Core Insights - Ant Group's research division has gained international academic recognition, with 22 papers published in top-tier journals and conferences since 2025, over 85% of which are classified as CCF A-level, focusing on key challenges in large-scale intelligent collaboration in the AI era [1][2] Group 1: Research Achievements - Ant Group's research addresses three major challenges in the AI era: establishing trust in distributed environments, responding to new security threats posed by AI technology, and enhancing the efficiency of large-scale collaborative decision-making [1] - The research results this year focus on blockchain consensus protocols, AI security, and trusted computing, providing new solutions for large-scale intelligent collaboration [1] Group 2: Blockchain Consensus Protocol - In collaboration with Tsinghua University, Ant Group developed the Rondo protocol, which provides secure, fair, and unpredictable "random numbers" for distributed networks with minimal resource consumption, laying the foundation for efficient collaboration among agents without a trusted third party [1] Group 3: Security Frameworks - To address security risks from deep fakes, Ant Group has designed a new learning framework that decouples features such as texture, color, and edges in image information, significantly increasing the difficulty of solving deep fake issues [2] - Ant Group introduced a "key forgetting" mechanism that allows detection models to ignore common forgery traces and focus on deeper forgery features, enhancing the ability to identify and warn against unknown forgery techniques [2] Group 4: Zero-Knowledge Proofs - In collaboration with East China Normal University, Ant Group achieved two key breakthroughs in the field of zero-knowledge proofs, creating the industry's first verifiable graph data query algorithm and the first verifiable federated learning framework (ZKSL), establishing a trusted protocol layer for inter-organizational agent collaboration [2] - These advancements enable rapid generation of verification proofs, ensuring the trustworthiness and efficiency of collaborative decision-making [2] Group 5: Collaborative Mechanisms - Ant Group has established joint laboratories and targeted research projects with universities such as Tsinghua University, Zhejiang University, and East China Normal University, promoting cutting-edge technology exploration and implementation through industry-academia collaboration [2]

Group 1 - The company, ShenSi Electronics, has achieved significant success in the digital construction sector in Jinan, covering areas such as urban safety, data elements, smart transportation, and low-altitude economy, becoming a core partner in the city's digital transformation strategy [2][5] - The company is leveraging its AI technology and industry resources to enhance urban governance through a comprehensive technology empowerment approach, focusing on smart infrastructure and refined urban management [3][5] - In collaboration with Inspur Smart City Technology Co., the company is expanding its urban safety and emergency rescue capabilities, building an integrated emergency support system based on existing digital construction achievements in Jinan [3][5] Group 2 - ShenSi Electronics is actively participating in the construction of a trusted data space in Jinan, aiming to create a market-oriented data element system that is rule-based, technologically advanced, and secure, which will serve as a model for national data market development [4][5] - The company has also made strides in the low-altitude economy by winning bids for the digital low-altitude flight management service platform, which will address industry challenges and support the development of a low-altitude economic zone in Jinan [4][5] - The projects undertaken by ShenSi Electronics in urban safety, data elements, smart transportation, and low-altitude economy reflect its technological capabilities and alignment with Jinan's development needs, contributing to the city's high-quality economic and social development [5]

Core Insights - The smart home industry faces challenges in information security testing, including limited coverage of traditional tools, low testing efficiency, and difficulty in identifying malicious attacks [1] - The State Administration for Market Regulation has developed a "Heterogeneous Fusion Detection Platform for Smart Home Information Security," which integrates a large model for quality safety to provide comprehensive security testing support for smart appliances, security systems, and wearable devices [1] Group 1 - The platform utilizes over 5,000 historical testing data points and more than 200 standards to train specialized vertical models, enabling the automatic generation and execution of test cases [1] - It includes over 10 standard detection modules covering more than 100 testing items and is compatible with 10 communication protocols, supporting 12 types of smart products for "plug-and-play" testing, improving efficiency by 20 times compared to traditional manual testing [1] - The platform has been piloted in over 10 representative companies, including Haier, Midea, and Xiao Tian Cai, where it identified 12 vulnerabilities with high and medium risks in smart cameras and proposed lightweight end-cloud collaborative security solutions [1] Group 2 - Future plans include adapting the platform for emerging products such as smart robots and low-altitude aircraft, aiming to create a full-chain intelligent service platform for "targeted detection - intelligent early warning - precise disposal" [2] - This initiative seeks to shift the quality safety of smart products in China from a "passive response" to "active prevention" approach, strengthening the foundation for industrial safety development [2]

Core Viewpoint - The 2025 Autonomous Trusted Computing Innovation Forum was held in Beijing, highlighting the importance of trusted computing and cybersecurity in China's digital economy, with Anheng Information becoming a key player in the collaborative innovation mechanism for autonomous trusted computing [1][4]. Industry Overview - The construction of the cybersecurity grading protection system is a significant initiative in China's cybersecurity field, with trusted computing serving as a core technological support for building proactive defense systems and ensuring the controllability of information systems [3][5]. Company Highlights - Anheng Information has extensive experience in the cybersecurity field, contributing to grading protection construction, trusted computing technology research and development, product implementation, and application in various scenarios [3][6]. - The company recently launched the "Grading Protection Evaluation Report Analysis Intelligent Agent," which integrates AI and core standards to create a multi-dimensional intelligent review engine, marking a new era in intelligent report auditing [6]. - Anheng Information was the first company to complete the initial "Enhanced Trusted Execution Environment Basic Capability Special Test" organized by the China Academy of Information and Communications Technology, focusing on privacy computing technologies [6]. - The company aims to build a secure data flow infrastructure and develop trusted data space products, utilizing advanced technologies such as Big Data Trusted Execution Environment (BDTEE), Multi-Party Computation (MPC), and federated learning to ensure reliable, controllable, and traceable multi-party data joint computing processes [6].

Core Viewpoint - The company is developing a trusted AI inference card based on its affiliate Jiangyuan Technology's domestically produced AI computing power chips and its own CCT02 TCM trusted chips, which supports national cryptography algorithms and enhances security against potential threats [1] Group 1 - The trusted AI inference card supports national cryptography algorithms SM2/3/4 [1] - It features static boot measurement capabilities to prevent software-related attacks and protect sensitive information [1] - The product complies with the GM/T 0012-2020 trusted computing standard [1]

Core Insights - The collaboration between Zhongke Shuguang and China Mobile aims to address the inefficiencies in data storage and computing power allocation in the "East Data West Computing" initiative [1][2] - The current investment ratio in computing power versus storage in China is approximately 40:1, compared to around 10:1 in foreign markets, indicating a significant imbalance [1][2] - Shuguang Storage has developed a unified scheduling platform to enhance data flow and management across different data centers, addressing key challenges in data visibility, organization, and utilization [3][4][5] Group 1: Industry Challenges - The primary bottleneck in AI infrastructure is not computing power but rather the foundational data layer, which is often fragmented and incompatible across different systems [3][4] - Data centers face issues such as lack of visibility into data assets, inefficient data flow, and high latency in accessing stored data, particularly in the context of the "East Data West Computing" strategy [4][5] - The rapid growth of AI applications has increased the performance requirements for data storage systems, necessitating advancements in IOPS and bandwidth capabilities [6][12] Group 2: Technological Advancements - Shuguang Storage has transitioned from being a follower to a solution provider in the storage technology space, leveraging over 21 years of R&D to establish a competitive edge [2][10] - The company has achieved global recognition for its centralized storage products, ranking first in the SPC-1 international benchmark for storage performance [2][10] - The development of a unified storage scheduling platform is seen as essential for facilitating data flow across heterogeneous and geographically dispersed data centers [7][8] Group 3: Strategic Collaborations - The partnership with China Mobile was initiated to address specific business needs and to support the national strategy of optimizing resource utilization in the West [7][8] - Shuguang Storage's extensive self-research capabilities position it as a key player in solving complex data flow challenges, which many other vendors struggle to address [8][9] Group 4: Future Outlook - The entry barriers for AI applications are expected to lower with advancements in technology, but new challenges related to privacy and data security will emerge [12][13] - Enhancing GPU resource utilization is critical for reducing AI operational costs, with Shuguang Storage's innovations in data transfer efficiency playing a pivotal role [13][14] - The company's focus on "storage-computing synergy" aims to optimize the interaction between storage systems and GPU resources, significantly improving processing speeds and efficiency [14]