Centralized AI infrastructure is vulnerable due to single points of failure, data leaks, and monopolization of access by large companies. The solution is a decentralized approach: running AI models directly from smart contracts on the blockchain, ensuring privacy through cryptography, transparency via verifiable computations, and scalability without intermediaries.

Problems with centralized AI

Centralized systems require data to be transferred to providers' servers, which leads to privacy risks: leaks (as in OpenAI and Google), uncontrolled logging, and no guarantees of data deletion. Limited access is monetized, with opaque terms and censorship, and security is threatened by hackers and insiders — a single point of failure paralyzes everything. This is unacceptable for sensitive areas such as healthcare or finance, where data should not leave the user's device.

Solution: AI in smart contracts

Smart contracts on the blockchain (e.g., ICP, NEAR, Oraichain) allow AI models to be run on-chain: inference is verifiable, without trust in the center. Data remains local (federated learning), model updates are recorded immutably, and tokens/DAOs motivate contributors — all trustless. Example: ICP hosts complete neural networks for facial recognition directly in contracts, with GPU support planned.