An unmanned delivery vehicle at the Jiushi Intelligent Huai'an manufacturing base. Photo by Wang Dong. (Provided by Visual Jiangsu Network.) By Xu Guanying, reporter for this newspaper.

This year's "Su Super" tournament drew remarkable attention for its high technological content both on and off the field. Security patrol unmanned vehicles developed by Jiushi (Suzhou) Intelligent Technology Co., Ltd. were deployed successively at venues in Xuzhou, Changshu, Nanjing, Lianyungang, and Huai'an to carry out security missions, becoming a key component of the "digital-intelligent defense line." Recently, the "Autonomous Driving Police Security Patrol Application Scenario" led by the company was selected for the "2026 Frontier Technology Application Scenario Construction Demonstration List" published by the Provincial Department of Science and Technology and the Provincial Development and Reform Commission. The list contains 31 scenarios in total, highlighting the distinctive characteristics of hardcore technology empowering future industries.

Since implementing the "5 Hundreds" action for future industry development in 2024, Jiangsu has actively built frontier technology application scenarios around the "10+X" future industry system, using scenarios to drive iterative upgrading of new technologies and the rapid emergence of new business formats, activating new momentum for future industries. With the release of the 2026 list, the number of frontier technology application scenarios has increased to 124.

Among the new batch of 31 scenarios, artificial intelligence accounts for the largest share with 9, involving the integration of AI with integrated circuits, new materials, smart factories, smart logistics, smart cities, and future health; embodied intelligent robotics has 4 scenarios; commercial aerospace, hydrogen energy, and new-type energy storage each have 3; the remaining scenarios fall in fields such as quantum technology, brain-computer interfaces, and atomic-level manufacturing.

The "Autonomous Driving Police Security Patrol Application Scenario" belongs to the "AI + Smart City" sub-sector. A representative from Jiushi explained that the company's 30,000 unmanned vehicles equipped with L4 autonomous driving systems have operated nearly 300 million kilometers across more than 300 cities, honing technology and accumulating experience through urban logistics delivery scenarios. Building the "Autonomous Driving Police Security Patrol Application Scenario" means extending mature L4 autonomous driving capabilities to police patrol operations, establishing an unmanned patrol system of "intelligent unmanned vehicles + cloud dispatch hub + police linkage business system" to address pain points such as delayed emergency response and high labor costs in urban patrols. The scenario is planned to advance in a "three-year, three-step" rhythm: first, adding pilot points in multiple areas of Suzhou, expanding常态化 patrol vehicles to 20 units, completing multi-scenario, all-weather stress testing and police adaptation verification to form a standardized solution; second, collaborating with relevant departments to build a provincial-level dispatch platform and replicate the scenario in other prefecture-level cities; third, expanding the mature model nationwide.

Scenario construction emphasizes enterprises' role as innovation leaders. Of the 31 scenarios, 28 are led by enterprises, accounting for 90.3%. In terms of distribution, 18 are led by enterprises in provincial-level or higher high-tech zones, accounting for 58.1%. MedGraph AI (Suzhou) Life Sciences Technology Co., Ltd., located in Suzhou High-tech Zone, is leading the construction of the "Quantum AI Innovative Drug Design Application Scenario." The company's independently developed drug design platform and quantum computing platform work in tandem to achieve high-precision dynamic simulation of key drug R&D processes such as "drug-target" interactions. Company CEO Li Xiaoran believes that for innovative drug R&D, the deep integration of quantum computing and artificial intelligence is expected to significantly shorten the preclinical research cycle; for quantum computing applications, innovative drug R&D is a promising industrial field. He said: "We will open both platforms and work with partners to explore the revolutionary potential of quantum computing in drug molecular dynamics simulation, drug screening, and optimization, driving a leapfrog improvement in innovative drug R&D efficiency."

In application scenario construction, Jiangsu encourages both practical needs-oriented verification and demonstration in government affairs, manufacturing, healthcare, and emergency response, as well as supporting the use of frontier technologies to empower scientific research and seize the high ground in future technological competition. The "CENI-Empowered High-Energy Physics Large Scientific Facility AI4S Cluster Innovation Demonstration Application Scenario" is led by the Jiangsu Future Network Innovation Research Institute and jointly built with the Institute of High Energy Physics, Chinese Academy of Sciences. The scenario aims to leverage China's first major national science and technology infrastructure in the information and communication field—the Future Network Test Facility CENI—to "link" dispersed large scientific facilities and form a "scientific research network" deeply integrating "computing, network, data, and intelligence." Wang Chunsheng, Director of the External Cooperation Department of the Jiangsu Future Network Innovation Research Institute and Director of the CENI Open Sharing Center, introduced that China's 11 large scientific facilities in the high-energy physics field are distributed across Guangdong, Sichuan, Tibet, Beijing, and other locations, continuously generating massive amounts of data, while the scientist teams using the data for research are even more widely dispersed. Connecting these facilities would involve network links exceeding 2,000 kilometers, with annual data transmission peaking at nearly 400 PB—equivalent to continuously playing a 4 GB, 2-hour high-definition movie for over 20,000 years. Traditional networks struggle to support efficient aggregation and high-real-time collaboration of massive data, while the deterministic network built on CENI can provide critical support. As the world races to deploy AI for Science, this research network carrying clustered innovation exploration of large scientific facilities will continue to drive paradigm shifts in research and facilitate major scientific outputs.