China’s new AI system, launched on December 23, 2025, runs on the National Supercomputing Network (SCNet), a high-speed infrastructure linking more than 30 supercomputing centers across the country. It is designed to accept natural-language research instructions and then break down tasks, allocate computing resources, perform simulations, analyze results and produce comprehensive reports without continuous human oversight.
Officials described the platform as capable of supporting nearly 100 scientific workflows spanning domains such as materials science, biotechnology and industrial artificial intelligence. By automating repetitive and computation-intensive research tasks, the system aims to streamline the pace at which complex scientific problems can be explored.
Platform Emerges In Context Of Global AI Science Initiatives
China’s rollout comes about a month after the United States announced its Genesis Mission, a federal initiative emphasizing the use of AI and national research datasets to accelerate scientific discovery nationwide. That plan, launched by President Donald Trump, aims to build an integrated AI science platform to advance breakthrough research in energy, health and other high-impact fields.
Unlike the U.S. initiative, which includes specific deadlines and cross-agency coordination, China’s platform is already operational at scale and accessible to more than 1,000 institutional users across research institutions and enterprises. Experts say this reflects a broader push by major powers to integrate advanced computing and machine intelligence into scientific discovery efforts more directly.
How The System Functions Across Research Domains
The autonomous AI agent within the system accepts simple natural-language prompts and internally constructs multi-step workflows that would traditionally require substantial manual design. Once a research question is set, the system distributes tasks across the supercomputing backbone, runs simulations, interprets large volumes of data and compiles findings into formatted scientific reports. This approach, officials say, can cut the time for certain research tasks from days to hours.
Institutional users reportedly include universities, corporate labs and government research bodies focused on accelerating discovery in areas where computation bottlenecks have historically limited progress. By linking AI to distributed computing at scale, the platform could help researchers run increasingly large experiments and test hypotheses that demand high levels of parallel processing.
Analysts note that enabling AI systems to autonomously manage research workflows represents a shift in how scientific investigation can be organized. Automating labor-intensive computations and data synthesis could reduce barriers for research teams lacking extensive human support infrastructure, potentially reshaping competitive dynamics in global science.
The intersection of AI with large-scale computing infrastructure continues to be a focus for governments and private research institutions, each seeking tools that can accelerate innovation in fields critical to economic and technological leadership. China’s deployment of this autonomous research platform signals growing urgency in this race and reflects how AI is being embedded into the core processes of scientific exploration.
