Have you ever thought about AI inference results being verifiable and auditable on the blockchain like financial contracts? Currently, most AI models' inference processes are like black boxes, with only outputs and no trustworthy process records. This means we cannot determine the logic behind the conclusions or put the results on the chain for auditing and trust verification. This is exactly the problem @inference_labs aims to solve. The team has proposed a "Proof of Inference" mechanism based on zero-knowledge proofs and Web3 technology, which runs AI inference off-chain while generating verifiable proofs. This allows each inference output to carry a traceable trust credential, representing a foundational innovation in the world of decentralized AI and intelligent agents. Since its inception, this project has attracted market attention, completing several million dollars in funding, from a $2.3 million pre-seed round to a subsequent $6.3 million strategic investment, with top-tier institutions involved. This reflects the industry's emphasis on verifiable AI infrastructure. The funding aims not only at technological development but also at building cross-chain and cross-protocol trust layers for broad applicability. They have also launched the Proof of Inference system on the testnet and plan to launch the mainnet soon, indicating that verifiable AI infrastructure is moving from theory to deployable reality. Combined with core components like zero-knowledge machine learning protocols and distributed proof systems, this framework could provide a trustworthy foundation for future autonomous agents, decentralized prediction markets, and automated trading agents. But the core question remains: when AI inference can not only be verified on-chain but also be constrained by economic incentive mechanisms, can we truly establish an intelligent ecosystem that is both trustworthy and fair? This is the key reflection where AI trust systems truly come to the surface. @Galxe @GalxeQuest @easydotfunX