Core Viewpoint - The article discusses the emergence of a new player in the field of embodied intelligence, highlighting the journey of the founding team from their previous experiences in AI to their current entrepreneurial venture, which focuses on practical applications in logistics and robotics [4][5][20]. Group 1: Company Formation and Background - The founding team of Yuanli Lingji consists of veterans from the AI 1.0 era, specifically from the company Megvii, bringing extensive experience in transitioning AI from laboratory settings to industrial applications [6][5]. - The initial inspiration for the startup came from the realization that many previously imported components for robotics are now available domestically, providing a solid material foundation for development [9][10]. - The company was officially established in March 2025 after a year of experimentation and prototype development [18][17]. Group 2: Business Focus and Strategy - Yuanli Lingji aims to penetrate the logistics sector, focusing on high-frequency, rule-based tasks such as sorting and distribution, leveraging their self-developed multimodal embodied intelligence model [20][21]. - The company has already demonstrated basic delivery capabilities and completed proof of concept (POC) in logistics scenarios within ten months of establishment [22][25]. - The founders emphasize the importance of hardware, AI, and application scenarios being equally critical for the success of robotics in industrial settings [26][60]. Group 3: Technological Development and Innovation - The company is developing its own hardware to meet industrial standards, focusing on reliability, consistency, and ease of maintenance, with plans to release a new generation of embodied robots [27][28]. - The founding team has a strong background in AI, having achieved significant milestones in various applications, which positions them well for the current AI 2.0 landscape [30][32]. - Yuanli Lingji has released several open-source tools and platforms to lower barriers for researchers and developers in the field of embodied intelligence, including Dexbotic and Robochallenge [38][44][50]. Group 4: Market Perspective and Future Outlook - The company acknowledges the current market's cautious approach, with potential industrial clients being in a phase of observation and exploratory investment [60][62]. - The founders believe that the development and application of technology will follow a long cycle, drawing from their experiences in the AI 1.0 era, and are committed to a patient and steady growth strategy [65][66]. - Yuanli Lingji aims to contribute to the standardization and open collaboration in the field of embodied intelligence, fostering a community that can innovate collectively [47][58].

Core Insights - The article highlights the recent funding success of "Yuanli Lingji" (原力灵机), a robotics startup focused on embodied intelligence, which has raised nearly 1.2 billion yuan in total funding this year [2][5]. Funding Overview - "Yuanli Lingji" completed a series of funding rounds, including an A+ round of approximately 1 billion yuan led solely by Alibaba on November 12, 2025, and an A round led by NIO Capital on August 27, 2025, with a total of nearly 1 billion yuan raised in these two rounds [3][5]. - The company has achieved a total of nearly 1.2 billion yuan in three funding rounds within nine months, starting with a 200 million yuan angel round on March 26, 2025 [3][5]. Company Background - "Yuanli Lingji" was founded on March 6, 2025, in Chongqing by early core technical members of Megvii Technology (旷视科技), including Tang Wenbin, Fan Haoqiang, and Zhou Erjin, focusing on the integration of large model technology with robotics [5][6]. - The founding team has a strong academic background and over ten years of experience in AI product implementation, making them a unique player in the embodied intelligence sector [7]. Technical Capabilities - The company has developed a comprehensive technology stack for embodied intelligence, achieving significant results in benchmark tests and becoming the first in China to exceed a 90% success rate across over a hundred tasks [8]. - "Yuanli Lingji" has created a proprietary end-to-end multi-modal large model (MMLA) that integrates various sensor data and language models, enabling intelligent generalization across different scenarios and tasks [8]. Competitive Landscape - The article notes that "Yuanli Lingji" shares the spotlight with another startup, "Tashi Zhihang," which has also raised significant funding without product launches, indicating a competitive and rapidly evolving market for embodied intelligence startups [10]. - The company is positioned to leverage its unique combination of algorithm, hardware, and application scenarios, which is seen as a competitive advantage in the robotics field [15].

Core Insights - Dexmal, a company focused on embodied intelligence, has completed a significant A+ round financing of several hundred million yuan, exclusively funded by Alibaba [2] - The company aims to utilize the nearly 1 billion yuan raised from both A and A+ rounds for the development and implementation of intelligent robot software and hardware technologies [2] Company Overview - Founded in March 2025, Dexmal specializes in the research and application of embodied intelligence software and hardware technologies [2] - The CEO, Tang Wenbin, is a notable figure with a strong academic background from Tsinghua University and experience as a co-founder and CTO of Megvii Technology [2] - The core team possesses a unique combination of AI academic excellence and over a decade of experience in deploying AI-native products, excelling in algorithm development, hardware innovation, data management, and practical applications [2] Technological Advancements - Dexmal has developed an end-to-end multimodal embodied intelligence model, MMLA, which integrates various sensor data and models to achieve intelligent generalization across different scenarios and tasks [3] - The company has launched the Dexbotic toolbox and the DOS-W1 open-source hardware product, significantly lowering the barriers to robot usage and enhancing maintenance and modification ease [3] - Dexmal has also partnered with Hugging Face to create RoboChallenge, the world's first large-scale real-machine evaluation platform for embodied intelligence [3] Competitive Edge - The company has achieved notable success in global robotics competitions, including winning first place in the RoboTwin simulation platform competition and gold medals in the ManiSkill-ViTac 2025 challenge [4] - These achievements highlight the innovative and leading nature of the company's embodied intelligence algorithms [4] Future Directions - Dexmal plans to accelerate collaborative innovation in algorithm-driven, hardware design, and scenario integration within the embodied intelligence field, aiming to bring general artificial intelligence into the physical world [4]

Core Insights - The article highlights the rapid growth and investment in the embodied intelligence sector, particularly focusing on the company Dexmal, which has raised nearly 1 billion RMB in funding [2][6]. Group 1: Company Overview - Dexmal, established in March 2025, specializes in the research and development of embodied intelligence hardware and software technologies [10]. - The company's mission is to create intelligent, useful, and trustworthy robots to enhance quality of life [11]. - The founding team consists of members with extensive backgrounds in AI and practical experience in scaling AI-native products, primarily from Megvii Technology [12][13]. Group 2: Recent Funding and Investment - Dexmal recently completed a significant A+ round of financing, with Alibaba as the exclusive investor, marking a notable endorsement from a major player in the tech industry [3][5]. - In just over two months, Dexmal has secured nearly 1 billion RMB across three funding rounds, indicating strong investor confidence and market interest [6][9]. Group 3: Technological Advancements - Dexmal has published over ten papers in top conferences related to AI and embodied intelligence, showcasing its research capabilities [16]. - The company has developed two frameworks, Real-time VLA and MemoryVLA, aimed at optimizing robot performance for real-time and long-duration tasks [17]. - Dexmal has also launched an open-source VLA toolbox called Dexbotic, designed to facilitate research in embodied intelligence by addressing issues of fragmentation in research ecosystems [20][22]. Group 4: Product Development - Alongside software, Dexmal has introduced a hardware product, DOS-W1, which serves as a modular and open experimental platform for data collection and robotics research [23][25]. - The DOS-W1 is designed to lower the barriers to entry for research in embodied intelligence while enhancing data collection efficiency [28]. Group 5: Competitive Edge and Achievements - Dexmal's team has achieved significant recognition in the robotics field, winning gold medals in global competitions such as the ICRA 2025 and CVPR 2025 [33][34]. - The team's past experiences and accolades serve as a quality assurance for their products, positioning Dexmal as a formidable player in the embodied intelligence landscape [35]. Group 6: Founding Team Background - The founding team includes notable figures such as Tang Wenbin, Fan Haoqiang, Zhou Yuzhen, and Wang Tiancai, all of whom have extensive experience in AI and have previously contributed to major advancements in the field [36][78]. - Their collective expertise and past successes in AI competitions and research provide a strong foundation for Dexmal's future endeavors in embodied intelligence [78].

Core Insights - Dexmal has completed a significant A+ round financing of several hundred million yuan, with Alibaba as the sole investor, following a previous A round led by NIO Capital and other notable investors, totaling nearly 1 billion yuan across both rounds [1] - Founded in March of this year, Dexmal focuses on the research and application of embodied intelligence hardware and software technologies, boasting a core team with top AI academic backgrounds and over a decade of experience in scaling AI-native products [1] - The company has developed an end-to-end multimodal embodied intelligence model, MMLA, which integrates various sensor data and models to achieve intelligent generalization across different scenarios and tasks [1] Recent Developments - In October, Dexmal launched the Dexbotic toolbox based on PyTorch, providing a one-stop research service for practitioners in the embodied intelligence field, and introduced the DOS-W1 open-source hardware product to lower the barriers for robot usage [2] - The company has also partnered with Hugging Face to release the world's first large-scale real-machine evaluation platform for embodied intelligence, named RoboChallenge, promoting industry development through software, hardware, and standards [2] - Dexmal has achieved notable success in competitions, including a tie for first place in the RoboTwin simulation platform competition and gold medals in two categories at the ICRA2025 global robot tactile fusion challenge [2] Future Outlook - Dexmal aims to accelerate collaborative innovation in algorithm-driven, hardware design, and scenario closure within the embodied intelligence field, with a focus on the physical world application of general artificial intelligence [2]

Group 1 - The core viewpoint of the article is that the investment landscape in the field of embodied intelligence is heating up, exemplified by the recent financing of Dexmal, which raised nearly 1 billion yuan [1][2][6]. - Dexmal's latest financing round attracted attention due to Alibaba being the exclusive investor, highlighting the company's potential and market interest [3][5]. - In just over two months, Dexmal has successfully raised close to 1 billion yuan across three financing rounds, indicating rapid growth and investor confidence [6][4]. Group 2 - Dexmal, founded in March 2025, focuses on the research and application of embodied intelligence hardware and software technologies [7]. - The company's mission is to create intelligent, useful, and trustworthy robots to enhance quality of life [8]. - The core team of Dexmal consists of members with top AI academic backgrounds and extensive experience in scaling AI-native products, primarily from Megvii Technology [9][10]. Group 3 - Dexmal has made significant progress in research, publishing over ten papers in top conferences related to AI and embodied intelligence [13]. - The company has developed two frameworks, Real-time VLA and MemoryVLA, which optimize robot performance for real-time and long-duration tasks [14][15]. - To address the fragmented research ecosystem, Dexmal has launched an open-source VLA toolbox called Dexbotic, aimed at providing a unified research platform for embodied intelligence [18][20]. Group 4 - Dexmal has also introduced a hardware product, DOS-W1, which serves as an open, modifiable, and expandable experimental platform for embodied intelligence research [21][24]. - The DOS-W1 is designed with a modular architecture, allowing for easy upgrades and modifications, thus lowering the research barrier in the industry [26]. - Additionally, Dexmal has partnered with Hugging Face to launch RoboChallenge, the world's first large-scale evaluation platform for embodied intelligence [28]. Group 5 - The founding team of Dexmal includes notable figures such as Tang Wenbin, Fan Haoqiang, Zhou Yanjin, and Wang Tiancai, all of whom have extensive experience in AI and have previously worked at Megvii Technology [33][57][71]. - Tang Wenbin, the CEO, has a strong background in computer science and has been instrumental in the success of Megvii [34][41]. - Fan Haoqiang and Zhou Yanjin are recognized for their achievements in international competitions and their contributions to the field of AI, further solidifying the team's expertise [44][62][68].

Core Insights - Dexmal, a company specializing in embodied intelligence, has completed a significant A+ round financing of several hundred million yuan, with Alibaba as the sole investor [2] - The company aims to utilize the nearly 1 billion yuan raised from both A and A+ rounds for the development and implementation of intelligent robot software and hardware technologies [2] Company Overview - Founded in March 2025, Dexmal focuses on the research and application of embodied intelligence software and hardware technologies [2] - The CEO, Tang Wenbin, is a notable figure with a strong academic background from Tsinghua University and extensive experience in AI product implementation [2] - The core team possesses a unique combination of AI academic expertise and over 10 years of experience in scaling AI-native products, excelling in algorithm development, hardware innovation, data management, and practical application [2] Technological Advancements - The company has developed an end-to-end multimodal embodied intelligence model, MMLA, which integrates various sensor data and models to achieve intelligent generalization across different scenarios and tasks [3] - Dexmal has launched the Dexbotic toolbox and the DOS-W1 open-source hardware product, significantly lowering the barriers to robot usage and enhancing maintenance and modification convenience [3] - The company has also partnered with Hugging Face to create RoboChallenge, the first large-scale real-world evaluation platform for embodied intelligence [3] Competitive Achievements - Dexmal has participated in prestigious global competitions, achieving top rankings in events such as CVPR 2025 and ICRA 2025, showcasing the innovation and leadership of its embodied intelligence algorithms [4] - The company has completed three rounds of financing within eight months, attracting investments from notable venture capital firms [4] Future Directions - Dexmal plans to accelerate collaborative innovation in algorithm-driven, hardware design, and scenario integration within the embodied intelligence field, aiming to bring general artificial intelligence into the physical world [4]

Group 1 - Dexmal has completed a series A+ financing round worth several hundred million yuan, with Alibaba as the sole investor [1] - The previous A round was led by NIO Capital, with participation from various investors, raising nearly 1 billion yuan in total across both rounds [2] - The funds will primarily be used for the research and development of intelligent robot software and hardware technologies [2] Group 2 - Dexmal, established in March 2025, focuses on the research and implementation of embodied intelligence software and hardware technologies [2] - The core team possesses top academic backgrounds in AI and over 10 years of experience in scaling AI-native products [2] - The company has developed an end-to-end multimodal embodied intelligence model (MMLA) that integrates various sensor technologies and models for intelligent generalization across different scenarios and tasks [2] Group 3 - Dexmal has open-sourced a VLA toolbox called Dexbotic based on PyTorch and launched an open-source hardware product, DOS-W1, which significantly lowers the barriers to using robots [2] - The open-source initiatives enhance the convenience of robot maintenance and modification [2]

Core Insights - Dexmal, a company specializing in embodied intelligence, has completed a Series A+ financing round amounting to several hundred million yuan, with Alibaba as the sole investor [1] - The previous Series A round was led by NIO Capital, with participation from several other investors, raising nearly 1 billion yuan across both rounds [1] - The funds will primarily be used for the research and development of software and hardware technologies for embodied intelligent robots [1] Company Overview - Dexmal was established in March 2025 and has developed a one-stop VLA toolbox called Dexbotic, along with a robot hardware platform named DOS-W1 [1] - The company has also launched a large-scale real machine evaluation platform called RoboChallenge, focusing on advancing the embodied intelligence robotics industry through software, hardware, and standards [1] - The team has accumulated substantial practical experience in the field of AI logistics robots [1]

Core Insights - Dexbotic is an open-source visual-language-action (VLA) model toolkit developed by Dexmal, aimed at researchers in the field of embodied intelligence, featuring a modular architecture with three core components: Data, Experiment, and Model [3][7][9]. Group 1: Need for a Unified VLA Development Platform - The VLA models serve as a crucial technology hub connecting perception, cognition, and action, but face challenges such as severe decentralization in research, cumbersome development processes, and fairness issues in algorithm comparison [5][7]. - The introduction of Dexbotic addresses these pain points by providing a standardized, modular, and high-performance research infrastructure, moving the field from "reinventing the wheel" to "collaborative innovation" [7][9]. Group 2: Dexbotic Architecture - The overall architecture of Dexbotic consists of three main layers: Data Layer, Model Layer, and Experiment Layer, with the Data Layer optimizing storage and integrating multi-source data [9][11]. - The Model Layer includes the foundational model DexboticVLM, which supports various VLA strategies and allows users to customize new VLA models easily [9][11]. - The Experiment Layer introduces an innovative script mechanism for conducting experiments, enabling users to modify configurations with minimal changes while ensuring system stability [11][12]. Group 3: Key Features - Dexbotic offers a unified modular VLA framework compatible with mainstream large language models, integrating embodied operation and navigation functionalities [13]. - High-performance pre-trained models are available for major VLA algorithms, significantly enhancing performance in various simulation environments and real-world tasks [13]. - The experimental framework is designed for flexibility and extensibility, allowing users to easily modify configurations and switch models or tasks [13][14]. Group 4: Open Source Hardware - Dexmal has launched its first open-source hardware product, Dexbotic Open Source - W1 (DOS-W1), featuring a fully open design that lowers barriers for use and maintenance [16][17]. - The hardware design includes modular components and ergonomic features to enhance user comfort and data collection efficiency [17]. Group 5: Future Outlook - Dexmal plans to expand its offerings with more advanced VLM base models and open-source hardware, integrating simulation-to-real-world transfer learning tools and establishing a community-driven model contribution mechanism [19]. - Collaboration with RoboChallenge aims to create a comprehensive technical loop for development, training, inference, and evaluation, ensuring transparency and fairness in performance validation [20].