The Integration of Crypto and AI: From Underlying Infrastructure to Application Layer Intelligent Agents

As the wave of artificial intelligence sweeps across the globe, the cryptocurrency sector is also actively exploring paths for integration with AI. This fusion process has evolved from underlying infrastructure to Application Layer agents, showcasing immense innovative potential and transformative possibilities.

Decentralized Computing Power: Initial Attempt

Initially, the combination of Crypto and AI focused primarily on the aggregation of decentralized computing resources. Key features of this stage include:

• Targeting the long-tail market, such as IO.net aggregating distributed GPU resources, reducing the threshold for lightweight inference and model fine-tuning.
• Emphasize flexibility, such as Gensyn activating individual idle GPUs for training through smart contracts.
• Explore new mechanisms, such as Bittensor's introduction of model competition and subnet mechanisms, Render Network's integration of Web2 resources, and ChainML's provision of decentralized model training and inference services.
• Combine DePIN (Decentralized Physical Infrastructure Network), such as decentralized map networks and crowdsourced camera networks, to unleash the performance of edge hardware.

Among them, Bittensor's innovative subnet structure is particularly noteworthy. It modularizes AI service, with each subnet having its own independent community of miners and validators. Users can participate in the ecosystem and earn rewards in various ways, forming a complete token economic model.

However, the attempts at this stage also expose obvious limitations: the pure computing power market is highly competitive, the decentralization performance of the inference layer is insufficient, and there is a lack of Application Layer narrative in the supply and demand matching. Crypto still remains in the role of underlying infrastructure in the AI world, failing to truly connect to the user experience level.

The Rise of AI Agents: Moving Towards the Application Layer

As the decentralized computing power market gradually stabilizes, the exploration of Crypto and AI has shifted from underlying resources to the Application Layer intelligent agent stage. This transformation is marked by the rise of on-chain AI Agents, rekindling the market's expectations for the combination of Crypto and AI.

The development of AI Agents has gone through several stages:

1. Meme Culture Phenomenon: Early projects quickly attracted attention through anthropomorphized and entertaining images.

2. Initial Interaction Ability: AI begins to perform simple tasks on social platforms, transitioning from passive display to active response.

3. Vertical application scenarios: On-chain finance, NFTs, data analysis, social companionship, and other fields have given rise to a large number of specialized intelligent agents.

4. Agent Framework and Execution Protocol: The emergence of modular frameworks such as Eliza, GAME, Rig, and Swarms supports personality modeling, task orchestration, and multi-agent collaboration.

5. The Emergence of Agent Economy: Projects like Virtuals, Eliza, and ARC have established standards for autonomous token issuance, protocol collaboration, and social dissemination through AI Launchpad.

Taking the Virtuals Protocol as an example, it proposes the Agent Commerce Protocol (ACP), allowing agents to autonomously interact, collaborate, and trade, simulating an economy similar to human enterprise ecosystems. Virtuals is incubating agent clusters such as autonomous media communities and autonomous hedge funds based on ACP.

On the other hand, Eliza has restructured the original plugin system through ElizaOS V2, introducing modular task orchestration and multi-agent collaboration, while launching the AUTOFUN platform, which lowers the threshold for AI Token creation.

These developments signify that Crypto+AI is moving from mere resource matching to the construction of on-chain economic systems, and from point-based functions to the reshaping of native finance and social structures.

MCP: Moving Towards Collaboration and Standardization

As the market cools down, the Crypto+AI field is undergoing a profound reshuffle. Against this backdrop, the Model Context Protocol (MCP), as an open standard protocol born for AI applications, has become the new catalyst that best meets the current needs.

MCP provides a unified communication method between large language models and external data and tools, greatly simplifying the development and deployment process of AI applications. The application ecosystem surrounding MCP is rapidly emerging, such as the DARK project in the Solana ecosystem and the SKYAI project on the BNB chain.

MCP opens up new directions for the future of Crypto+AI:

• Multi-Agent Collaboration: Through MCP, agents can collaborate by functional division of labor to complete complex tasks.
• On-chain transaction automation: MCP connects various transactions and risk control agents to achieve safer and more efficient on-chain asset management.
• The rise of InfoFi: Based on MCP, intelligent agents can smartly plan profit paths according to user profiles, promoting new financial models.

The Long Evolution of the Intelligent Body Economy

Looking back at the evolution of Crypto+AI, we can see a long path of deepening functionality and enhancing practicality: from entertainment dialogue agents to tool-based agents, then to trading execution agents and the DeFAI abstraction layer, ultimately advancing towards collective intelligence and multi-agent collaboration.

Every leap brings AI Agents closer to the demands of the real world. In the future, the development of AI Agents will no longer rely on simple narratives, but must be built on a foundation of real practicality. Although this path is long, its potential far exceeds imagination and is expected to bring revolutionary changes to the fields of cryptocurrency and artificial intelligence.