After observing various trends in the pan-AI field over the past month, I found an interesting evolution logic: web2AI is moving from centralization to distribution, while web3AI is transitioning from proof of concept to practicality. The two are accelerating their integration.

1) First, let's look at the development trends of web2AI. The local intelligence of Apple and the proliferation of various offline AI models reflect that AI models are becoming lighter and more convenient. This tells us that the carriers of AI are no longer limited to large cloud service centers, but can be deployed on mobile phones, edge devices, and even IoT terminals.

The question arises: how to ensure data consistency and decision credibility among these distributed AI instances when the carriers of AI become highly decentralized?

There is a layer of demand logic here: technological advancement (model lightweighting) → change in deployment method (distributed carrier) → new demand generation (decentralized verification).

2) Looking at the evolution path of web3AI, most of the early AI Agent projects were dominated by MEME attributes, but in recent times, the market has shifted from the hype of simple launchpads to the systematic construction of AI layer1 infrastructure with a lower architecture.

Here is another gradually clearer supply logic: MEME speculation cools down (bubble clearing) → Infrastructure demand becomes apparent (driven by essential needs) → Professional division of labor emerges (efficiency optimization) → Ecological synergy effect (network value).

You see, the "shortcomings" of web2AI in demand are gradually approaching the "strengths" that web3AI can supply. The evolutionary paths of web2AI and web3AI are gradually converging.

Web2 AI is becoming increasingly mature technologically, but lacks economic incentives and governance mechanisms; Web3 AI has innovations in economic models, but its technical implementation lags behind Web2. The integration of the two can complement each other's strengths.

In fact, the integration of the two is giving rise to a new paradigm of AI combining "efficient computing" off-chain and "fast verification" on-chain.

In this paradigm, AI is no longer just a tool, but a participant with economic identity; the focus of resources such as computing power, data, and reasoning will be offline, but a lightweight verification network is also needed.

This combination is clever: it maintains the efficiency and flexibility of offline calculations while ensuring credibility and transparency through lightweight on-chain verification.

Note: Until now, there are always people who think that web3AI is a false proposition, but if you feel it carefully and have a certain forward-looking insight, you will know that with the rapid development of AI, it will never distinguish between web2 and web3, but human bias will.