Investment Rating - The SW Machinery Equipment Index increased by 5.39% during the week of January 5 to January 9, 2026, ranking 10th among 31 primary industry categories [12][14]. Core Insights - The report anticipates a significant increase in domestic rocket launches in 2026, driven by the urgent demand for satellite deployment [21]. - The robotics sector is expected to experience a strong market trend in Q1 2026, with advancements in humanoid robots [21]. - The nuclear fusion energy sector is highlighted as a potential investment opportunity during the 14th Five-Year Plan period, with significant technological breakthroughs reported [22]. - The global shipbuilding industry is showing signs of recovery, with new ship prices increasing and order volumes significantly improving [31]. - The engineering machinery sector is entering an upward cycle, with robust domestic and export sales of excavators and loaders [35]. - The report indicates varying degrees of industry performance, with general machinery under pressure, while engineering machinery and railway equipment show positive trends [46][45]. Summary by Sections 1. Stock Portfolio - Recommended stocks include Chaojie Co., Feiwo Technology, Guanglian Aviation, Hengli Hydraulic, Lianchuang Optoelectronics, XCMG, SANY Heavy Industry, Zoomlion, LiuGong, and China Shipbuilding [10]. 2. Market Review - The SW Machinery Equipment Index rose by 5.39% in the first week of 2026, outperforming the CSI 300 Index, which increased by 2.79% [12][14]. 3. Key Data Tracking 3.1 General Machinery - The manufacturing PMI was reported at 50.1% in December, indicating a slight recovery [23]. 3.2 Engineering Machinery - Excavator sales reached 23,095 units in December, marking a year-on-year increase of 17.6% [35]. 3.3 Railway Equipment - Railway fixed asset investment has maintained a steady growth rate of around 6% since 2025 [45]. 3.4 Shipbuilding - The global new ship price index reached 184.65 in December, with a month-on-month increase of 0.17% [46]. 3.5 Oil Service Equipment - The oil service equipment sector is stabilizing, with high demand in the Middle East [49]. 3.6 Industrial Gases - A decrease in raw material prices is expected to improve profitability in the steel sector, boosting demand for industrial gases [55]. 3.7 Gas Turbines - GEV's new gas turbine orders grew by 39% year-on-year in the first three quarters of 2025, indicating a robust market [57].

Summary of Key Points from the Conference Call Industry Overview - The focus of the humanoid robot industry has shifted towards the application of AR capabilities and large model capabilities to meet user demands, with expectations for deep integration of hardware and models within 3-5 years in everyday scenarios [1][3] - The development of humanoid robots can be categorized into three stages: initial focus on core components, establishment of hardware architecture, and eventual deep integration of hardware and models for widespread application [3] Core Insights and Arguments - AI Agents play a crucial role as the "brain" of embodied robots, responsible for task decision-making and reasoning, enhancing task execution efficiency through tailored applications for different scenarios [1][8] - The mainstream framework for embodied robot brains is structured in five layers: physical layer, training layer, data layer, model layer (including LLM, VLM, and VLA), and application layer [1][9] - The introduction of 3D spatial perception capabilities is essential for improving spatial modeling and perception, which is vital for achieving general AGI [1][19] - The industrial sector predominantly employs a hierarchical embodied large model architecture to avoid retraining software due to hardware upgrades, contrasting with the academic sector's end-to-end approach [1][17] Technological Developments - Google's RT series models have significantly advanced VLA model development, although they have not been open-sourced, while Stanford and Berkeley's open-source models have accelerated industry growth [1][10][12] - Philips' Helix architecture, released in February 2025, differs fundamentally from the VOLATI model by employing a layered system that allows for cost-effective hardware upgrades [1][14][15] - The VELAN model is currently simple, utilizing text, visual, and action encoding for training, similar to Tesla's autonomous driving approach [1][16] Challenges and Future Directions - Current VLA models face challenges such as insufficient data volume, low task generalization ability, and significant performance impacts from lighting changes [1][18] - The importance of establishing industry standards for humanoid robots is emphasized, as it will influence market development and safety certifications [1][24] - Future trends in intelligent large models will focus on data collection and training to enhance the generalization capabilities of VRA models, with potential for unified foundational VOI models [1][27] Additional Insights - The competition among terminal manufacturers will hinge on optimizing foundational large models and unique advantages in scene data training for better hardware integration [1][2][27] - The VRM model's core in interaction capabilities includes voice recognition, output, and expression management, which are crucial for enhancing robot interaction [1][26] - Data collection in humanoid robotics is evolving, with a focus on human sensory perception data to improve design richness and reduce the Sim-to-Real gap [1][23]