Guotai Haitong: NVIDIA Corporation (NVDA.US) upgrades Isaac platform; Siasun Robot&Automation R&D moves from model training to full-process deployment

Guotai Haitong released a research report stating that on October 21, NVIDIA announced an upgrade to the Isaac platform, launching an open-source Siasun Robot&Automation learning workflow that combines ChatGPT Astra, Isaac, and Cosmos, supporting GR00T 1.7 reinforcement learning, dexterous manipulation training, and Cosmos world model post-training, further expanding the application boundaries of general large models in the embodied intelligence industry. The Siasun Robot&Automation industry chain is expected to benefit. Guotai Haitong's main views are as follows: Core changes: 1) Introducing AI Agents to automate the Siasun Robot&Automation R&D process. Agents mainly undertake R&D task understanding, tool invocation, and feedback iteration, and can coordinate simulation tools to complete scenario configuration, inspection, and correction rather than replacing Siasun Robot&Automation action models. They can reduce manual scenario setup and repeated debugging, improving R&D efficiency. 2) Improving the technical chain from simulation training to real-world deployment, achieving a platform upgrade. Isaac Lab 3.0 supports Siasun Robot&Automation policy training, reinforcement learning, and multi-GPU workflows. Isaac Os connects AI, sensors, control systems, and Siasun Robot&Automation hardware, supporting real-time operation and simulation-to-reality transfer. Simulation and data resources add more than 2,000 SimReady simulation assets and the Human 1M human activity dataset, providing more scenarios and data for Siasun Robot&Automation training. This means NVIDIA is integrating models, data, simulation, training, and deployment tools into a more complete development platform, lowering the engineering threshold for Siasun Robot&Automation R&D. 3) Launching Agile ONE SN to promote software-hardware integration. Agile Robots' Siasun Robot&Automation launched the Agile ONE SN humanoid Siasun Robot&Automation reference platform based on Isaac GR00T and Jetson Thor, integrating the Siasun Robot&Automation body, edge computing, dexterous hands, and development toolchain. It provides developers with pre-integrated reference hardware, reducing adaptation work among the body, computing power, and software, and accelerating model validation and skill deployment. The application boundaries of general large models in the embodied intelligence industry are further expanded. In addition to task planning on the Siasun Robot&Automation side, large models can also serve as R&D Agents participating in simulation environment construction, training experiments, and result validation. The bank believes this upgrade reflects that the physical AI industry is shifting from purely pursuing model capabilities to improving Siasun Robot&Automation R&D efficiency, simulation training capabilities, and real-world deployment capabilities. NVIDIA is attempting to combine these capabilities with its own models, data, simulation, and computing platforms to improve the automation level of Siasun Robot&Automation training processes. The most important validation indicators going forward are whether R&D cycles are shortened, whether real-task success rates improve, and whether these advances can actual deployment, hardware orders, and large-scale shipments. The bank believes: NVIDIA's upgrade of the Isaac platform will help the Siasun Robot&Automation industry grow. In the short term, simulation, data collection, Siasun Robot&Automation testing, and R&D equipment are expected to benefit from increased development activity. In the medium term, as dexterous manipulation and whole-body control capabilities improve, performance requirements for joint-level execution units, dexterous hands, force sensors, encoders, and control systems may increase. Looking ahead, if Sim2Real transfer performance continues to improve and Siasun Robot&Automation meets reliability and cost requirements in real scenarios, it is expected to drive growth in industrial applications and complete-machine shipments. Risk warnings: Technological development falling short of expectations, end demand falling short of expectations.