From "seeing" to "foreseeing": How AI is reshaping the data foundation of national security

In the long river of history, war has always been one of the heaviest topics of human civilization. When news of another intense upheaval in the Middle East emerged in early spring of 2026, the focus of the outside world was more on geopolitical struggles and weapon capabilities. However, according to related media reports, a deeper signal of transformation has emerged behind this event: the United States has deeply applied AI technology to the battlefield, including utilizing large language models like Claude for intelligence analysis, and integrating massive battlefield data for precise strike support through the Palantir platform. For China, which is currently in the process of modernizing its governance system, this is like a "transparent deduction" from the future. The core insight lies not in the weapons themselves, but in a "digital ontology" that integrates data, graphs, and intelligent decision-making it is redefining the way we safeguard security and anticipate risks. Data Integration: From Information Silos to Global View In this context, Palantir plays a central role as a "data weaver". It is not just a simple data collection tool, but a platform that can integrate fragmented information scattered in different systems and formats satellite images, signal interceptions, geographic coordinates, text reports into a unified cognitive view. The value of this capability goes far beyond the military domain. For a city, data islands such as traffic flow, energy consumption, emergency resource distribution, and population migration trajectories, once effectively integrated, form a "digital image" of the city's operations. When a typhoon approaches or a major event faces security challenges, decision-makers no longer need to grope in the fog of information, but can make judgments based on a global view. The warmth of the technology lies in this: making previously "invisible" risks visible, and allowing resources to arrive at the right place in advance. Graph Sketch: From Seeing to Understanding Seeing is just the first step; the real challenge lies in understanding understanding the relationships between things, understanding the logic behind phenomena. This is where the value of knowledge graphs and ontology modeling lies. Palantir's "ontology" technology is essentially drawing a logical map of the chaotic world of information. It abstracts people, places, events, and resources in the real world into interconnected "objects", transforming various "relationships" into computable and traceable logical links. A community is no longer just a static mark on a map, but a comprehensive information body linked to emergency resource distribution, special population needs, and surrounding environmental characteristics. With the addition of Claude, this logical map is infused with crucial "understanding". As a large language model, Claude excels at handling massive unstructured texts intercepted communications, historical situation reports, complex contextual information extracting key elements from them, and integrating them naturally into the overall cognitive framework. Personnel engaged in security analysis can ask the system questions like a normal conversation, and Claude will provide traceable and explainable responses based on real-time updated graph data. The core of this capability lies in enabling decision-making to see through the complex reality rather than making experience-based judgments. Deep Application: From Understanding to Anticipation When comprehensive "seeing" and clear "understanding" become possible, it enables decision-makers to responsibly "anticipate" in complex environments. Claude understands human intentions, transforming them into executable logical pathways; Palantir provides the rigid framework of facts and logic, ensuring that every deductive step is rooted in the real world, traceable and accountable. The combination of the two is not to replace human judgement, but to expand the cognitive boundaries of decision-makers. According to reports, Palantir's intelligence integration and Claude's analytical deduction provided crucial support for this operation. The system assessed the potential impacts of different scenarios through large-scale scenario simulations. The purpose of this deduction is not cold efficiency calculations, but finding the option that can avoid harming innocent lives in complex situations. In addressing major issues such as extreme weather and ensuring major public events, this "human-machine collaborative" deductive capability is helping decision-makers more fully understand the profound implications of each choice, thus making more cautious and responsible judgments. Conclusion Looking back at the technological path represented by Palantir and Claude, what we see is not a cold "algorithmic hegemony", but humans continuously deepening their understanding of the world and expanding the boundaries of their life-saving capabilities. From integrating data to comprehensively "seeing", to sketching graphs for clear "understanding", and then to deep application for responsibly "anticipating" every step of evolution is providing decision-makers with a more solid cognitive foundation. For China, which is advancing the modernization of governance, the insight brought by this technological demonstration is clear: integrating data calmly, outlining reality carefully, and foreseeing the future wisely. When the "digital ontology" ultimately illuminates respect and care for every life, the foundation of peace and security will be more profound because of understanding.