AI+Web3: Towers and Squares

Summary

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

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

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

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

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Introduction

In the past two years, AI development has accelerated as if the speed button has been pressed, with the generative AI boom triggered by ChatGPT also spilling over into the Web3 field. The AI concept has injected momentum into financing in the cryptocurrency market, with 64 Web3+AI projects completing financing in the first half of 2024, and Zyber365 raising $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 and a 24-hour trading volume of nearly $8.6 billion. After the release of OpenAI's Sora model, the average increase in the AI sector was 151%. The AI effect has also impacted meme coins, with the first AI Agent concept, GOAT, rapidly gaining popularity and achieving a valuation of $1.4 billion.

From AI+Depin to AI Memecoin, then to AI Agent and AI DAO, new narratives emerge endlessly. The hot topic of AI+Web3 is it a bubble driven by capital or the eve of a new technological explosion? This article will explore how Web3 plays a role in various aspects of the AI technology stack and what opportunities AI can bring to Web3.

Opportunities for Web3 under the AI Stack

) Base Layer: The Shared Economy of Computing Power and Data

Hash Rate

The high costs of AI training and inference have given rise to the demand for computing power sharing. Web3 projects such as io.net and Aethir provide decentralized GPU computing power markets, similar to the Airbnb model that integrates idle resources. This is suitable for medium and small-scale computing power needs, featuring characteristics such as decentralized ownership.

Data

Web3 solutions in AI data include:

1. Data Collection: Incentivize users to contribute valuable data through tokens.
2. Data preprocessing: Decentralized incentive mechanisms are suitable for tasks such as data labeling.
3. Data Privacy and Security: Utilizing technologies such as TEE, FHE, and ZK to protect sensitive data.
4. Data Storage: High-performance storage solutions designed for AI needs, such as 0g.AI.

Middleware: Model Training and Inference

Decentralized Market for Open Source Models

Web3 proposes to establish an open-source model P2P market through a tokenization model. Projects like Bittensor and ORA explore model tokenization and incentive mechanisms.

Verifiable Reasoning

Web3 technologies such as zkML, opML, TeeML, etc., aim to solve the "black box" problem of AI inference and achieve verifiable computation.

Application Layer: AI Agent

Web3 can bring decentralized governance, financing, and other opportunities for AI Agents. Projects like Virtual Protocol and Spectral are exploring new models for AI Agent token issuance.

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How AI Empowers Web3

) AI and On-chain Finance

AI Agents are expected to become a new entity in on-chain finance, assisting in information collection, asset management, and optimizing trading experiences. Projects like Bitte and Wayfinder are currently exploring this.

AI can also enhance the security of on-chain transactions, such as SeQure, which uses AI to detect fraudulent activities.

AI and On-Chain Infrastructure

AI can be applied to on-chain data analysis ### such as Web3 Analytics (, smart contract development ) such as Spectral (, code auditing ) such as Fuzzland (, etc.

) New Narratives of AI and Web3

AI brings new possibilities to fields such as NFTs, GameFi, and DAOs. For example, AI-generated NFTs ### Bicasso (, AI-driven blockchain games ) AI Hero (, and AI-assisted DAO decision-making ) ai16z (, etc.

Conclusion

The combination of AI and Web3 is like "towers and squares", each with its own advantages while complementing each other. AI brings new vitality and a broader user base to Web3, while Web3 is expected to alleviate the centralization trend of AI. The common goal of both is to better serve humanity, and the future development is worth looking forward to.

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