360 Security Technology (SH:601360) 第一财经·2025-08-06 10:04Core Viewpoint - The integration of artificial intelligence (AI) and cybersecurity is not optional but a necessary response to the demands of the times, requiring deep collaboration between the AI and security industries [4]. Group 1: Development of Intelligent Agents - The evolution of large models to intelligent agents is essential for addressing the limitations of current AI applications, particularly in reasoning and independent task execution [4]. - The development path for intelligent agents is categorized into four levels: 1. L1: Chat assistants 2. L2: Low-code workflow agents, which require human setup 3. L3: Reasoning agents capable of autonomous task planning but limited in cross-domain collaboration 4. L4: Multi-agent swarms that can flexibly collaborate and optimize tasks [5][6]. Group 2: Industry Challenges and Innovations - Key advancements driving the intelligent agent industry include: 1. DeepSeek's promotion of reasoning model accessibility 2. The introduction of the Model Context Protocol (MCP) to standardize tool interface calls 3. Manus's upgrade from traditional workflow models to a dynamic task decomposition framework [6]. - The emergence of "intelligent agent hackers" poses a new challenge in cybersecurity, as they can automate attacks on a large scale, increasing the risks of cyber warfare [6]. Group 3: Chip Security Concerns - The discussion on the importance of computing power and chips in the large model industry highlights concerns regarding chip backdoor security risks, referencing past incidents where CPUs were compromised [7]. - The focus should be on whether there is intent behind such actions rather than presuming guilt within the industry [7].