Recently, many users have been sharing their annual data reports, which has sparked some reflections. In the face of an increasingly complex digital environment, security issues are becoming more prominent.

Especially with the emergence of numerous AI-related scams. In traditional models, AI operates within opaque centralized servers, allowing hackers to secretly tamper with operational commands in the background—original "investment instructions" could be replaced with "transfers to attackers." This black box operation leaves significant security vulnerabilities.

In contrast, transparent and verifiable solutions are different. Take Mira as an example; its core philosophy is "Reject the black box, verify authenticity throughout"—by recording transparent on-chain records and verifiable execution processes, every step can be tracked and audited, greatly reducing the risk of covert manipulation. Users can view the complete execution path of instructions in real-time, ensuring they haven't been tampered with by intermediaries.

This shift from "trust in the black box" to "verified transparency" could be an important direction for future AI applications in the crypto space.