The “Unified Neural Network” and “AI-Catalyzed Fourth Generation Internet” mark a paradigm shift from “information connection” to “autonomous collaboration”. At its core lies the reconstruction of network architecture, interaction models, and productivity logic through AI Agents, enabling deep integration of human-machine-material intelligence. Below we analyze the technological drivers, architectural transformations, implementation scenarios, and future challenges:
I. Core Characteristics of Web4: AI Agent-Driven Unified Network#
Paradigm Shift: From Human Operation to Agent Execution
- Traditional internet relies on active user operations (e.g., search, click), while Web4 uses AI Agents as hubs to establish an “autonomous execution + human supervision” model. Users transition from operators to decision-makers, with Agents actively decomposing tasks and coordinating resources through “LLM + memory systems + tool invocation + planning capabilities”.
- Data: 2021-2024 saw AI contribute 48% of global internet traffic growth; China’s daily token consumption reached 10 trillion in 2025 (100x YoY), confirming AI as the traffic driver.
Network Architecture Reconstruction: Edge-Centric, High Uplink, Multimodal Fusion
- Traffic restructuring: Uplink traffic share jumped from 15% to 50%; edge node traffic increased from 15% to 65%.
- Hyper-convergence: Academician Wu Jiangxing’s “Five Unifications” vision integrates human-machine-material intelligence, space-air-ground networks, computing-storage-communication-sensing, security-information, and smart O&M, transforming networks into multifunctional platforms.
II. Technological Pillars: How Agents Enable “Unified Neural Networks”#
Three Evolutionary Stages of Agents
- Single Agent: Domain-specific (e.g., medical imaging, industrial inspection)
- Multi-Agent Collaboration: Cross-domain coordination via centralized orchestration (e.g., smart city traffic-public service integration)
- Internet of Agents (IoA): Open heterogeneous collaboration through blockchain and federated learning, serving as human “digital avatars”.
Generative Networks and Intrinsic Security
- Polymorphic Intelligent Network Environment (PINE): Dynamically generates scenario-optimized network modalities via AI orchestration.
- Intrinsic Security Architecture: Dynamic Heterogeneous Redundancy (DHR) converts threats like data poisoning into quantifiable, mitigatable risks.
III. Application Scenarios: From Enterprise Efficiency to Consumer Accessibility#
Enterprise (2B): Embedded Agents Reshape Productivity
- Drug Discovery: End-to-end Agent collaboration reduces R&D cycles
- Smart Manufacturing: Gartner predicts 33% of enterprises will adopt Agentic AI by 2028
- Financial Risk Control: Mortgage approvals accelerate from 45 days to 72 hours
Consumer (2C): AI Agents as a Service
- Complex Task Delegation: Travel planning via voice command
- Device Revolution: Agent-embedded phones/AR glasses extend perception
- Health Management: Personal health Agents provide real-time interventions
IV. Challenges & Breakthrough Paths#
Technical Bottlenecks
- Compute Energy: AI consumes 2%-3% of US energy, nearing critical 6% threshold
- Coordination: Requires standardized protocols and trust frameworks
Social Acceptance & Ethics
- Accountability: Humans retain ultimate responsibility for Agent decisions
- Privacy: Federated learning ensures data sovereignty compliance
V. Future Vision: Testbeds & Social Surplus Creation#
- National Testbeds: Wu Jiangxing’s team proposes “Hyper-Converged Network & Intelligent Computing Testbeds” to validate architectural theories.
- Social Surplus: Microsoft CEO’s theory posits AI must penetrate economic fundamentals (e.g., $18B annual healthcare savings) to prove net value creation.
Conclusion#
Web4’s essence is the unification of “neural centers” and “intelligent limbs”:
- Neural Centers: Generative networks dynamically orchestrate resources
- Intelligent Limbs: Agents operate autonomously within permission frameworks
As Wu Hequan stated, this decade is critical for China to lead in asymmetric tracks like polymorphic networks and intrinsic security. This transformation will redefine not just technology, but human collaboration paradigms—ushering in a “social surplus”-driven civilization.