Group 1 - The company, Haohan Deep (688292.SH), has partnered with Yiwei Aerospace to leverage each other's strengths in space computing capabilities, with Yiwei providing core hardware and Haohan Deep offering data exchange systems and application validation support [1] - The collaboration aims to establish a long-term joint laboratory to create benchmark cases for space computing and build an open industry ecosystem [1] - Haohan Deep is a pioneer in the field of network visualization and AI forgery detection, with its self-developed deep forgery detection system certified by the China Academy of Information and Communications Technology, covering 22 types of generative model detection capabilities [1] Group 2 - The company's subsidiary, Guorui Zhizhi, achieved a "double excellent" rating in video and audio forgery detection during tests conducted by the China Academy of Information and Communications Technology, a rare honor in the industry [1] - The company has successfully won the bid for the AI forgery detection platform project for Jiangxi Telecom, marking a commercial breakthrough [1] - In the L3 autonomous driving sector, the company, through its subsidiary Zhilian Cloud Security, has developed an integrated security protection system and has participated in the formulation of multiple vehicle networking security standards [1] Group 3 - The company has implemented its vehicle-road-cloud intelligent system 1.0 solution in high-level autonomous driving demonstration areas in Beijing, providing services such as traffic situation analysis and signal light anomaly detection [1] - Over the past year, the company has delivered various systems for autonomous driving demonstration areas in multiple cities, ensuring safety for L3 and above autonomous vehicles [1] - The company is actively exploring emerging business opportunities, although these new businesses currently represent a small proportion of overall performance and have not significantly impacted the company's financial results [1]

Core Viewpoint - The collaboration between Haohan Deep (688292.SH) and Yiwei Aerospace focuses on leveraging each other's strengths in space computing capabilities and data exchange systems, aiming to create a benchmark case in space computing and build an open industrial ecosystem [1] Group 1: Collaboration and Technology Development - The partnership involves Yiwei Aerospace providing core hardware such as onboard servers and computing units, while Haohan Deep contributes its expertise in data exchange and intelligent algorithms [1] - A joint laboratory will serve as a long-term platform for both companies to work together on space computing projects [1] Group 2: AI Forgery Detection Business - Haohan Deep is a pioneer in the field of network visualization and AI forgery detection, with its self-developed digital content deep forgery detection system certified by the China Academy of Information and Communications Technology (CAICT) [1] - The system covers detection capabilities for 22 types of generative models and has achieved "double excellent" ratings in video and audio forgery detection [1] - The company has successfully won a bid for the AI forgery platform project with Jiangxi Telecom, marking a commercial breakthrough [1] Group 3: L3 Autonomous Driving Cloud Business - Through its subsidiary, Zhiliang Cloud Security, the company is building an integrated security protection system for autonomous driving [1] - The company has led and participated in the formulation of multiple vehicle networking security standards under the China Communications Standards Association (CCSA) [1] - The vehicle-road-cloud intelligent system 1.0, based on a "small model + large model + RAG" architecture, has been trialed in high-level autonomous driving demonstration areas in Beijing, providing data intelligence services such as traffic situation analysis and signal light anomaly detection [1] Group 4: Business Outlook - The company is actively exploring emerging business opportunities while noting that these new ventures are still in their early stages and currently represent a small proportion of overall performance [1]