AI+Web3: Towers and Squares

Summary

1. Web3 projects with AI concepts have become targets for capital attraction in both primary and secondary markets.

2. The opportunities of Web3 in the AI industry are reflected in: utilizing distributed incentives to coordinate long-tail supply, covering data, storage, and computation; while establishing a decentralized market for open-source models and AI agents.

3. AI is primarily applied in the Web3 industry for on-chain finance ( cryptocurrency payments, trading, data analysis ) and assisting development.

4. The utility of AI + Web3 is reflected in their complementarity: Web3 is expected to counteract AI centralization, while AI is expected to help Web3 break out of its circle.

Introduction

In the past two years, AI has developed rapidly, with ChatGPT igniting a wave of generative AI, which has also impacted the Web3 field. With the support of AI concepts, financing for Web3 projects has significantly increased. In the first half of 2024, 64 Web3+AI projects completed financing, with Zyber365 obtaining $100 million in Series A funding. The secondary market is even more prosperous, with the total market value of the AI sector reaching $48.5 billion.

The combination of AI and Web3, filled with hot money, trends, and future fantasies, is inevitably seen as a marriage orchestrated by capital. This article attempts to examine this pattern: how Web3 plays a role in the AI technology stack, and what new opportunities AI can bring to Web3?

1. Opportunities of Web3 under the AI Stack

1. Base Layer: The Airbnb of Computing Power and Data

Hash Rate

One of the high costs of AI is the computational power and energy required for training and inference. The Web3 DePin( decentralized physical infrastructure network) projects aim to address this issue, such as io.net, Aethir, and others. The logic is to allow contributors with idle GPU resources to provide computational power in a decentralized manner, forming a market similar to Airbnb.

Features:

• Gather idle GPU resources
• Long-tail market oriented towards AI computing power
• Decentralized Ownership

Data

Data is the foundation of AI. Web3 solutions for AI data needs include:

• Data Collection: Projects like Grass and Vana allow users to participate in data value creation.
• Data preprocessing: Consider adding a data annotation stage for Grass and OpenLayer.
• Data Privacy and Security: such as Super Protocol(TEE), BasedAI(FHE), Reclaim Protocol(zk), etc.
• Data Storage: 0g.AI designs storage solutions for high-performance AI requirements.

2. Middleware: Model Training and Inference

Open Source Model Decentralized Market

Web3 proposes the possibility of decentralized open-source model markets, such as projects like Bittensor and ORA.

Verifiable reasoning

Web3 solutions for the AI inference "black box" problem include zkML, opML, TeeML, and others.

3. Application Layer: AI Agent

Opportunities for AI Agents brought by Web3:

• Decentralization: such as projects like GaiaNet, Theoriq, etc.
• Cold start: Projects like Virtual Protocol and Spectral help AI Agent projects secure early funding.

II. How AI Empowers Web3

1. AI and On-Chain Finance

Potential Applications of AI Agents in On-Chain Finance:

• Information Collection and Prediction
• Asset Management
• Optimize financial experience

The application of AI in on-chain transaction security, such as SeQure and AI-powered Sentinel.

2. AI and On-chain Infrastructure

The application of AI in on-chain data analysis, such as Web3 Analytics, MinMax AI, etc.

AI-assisted Web3 development, such as one-click deployment platforms like Clanker and Spectral.

The application of AI in smart contract auditing, such as Fuzzland.

3. AI and the New Narrative of Web3

AI brings new possibilities to Web3 fields such as NFT, GameFi, and DAO.

III. The Significance of the Combination of AI and Web3: Towers and Squares

The combination of AI and Web3 is like the relationship between a tower and a square. The centralization trend of AI builds a tall tower, while Web3 attempts to create new possibilities in the square. The inherent properties of Web3 can enhance AI systems:

• Smart contracts implement transparent rule execution
• Token economy coordination participant behavior
• Decentralized governance promotes information censorship

AI also brings new vitality to Web3, lowers the barrier to use, and attracts more users.

Although AI and Web3 have different starting points, their ultimate goal is to enable machines to better serve humanity. We look forward to seeing the future brought about by the combination of the two.