AI+Web3: Towers and Square

In the past two years, the development of AI has been like pressing the fast-forward button. This butterfly effect sparked by ChatGPT has not only opened a new world of generative artificial intelligence but has also created a huge wave in the Web3 field.

With the backing of AI concepts, there has been a noticeable boost in financing in the cryptocurrency market, which has slowed down. According to statistics, 64 Web3+AI projects completed financing in the first half of 2024, among which the AI-based operating system Zyber365 raised 100 million dollars in Series A funding.

The secondary market is more prosperous. According to Coingecko, in just over a year, the total market value of the AI sector has reached $48.5 billion, with a 24-hour trading volume close to $8.6 billion. The significant advancements in mainstream AI technology have brought obvious benefits; after the release of OpenAI's Sora text-to-video model, the average price of the AI sector increased by 151%. The AI effect has also spread to the cryptocurrency fundraising sector Meme: the first AI Agent concept MemeCoin - GOAT rapidly gained popularity and was valued at $1.4 billion, sparking an AI Meme craze.

The research and topics related to AI+Web3 are equally hot, ranging from AI+Depin to AI Memecoin, and currently to AI Agent and AI DAO, with the speed of new narratives being overwhelming.

The combination of AI and Web3, filled with hot money, trends, and future fantasies, is inevitably seen as a marriage arranged by capital matchmaking. It is difficult for us to discern whether beneath this glamorous exterior lies a playground for speculators or the eve of a transformative outbreak.

To answer this question, a key consideration is: will it get better with the other party? Can we benefit from the other party's model? This article attempts to examine this pattern from the shoulders of predecessors: how Web3 plays a role in various aspects of the AI technology stack, and what new vitality AI can bring to Web3?

What Opportunities Does Web3 Have Under the AI Stack?

Before we delve into this topic, we need to understand the technology stack of AI large models:

1. Base Layer: A shared platform for computing power and data

In terms of computing power, one of the highest costs for AI currently is the computing power and energy required for training models and inference. For example, Meta's LLAMA3 requires 16,000 NVIDIA H100 GPUs for 30 days to complete training, with hardware investments ranging from $400 million to $700 million, consuming 1.6 billion kilowatt-hours of electricity per month, and energy expenses nearing $20 million.

This is precisely the area where Web3 intersects with AI the earliest - DePin( decentralized physical infrastructure network). Its main logic is: the platform allows owners of idle GPU resources to contribute computing power in a permissionless decentralized manner, improving the utilization of GPU resources through an online marketplace similar to Uber or Airbnb, providing users with more cost-effective efficient computing resources.

In terms of data, Web3 solutions are reflected in data collection, preprocessing, privacy and security, storage, and other aspects. For example, Grass is a decentralized data layer and network where users can contribute bandwidth by running nodes to capture real-time internet data and earn rewards. Vana introduces the concept of data liquidity pools, allowing users to upload private data to specific pools and flexibly authorize third parties to use it.

2. Middleware: Model Training and Inference

Web3 proposes the possibility of a decentralized open-source model market, which involves tokenizing the models themselves, reserving a certain proportion of tokens for the team, and directing part of the future revenue streams to token holders. For example, the Bittensor protocol establishes an open-source model P2P market, composed of multiple "subnets," where resource providers compete with each other to meet the specific objectives of the subnets.

3. Application Layer: AI Agent

The current focus of AI development has shifted from model capabilities to AI Agents. The decentralized characteristics of Web3 enable the Agent system to be more distributed and autonomous, establishing incentive and penalty mechanisms for stakers and delegators through PoS, DPoS, and other mechanisms, thereby promoting the democratization of the Agent system.

How does AI empower Web3?

1. AI and On-chain Finance

AI Agents are seen as the future of on-chain finance, with potential scenarios including: information gathering and forecasting, asset management, and optimizing financial experiences. AI wallets like Bitte and Wayfinder attempt to enable users to command Agents to perform various on-chain operations through interfaces similar to ChatGPT.

2. AI and On-chain Infrastructure

AI technology plays an important role in on-chain data collection and analysis, with tools such as Web3 Analytics and MinMax AI providing AI-based on-chain data analysis. In development, AI can assist in the generation, verification, and testing of smart contracts, lowering programming barriers. For example, Clanker allows users to launch tokens with one click on social platforms.

3. AI and the New Narrative of Web3

Generative AI brings new possibilities for the new narrative of Web3. In the NFT field, AI can generate unique artworks and characters; in GameFi, AI is expected to improve the efficiency of game content production; in the DAO aspect, AI can help track community interactions and record contributions.

The Significance of AI and Web3 Integration: Towers and Squares

AI is essentially an industry of scaling and centralization, and this technological revolution pushes tech companies to higher levels. As towers rise higher and decision-makers behind the scenes shrink in number, the centralization of AI brings many hidden dangers, which is precisely the issue that Web3 hopes to address.

The inherent properties of blockchain enhance AI systems and bring new possibilities: achieving transparent automatic execution of rules through smart contracts; coordinating participant behavior through token mechanisms; and decentralized governance fosters questioning of information sources, cultivating a more informed and empowered society.

The development of AI has also brought new vitality to Web3. When Web3 was questioned as a niche self-indulgence, the addition of AI has provided a foreseeable future: a more stable scale of user base, more innovative business models and services.

We live in a world where "towers and squares" coexist. 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 of AI + Web3.