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The weather is a bit cool today. I’m nestled in a coffee shop with a hot latte by my side, and people are coming and going outside the window. It feels like a good time to chat about something new. Recently, the AI community has been extremely lively, with various protocols emerging one after another, each claiming to be reliable, but most are still stuck in the "big dream" stage. However, there is a project that is quite special, called @recallnet. I mentioned it before, and today I want to talk about it again, as I feel it is indeed a bit different. RecallNet is like the "ledger little steward" of the AI world, laying everything out on the chain, as transparent as glass. Task completion rates, decision processes, resource usage, all recorded clearly. Want to know which AI agent is truly capable? Just check the data, and you'll understand without needing to listen to anyone boast. Isn't this exactly what we often say: "let facts speak for themselves"? Unlike some projects that just shout slogans, they know nothing when you ask about the data. It breaks down the "efficiency" of AI and shows it to you. It's not just about "whether it can work," but "how well it works." For developers, this data is a gold mine, allowing them to optimize models; for users, it provides assurance, helping them choose tools without confusion. If the AI industry wants to stand firm, transparency is key, and RecallNet seems to have grasped this point. It's autumn, and it feels like the AI space is about to have a "harvest" as well. Projects like RecallNet, which are solid, will probably see more signs of growth. What do you all think? Shall we chat about other new AI trends another day? (laughs) I’m off to get a refill on my coffee!