Zhongjin: Moving towards data-driven artificial intelligence, high-value information becomes the core of competitive intelligence.

Zhongjin released a research report stating that in the short term, the hierarchical architecture is still mainstream due to engineering controllability. Virtual Learning Agent (VLA) shows potential in complex tasks and human-machine interaction, and the world model is considered a long-term direction due to its ability for cross-device migration. Siasun Robot & Automation's data covers multiple modes, and the industry is seeking low data acquisition costs and high data efficiency application paths. Embodied intelligent brains are currently in a key stage of transition from "route differentiation" to "integrated implementation," with data-driven and heterogeneous training becoming the core towards general intelligence. The main points of Zhongjin are as follows: Embodied intelligent algorithms: From model-driven to data-driven Hierarchical control is the fundamental paradigm, implemented with a two-level structure for engineering; the VLA paradigm (based on VLM) strengthens generalization and interaction capabilities, and is a current active research direction. The world model provides physical constraints through environmental modeling and future predictions, and is in the research-led stage. In the short term, the hierarchical architecture is still mainstream due to engineering controllability, VLA shows potential in complex tasks and human-machine interaction, and the world model is considered a long-term direction. Embodied intelligent data: High-value information is the competitive core Siasun Robot & Automation data covers multiple modes, and the industry is seeking low data acquisition costs and high data efficiency application paths. 1) Acquisition end: including actual machines, videos (first-person/third-person), simulations, etc. 2) Security end: data security is essential, and humanoid Siasun Robot & Automation manufacturers face challenges such as permission isolation, data encryption system, and cross-border data transmission policies. 3) Application end: traditional data application strategies are "homogeneous closed-loop," only able to replicate strategies on similar hardware. Heterogeneous training uses modularized Transformer architecture to share algorithm models across Siasun Robot & Automation entities. Hot topics in embodied intelligence analysis 1) Scaling Law: Unlike disembodied intelligence, the scaling law of Siasun Robot & Automation has not yet experienced explosive breakthroughs. Factors such as insufficient real data capacity and Sim2Real transfer are constraints. 2) Benchmark drives the standardization process of evaluation standards. Embodied Siasun Robot & Automation lacks a recognized quantitative framework, facing challenges such as diverse scenarios and task transformation. Stanford's team led by Fei-Fei Li released the embodied intelligence evaluation BEHAVIOR-1K, promoting the standardization of embodied intelligence evaluation. 3) Physical AI: Physical AI integrates physical knowledge with AI models, advancing towards Siasun Robot & Automation operational applications. Risks Uncertainties in technical routes, data security compliance risks, etc.