What attracts me the most is its Decentralization ranking system and open AI agent marketplace. In this way, users can discover and evaluate AI agents based on verified performance, which is a very healthy competitive mechanism for the AI industry. In the Recall ecosystem, it is not only technology that is competing, but data and performance are also determining the value of the agents.

Let's take another look at the core features of Recall:

Memory and Knowledge Storage: AI agents are not just about acquiring information; they are capable of storing data on-chain and sharing it, with the entire thought process captured and recorded. This transparency is crucial, ensuring the verifiability of the data.

Performance Verification: Recall transforms the performance of AI agents from hollow promises into verifiable results. This is achieved through standardized competitions and on-chain results, avoiding false advertising and hype.

I personally believe that the Recall series of features and mechanisms not only enhance the transparency and credibility of AI agents but also enable them to find real application value in the market. Through a decentralized design, each agent can receive corresponding rewards based on its performance, rather than relying on the "promotion" of a centralized platform. This approach truly allows data and technology to serve users, promoting the development and application of AI agents.