Core Insights - NVIDIA has launched the powerful new robot supercomputer NVIDIA Jetson AGX Thor, aimed at powering next-generation general and humanoid robots across various sectors including manufacturing, logistics, construction, and healthcare [3][4] - The Jetson AGX Thor offers up to 2070 FP4 teraflops of AI computing power, with a performance increase of up to 7.5 times and energy efficiency improvement of 3.5 times compared to its predecessor, Jetson Orin [3][10] - NVIDIA's CEO Jensen Huang emphasized that Jetson Thor is designed for developers creating robotic systems that interact with the physical world, marking a significant leap in physical AI capabilities [6][9] Product Launch and Features - The Jetson AGX Thor developer kit is priced at $3499 and has already been adopted by several companies including Agility Robotics, Amazon Robotics, and Boston Dynamics [4][6] - The new system supports real-time inference and is capable of running multiple generative AI models, addressing one of the major challenges in robotics [10][12] - Jetson Thor is built on NVIDIA's Blackwell architecture and features a 14-core Arm Neoverse V3AE CPU, enhancing real-time control and task management [9][10] Market Impact and Adoption - NVIDIA's Jetson platform has attracted over 2 million developers and has a growing ecosystem of over 150 hardware and software partners [8][15] - The introduction of Jetson Thor is expected to significantly enhance the capabilities of humanoid robots, with predictions of a market growth that could exceed $100 billion in the coming years [16][20] - Companies like BYD, GAC, and Xiaomi are already developing products based on NVIDIA's DRIVE AGX Thor developer kit for autonomous driving [4][18] Future Outlook - Analysts predict NVIDIA's market capitalization could reach $9 trillion by 2030, with annual revenues potentially hitting $600 billion, driven by the demand for AI infrastructure [18][20] - The company is focusing on creating a new industry that supports AI factories, AI agents, and robotics, positioning itself as a leader in the physical AI and general robotics space [20][17]

Core Viewpoint - Nvidia's Jetson Thor platform significantly enhances AI computing power and efficiency, enabling real-time processing for robotics and physical AI applications [1][3][5]. Group 1: Product Features and Specifications - Jetson Thor offers up to 2070 FP4 TFLOPS of AI computing power with a power consumption of 130 watts, and features 128GB of memory [1][3]. - The platform's AI computing performance is 7.5 times greater than its predecessor, Jetson Orin, while CPU performance has increased by 3.1 times [5][7]. - The developer kit, Jetson AGX Thor, is priced at $3499, with a bulk purchase price of $2999 for orders over 1000 units [1][3]. Group 2: Applications and Industry Adoption - Jetson Thor is designed to support various generative AI models, enabling real-time processing of high-speed sensor data and visual reasoning in dynamic environments [7][12]. - Major industry players such as Agility Robotics, Amazon Robotics, and Boston Dynamics have adopted Jetson Thor for their next-generation robotics [3][12]. - The platform is expected to enhance the agility, decision-making speed, and autonomy of robots, making it crucial for navigation and interaction in real-world scenarios [13]. Group 3: Ecosystem and Support - Jetson Thor is supported by a complete Nvidia Jetson software platform, compatible with major AI frameworks and generative AI models [11]. - The platform has attracted over 2 million developers and more than 150 hardware and software partners since its launch in 2014 [11]. - Research institutions like Stanford University and Carnegie Mellon University are leveraging Jetson Thor to advance capabilities in perception, planning, and navigation models [11]. Group 4: Autonomous Driving Applications - Nvidia has also launched the DRIVE AGX Thor developer kit for autonomous vehicles, which is now available for pre-order and expected to ship in September [4][14]. - Leading automotive companies, including BYD and Volvo, are developing solutions based on the DRIVE AGX Thor platform [14][15].

Core Insights - Nvidia is preparing for a significant announcement related to robotics, scheduled for August 25, 2025, as indicated by a teaser post on their social media [1][3] - The company has recently introduced an open-source physical AI application and a robot vision reasoning model called Cosmos Reason, which enables robots to reason like humans and take actions in the real world [3][5] Group 1: Physical AI Development - Nvidia's CEO Jensen Huang has emphasized that the next wave of AI will be Physical AI, which involves using motion skills to understand and interact with the real world [5] - Physical AI models are typically embedded in autonomous machines such as robots and self-driving cars, allowing them to perceive, understand, and execute complex operations in real-world scenarios [5][6] Group 2: Market Potential and Industry Trends - At the 2025 World Robot Conference, Nvidia's VP highlighted that Physical AI could unlock a trillion-dollar market, with advancements in technology and industry standards driving growth in the robotics sector [6] - Major companies, both domestically and internationally, including Huawei, ByteDance, BYD, Xiaomi, and Tesla, are intensifying their focus on embodied intelligence, indicating a competitive landscape in the humanoid robot industry [6] Group 3: Humanoid Robot Applications - The humanoid robot industry is entering a phase of rapid development, with a clear trend towards commercialization and practical applications in industrial settings [6] - Analysts suggest that the emergence of companies like DeepSeek is facilitating the development of general-purpose humanoid robot models, leading to a flourishing ecosystem in the humanoid robotics sector [6]

Core Insights - NVIDIA has launched the Jetson Thor, a new robotic computing platform that integrates server-level computing power into robots, achieving an AI performance of 2070 TFLOPS, which is 7.5 times higher than the previous generation Jetson Orin, with a 3.5 times improvement in energy efficiency [1][3][4]. Performance and Specifications - Jetson Thor features a massive 128GB memory configuration, unprecedented in edge computing devices [2]. - The platform is built on the Blackwell GPU architecture, supporting multiple AI models simultaneously on edge devices [6]. - The Jetson AGX Thor developer kit is priced at $3499 in the U.S. (approximately 25,000 RMB), while the T5000 module is available for $2999 for bulk purchases [8][9]. Technical Features - The Jetson Thor includes advanced specifications such as a GPU with 2560 CUDA cores and 96 fifth-generation Tensor Cores, and a CPU with 14 Arm Neoverse V3AE cores, significantly enhancing real-time control and task management capabilities [11][13]. - It supports high bandwidth with 128GB LPDDR5X memory and 273GB/s memory bandwidth, crucial for large Transformer inference and high-concurrency video encoding [13]. - The platform can achieve a response time of 200 milliseconds for the first token and generate over 25 tokens per second, enabling real-time human-robot interaction [16]. Industry Adoption - Several Chinese companies, including Unisound Medical and Youbik, are integrating Jetson Thor into their systems, highlighting its impact on robot agility, decision-making speed, and autonomy [19]. - Boston Dynamics is incorporating Jetson Thor into its Atlas humanoid robot, allowing it to utilize computing power previously only available in servers [20]. - Agility Robotics plans to use Jetson Thor as the core computing unit for its sixth-generation Digit robot, enhancing its logistics capabilities [21]. Software and Development - Jetson Thor is optimized for various AI frameworks and models, supporting NVIDIA's Isaac for simulation and development, and Holoscan for sensor workflows [14]. - The platform facilitates a continuous training-simulation-deployment cycle, ensuring ongoing upgrades to robotic capabilities even after deployment [25]. Future Outlook - NVIDIA emphasizes the need for a triad of computing systems for effective physical AI and robotics: a DGX system for training, an Omniverse platform for simulation, and the Jetson Thor as the robot's brain [23].

Core Insights - NVIDIA has launched the Jetson AGX Thor developer kit and production-grade module, designed to provide computational power for millions of robots across various industries including manufacturing, logistics, transportation, healthcare, agriculture, and retail [2] - The Jetson Thor is already being utilized by several industry leaders such as United Imaging Healthcare, Wanji Technology, UBTECH, Galaxy General, Yushu Technology, Zhongqing Robotics, and Zhiyuan Robotics [2] - NVIDIA's CEO Jensen Huang emphasized that Jetson Thor is built for millions of developers globally, enabling them to create robotic systems that can interact with and even change the physical world [2] Performance and Specifications - Jetson Thor is based on NVIDIA's Blackwell GPU and features 128GB of memory, offering up to 2,070 FP4 TFLOPS of AI computing power while operating within a power range of 130 watts [2] - Compared to its predecessor, the Jetson AGX Orin, the AI computing performance of Jetson Thor has increased by 7.5 times, and its energy efficiency has improved by 3.5 times [3] - Jetson Thor can run various generative AI models, including NVIDIA Isaac GR00T N1.5 and mainstream large language and vision-language models [3]

Core Viewpoint - NVIDIA has launched the Jetson AGX Thor developer kit and product module, aimed at supporting millions of robots across various industries such as manufacturing, logistics, transportation, healthcare, agriculture, and retail [2][8] Group 1: Product Features - Jetson Thor is powered by NVIDIA Blackwell GPU, featuring 128GB of memory and delivering up to 2,070 FP4 teraflops of AI computing power with a maximum power consumption of 130 watts [2] - Compared to its predecessor, Jetson AGX Orin, Jetson Thor offers a 7.5 times increase in AI computing power and a 3.5 times improvement in energy efficiency, capable of running any generative AI model [3][8] - The system addresses significant challenges in robot development by enabling real-time intelligent interaction between robots and the physical world [3][8] Group 2: Industry Adoption - Early adopters of Jetson Thor include industry leaders such as AgiBot, Engine AI, Galaxy Universal, UBTECH, United Imaging, Yushun, and Vanjee [2][8] - The Jetson platform has attracted over 2 million developers and a growing ecosystem of over 150 hardware, software, and sensor partners since its launch in 2014 [4] - Jetson Thor is expected to advance the development of visual AI agents and complex robotic systems, including humanoid and surgical robots [4] Group 3: Market Availability - The NVIDIA Jetson AGX Thor developer kit is now available, starting at a price of $3,499, with the Jetson T5000 product module available through global distribution partners [5]

Core Insights - NVIDIA has announced the launch of the NVIDIA Spectrum-XGS Ethernet technology, aimed at connecting distributed data centers to create an AI super factory with capabilities in the hundreds of billions [3][5] - The company is also preparing to release a new product for robotics, referred to as a "new brain," scheduled for August 25, 2025 [3][9] NVIDIA Spectrum-XGS Ethernet Technology - The Spectrum-XGS Ethernet technology is part of the NVIDIA Spectrum-X Ethernet platform and addresses the limitations of existing Ethernet infrastructure, which has high latency and unpredictable performance [5][6] - This technology introduces a scale-across infrastructure, which is considered the "third pillar" of AI computing, alongside scale-up and scale-out, enabling the connection of multiple distributed data centers into a massive AI super factory with a power capacity of one billion watts [5][6] - Key features include adaptive congestion control, nearly doubling the performance of the NCCL communication library, and an end-to-end telemetry system to ensure predictable performance across geographically dispersed clusters [6][7] Robotics Strategy - NVIDIA is set to unveil a new product for robotics, which is expected to enhance the capabilities of humanoid robots [9][10] - The company has been focusing on the development of physical AI, which involves using motion skills to understand and interact with the real world, encapsulated in autonomous machines like robots and self-driving cars [12][13] - NVIDIA's CEO has indicated that the next wave of AI will be in robotics, emphasizing the potential for significant market growth in this area [14]

Core Insights - Nvidia has introduced an open-source physical AI application and robot vision reasoning model called Cosmos Reason, which enables robots to reason like humans and take actions in the real world based on understanding [1] - The physical AI market is projected to reach trillions of dollars, as emphasized by Nvidia's executives at industry conferences [1] - Nvidia's founder, Jensen Huang, has stated that the next wave of AI is physical AI, following perception AI, generative AI, and agentic AI [1] Group 1: Nvidia's Robotics Strategy - Nvidia began its foray into robotics a decade ago with the launch of the Jetson TK1 robot brain module in 2014, marking a significant step in robot intelligence [2] - Over the past ten years, Nvidia has built a comprehensive robotics technology matrix through hardware iterations, software upgrades, and ecosystem development [2] Group 2: Collaborations and Market Trends - Nvidia has established partnerships with leading humanoid robot companies in China, including Yushu Technology and Galaxy General [3] - The humanoid robot industry is experiencing a vibrant development phase, with emerging players like DeepSeek driving the advancement of general-purpose robot models [5] - Analysts suggest that the humanoid robot industry is on the verge of large-scale commercialization, with significant advancements in intelligent decision-making and motion collaboration [5] Group 3: Investment Opportunities - Companies like UBTECH Robotics have raised substantial capital, with a recent placement raising 2.41 billion HKD, marking the largest placement in the humanoid robot sector [6] - Horizon Robotics is projected to achieve a compound annual growth rate of 57.5% from 2025 to 2027, with a target price of 7.45 HKD [6] - Portai Robotics has signed a groundbreaking order for 10,000 humanoid robots, setting a new industry standard for large-scale commercialization [7] - SUTENG Juchuang has showcased its new Active Camera platform at the World Robot Conference, highlighting its leadership in the global lidar market [8] - Tsugami Machine Tool China is expanding its production lines and actively entering the humanoid robot sector, with significant growth potential in high-end machine tools driven by the demand for humanoid robots [8]

Core Viewpoint - NVIDIA has announced the launch of the Spectrum-XGS Ethernet technology, aimed at connecting distributed data centers to create an AI super factory with a computing capacity of hundreds of billions [1][3][4] Group 1: Spectrum-XGS Ethernet Technology - The Spectrum-XGS Ethernet technology is part of the NVIDIA Spectrum-X Ethernet platform and addresses the limitations of existing Ethernet infrastructure, which has high latency and unpredictable performance [3] - This technology introduces a "scale-across" infrastructure, which is considered the third pillar of AI computing, alongside vertical and horizontal scaling, enabling the integration of multiple distributed data centers into a massive AI super factory [3][4] - Key features of Spectrum-XGS Ethernet include adaptive congestion control, improved latency management, and an end-to-end telemetry system to ensure predictable performance across geographically dispersed clusters [3][4] Group 2: Upcoming Robotics Product - NVIDIA's robotics account teased a new product, referred to as a "new brain" for robots, set to be unveiled on August 25, 2025 [5][6] - The teaser included a video showing a humanoid robot interacting with a gift box, suggesting that the new brain will be compatible with various humanoid robot models [6][7] - NVIDIA has been deepening its strategic focus on robotics, with CEO Jensen Huang emphasizing that the next wave of AI will be in the form of physical AI, which involves robots that can understand and interact with the physical world [8][9]

Core Viewpoint - Nvidia is set to unveil a new humanoid robot featuring advanced AI capabilities, referred to as the "new brain" for robots, indicating a significant advancement in physical AI technology [3][6]. Group 1: Product Launch and Features - Nvidia's upcoming humanoid robot is being promoted through a social media campaign, including a video featuring the robot reading a card from CEO Jensen Huang [3][4]. - The new brain technology is designed to be compatible with various humanoid robot models, suggesting a versatile application across different platforms [6]. Group 2: Physical AI Development - Nvidia is accelerating its deployment in the physical AI sector, which is seen as the next wave following generative and agent AI technologies [6]. - The company emphasizes that physical AI relies on neural graphics, synthetic data generation, physical modeling, reinforcement learning, and AI reasoning technologies, which are crucial for modern robotics and autonomous vehicles [6]. Group 3: Market Position and Ecosystem - Nvidia is actively seeking more applications for its GPUs in industrial and robotic fields, where physical AI is increasingly relevant [6]. - The company has established a strong ecosystem for humanoid robots, with many manufacturers opting for Nvidia's solutions due to their comprehensive support, which reduces development time [6]. Group 4: Recent Product Introductions - In January, Nvidia introduced the foundational world model Cosmos at CES, aimed at generating synthetic scenarios for autonomous driving and supporting physical AI system development [7]. - At SIGGRAPH, Nvidia launched an open-source 7 billion parameter visual language model (VLM) called Cosmos Reason, designed to help robots and visual AI agents understand and interact with the physical world [7]. - Nvidia also announced new hardware solutions, including servers equipped with RTX PRO 6000 Blackwell GPUs, targeting enterprise workloads in agent AI, industrial applications, and physical AI [7].