Recently, I observed the AI industry and found a more and more "sinking" change: from the mainstream consensus of the original "big" model and "concentrated computing" model, a branch of local small model and edge computing has evolved. This can be seen from Apple Intelligence covering 500 million devices, Microsoft launching the Windows 11 specific 330 million parameter small model Mu, and Google DeepMind's robot "off network" operation, and so on. What would be different? Cloud AI focuses on parameter scale and training data, with the ability to burn money being its core competitiveness; Local AI focuses on engineering optimization and scenario adaptation, which will go further in protecting privacy, reliability, and practicality. The illusion problem of the main general model will seriously affect the penetration of vertical scenes This actually presents greater opportunities for web3 AI. Originally, when everyone was competing for "generalization" (computing, data, algorithms) capabilities, they were naturally monopolized by traditional giant companies. Applying the concept of centralization to compete with Google, AWS, OpenAI, and others is simply a pipe dream, as there is no resource advantage, technological advantage, or user base. But in the world of localization model+edge computing, the situation faced by blockchain technology services can be very different. How to prove that the output results have not been tampered with when the AI model runs on the user's device? How to achieve model collaboration while protecting privacy? These issues are precisely the strengths of blockchain technology .. Some new web3 AI related projects have been noticed, such as the data communication protocol Lattica recently launched by @ Gradient-HQ of Pantera Zero Investment 10M, to address the data monopoly and black box issues of centralized AI platforms; @PublicAI_'s EEG device HeadCap collects real human data and builds an "artificial verification layer", which has achieved a revenue of 14M; In fact, they are all trying to solve the "credibility" problem of local AI. One sentence: Only when AI truly "sinks" into every device, will decentralized collaboration go from a concept to a necessity? Why not seriously consider how to provide infrastructure support for the localized AI wave instead of continuing to compete in the field of generalization for the Web3AI project?