robotic controllers for humanoid robots, AMRs, and unmanned vehicles, providing real-time AI reasoning and inference with GPU-accelerated SLAM [2] - Advantech's robotic controllers support multi-camera GMSL, 2D/3D sensors, and IMUs, enabling rapid integration and deployment with features like hardware time sync and anti-vibration design [2] Group 2: Medical AI Systems - Advantech's medical AI systems leverage NVIDIA Jetson Thor and advanced SDKs to enhance real-time sensor processing and image analysis for surgical robotics and diagnostics [3] - The platforms aim for low latency and high precision, making them suitable for operating rooms and clinical workflows [3] Group 3: Data AI Systems - The AIR-075 system is designed for data AI applications, featuring powerful computing capabilities with 4× 10GbE and GMSL interfaces [4] - It integrates with NVIDIA AI technologies to enable sensor fusion and real-time predictive edge intelligence [4] Group 4: Container Solutions - Advantech Container Catalog (ACC) offers a range of ready-to-develop edge AI applications optimized for NVIDIA Jetson platforms [5] - The containerized architecture supports scalable edge AI expansion, facilitating development from single-node setups to distributed networks [5]

Core Insights - Jinqiu Fund has completed an investment in Manifold AI, focusing on world models and embodied intelligence, with a total of over 100 million yuan raised in two funding rounds [2][4] - Jinqiu Fund emphasizes a long-term investment philosophy, seeking groundbreaking technologies and innovative business models in the field of general artificial intelligence [3][16] Investment Overview - The recent angel round of financing for Manifold AI was led by Jinqiu Fund, with participation from co-investors including Chuangweiye and existing shareholder Inno Angel Fund [4] - The seed round was led by Inno Angel Fund, with follow-on investment from the Waterwood Tsinghua Alumni Seed Fund [4] Technological Focus - Manifold AI's original embodied world model technology aims to drive the large-scale deployment of robotic brains, addressing the challenges of diverse bodies, limited data, and fragmented applications in general robotics [6][16] - The company utilizes a World Model Action (WMA) approach, leveraging vast amounts of ego-centric video data for pre-training, which is expected to enhance physical space intelligence emergence [10][16] Industry Context - The rapid evolution of robotics and the need for autonomous operational capabilities are critical for large-scale implementation [6] - The shift in technology strategies by companies like Tesla and Figure AI towards using extensive ego-centric video data for training reflects a broader trend in the industry [6][7] Team and Leadership - Manifold AI's core team is based in Beijing, with members having backgrounds in robotics and large models, and experience in developing AI products with millions of users [12] - The founder and CEO, Dr. Wu Wei, has extensive management experience and previously led the development of the world model at SenseTime [13][16] Future Outlook - Jinqiu Fund anticipates exploring the next generation of embodied intelligent world models in collaboration with Manifold AI, as the industry moves towards a deeper understanding of machine interaction with the world [17]

Core Viewpoint - The article highlights the advancements of the "Kua Fu" humanoid robot developed by Leju, which is now equipped with NVIDIA Jetson Thor, enabling it to perform various industrial applications effectively, thus accelerating the commercialization of robotics in multiple sectors [1][3]. Group 1: Technological Advancements - "Kua Fu" features over 40 degrees of freedom in its bionic structure, enhancing its flexibility and adaptability for complex tasks [3]. - NVIDIA Jetson Thor provides 2070 FP4 TFLOPS of AI computing power, significantly improving the robot's operational capabilities across various industrial scenarios [3][8]. - The bandwidth of NVIDIA Jetson Thor has been increased by 35%, allowing "Kua Fu" to maintain stable performance during long-duration tasks [5]. Group 2: Industrial Applications - In logistics, "Kua Fu" demonstrates excellent long-term stability in package sorting applications, effectively handling diverse item shapes and sizes [5]. - In smart manufacturing, the robot's full-body coordination is crucial for SMT tray retrieval tasks, ensuring high precision and compliance with operational standards [8]. - In the 3C electronics sector, "Kua Fu" can achieve rapid recognition and action response within milliseconds, essential for high-speed material sorting [10]. Group 3: Enhanced Capabilities - "Kua Fu" can autonomously adjust its grasping posture to handle various sizes and weights of containers, showcasing its spatial understanding and decision-making abilities [12]. - The robot excels in complex operations such as the precise placement of daily chemical products, requiring advanced tactile and force perception [14][15]. - The integration of NVIDIA Jetson Thor enhances "Kua Fu's" ability to process multi-modal sensor data, improving its agility, decision-making speed, and operational efficiency [15]. Group 4: Future Directions - Leju aims to continue exploring key technologies and innovative applications in humanoid robotics, pushing towards broader industrial and commercial integration [15].

Core Insights - The article highlights the integration of the "Kua Fu" humanoid robot by Leju with NVIDIA Jetson Thor, showcasing its capabilities in various industrial applications, which accelerates the commercialization of robotics technology [1][3][19] Group 1: Technology Integration - The "Kua Fu" humanoid robot features over 40 degrees of freedom, providing unprecedented flexibility and adaptability for complex industrial tasks [5] - NVIDIA Jetson Thor enhances the robot's AI computing performance by 7.5 times compared to traditional solutions, ensuring stable processing of multimodal data streams [5][19] Group 2: Industrial Applications - In logistics, "Kua Fu" demonstrates long-term stable sorting performance, overcoming traditional challenges of accuracy degradation over time [8] - The robot successfully executes a full process operation in SMT material tray retrieval, showcasing its precision in a manufacturing environment [10] - In the 3C electronics sector, "Kua Fu" achieves millisecond-level response times for identification and sorting, supporting high-speed production lines [12] - During automotive assembly, the robot adapts to various container sizes and weights, illustrating its flexibility in non-structured environments [15] - In daily chemical production, "Kua Fu" performs complex tasks with smooth operation, validating its capabilities in intricate task execution [17] Group 3: Future Prospects - The successful integration of advanced robotics hardware with AI computing power is seen as a key driver for the evolution of humanoid robots from standardized industrial applications to more flexible, general-purpose scenarios [19] - Leju's ongoing efforts in training and optimizing robots in real environments are expected to further enhance their performance and accelerate the commercialization process [19]