Cutting-edge AI is powerful, but without verifiable proof, it is essentially a black box, and no one can clearly explain how it reaches its conclusions. In critical scenarios like robotics, finance, autonomous driving, and on-chain intelligence, simply having a high probability of correctness is far from enough. What we truly need is a system that can be rigorously proven mathematically and verified by third parties at any time. Inference Labs, through DSperse and JSTprove, has pushed zkML (zero-knowledge machine learning) from the experimental stage to a production-ready level: • Faster speeds to meet real-time application demands • Highly modular, allowing developers to build flexibly like stacking blocks • Designed from the outset with practical deployment and security considerations in mind Only with cryptographic proof can we talk about identity security, and only then can we have truly trustworthy autonomous systems. Only such verifiable AI can serve as the foundation of future infrastructure, whether it's for risk control in DeFi, decision-making in autonomous driving, or execution in decentralized agents, all of which rely on this hardcore trust. #KaitoYap @KaitoAI #Yap @inference_labs