Analysis of Investment Directions in the AI+Crypto Track

In recent years, the rapid development of artificial intelligence and blockchain technology has made AI+Crypto an investment hotspot. The decentralized and highly transparent characteristics of blockchain complement AI systems, bringing new opportunities to the industry.

Industry experts believe that the application of AI in conjunction with blockchain can be mainly divided into four categories: as application participants, interfaces, rules, and objectives. From the perspective of productivity, the role of AI in Crypto can be considered from three directions: optimizing computing power, algorithms, and data.

According to the levels of AI applications, the participation directions of Crypto technology can be divided into the infrastructure layer, execution layer, and application layer. For example, zkML technology combines zero-knowledge proofs and blockchain to provide secure and verifiable solutions for AI agent behavior. AI has also shown potential in data processing, automated development, and on-chain transaction security at the execution layer. In the application layer, AI-driven trading bots, predictive analytics tools, and others play important roles in the DeFi space.

This article will explore the key directions and future challenges of the AI + Crypto sector from the perspective of medium to long-term investment strategies.

Key Directions in the AI Track

1. zkML direction

zkML technology combines zero-knowledge proofs and blockchain to provide a secure and verifiable solution for monitoring and constraining AI agent behavior. It can prove that AI has performed specific tasks while protecting privacy, pioneering new methods for verifying private data using public models or verifying private models using public data. This makes smart contracts more flexible and adaptable to a wider range of application scenarios.

Typical projects include:

• Modulus Labs: Developing on-chain AI application examples, such as the RockyBot trading robot, etc.
• Giza: A protocol for deploying AI models on the chain
• Zkaptcha: Provides CAPTCHA services for smart contracts, creating solutions resistant to witch attacks.

2. Data Processing Direction

Mainly refers to breakthroughs of AI at the execution layer, including:

a. AI and On-Chain Data Analysis: Using large models and deep learning algorithms to mine blockchain data for insights.

b. AI and Automated dApp Development: Using AI development tools to help developers quickly write smart contracts and automatically correct errors.

c. AI and On-Chain Transaction Security: Deploying AI agents on the blockchain to enhance the security and credibility of AI applications. For example, the SeQure platform utilizes AI for real-time monitoring and analysis to defend against malicious attacks.

3. AI + DeFi Direction

1. AI-driven trading bots: Quickly and accurately execute trades, analyze market data to make decisions.

2. Predictive Analysis: Provides reliable forecasts of market trends and price movements.

3. AMM Liquidity Management: Smartly adjust the liquidity range to optimize the efficiency of automated market makers.

4. Liquidation protection and debt position management: Implement intelligent liquidation protection strategies by combining on-chain and off-chain data.

5. Complex DeFi Structured Product Design: Relies on financial AI models to design treasury mechanisms, increasing product flexibility.

4. AI + GameFi direction

1. Game strategy optimization: AI learns player habits and adjusts game difficulty and strategy.

2. Game Asset Utilization Management: Help players efficiently manage and trade virtual assets.

3. Enhance game interaction: Create intelligent responsive NPCs to improve game immersion.

Investment Strategy Time Dimension

• Short-term: Focus on conceptual AI applications and memes, seizing hot opportunities brought by the upgrades of Web2 AI companies.

• Medium term: Focus on the combination of AI Agent and Intent, which may break through the traditional blockchain model of ledger + contract.

• Long-term: The combination of AI and zkML technology may have a profound impact on the Crypto field.