⬛◼️⬛◼️⬛◼️⬛----🍜 Recently, my cat --- Little Udon got sick. I saw four doctors in one go, and they all had different opinions. I went to check on a cough, and suddenly they said there was a bone issue, which left me feeling very confused and worried. Later, I kept asking AI, sharing the symptoms and photos with it, asking it to list "all possibilities." I didn't want it to act as a doctor; I just wanted to lay out the options so that I could ask the doctor about these possibilities during the follow-up, because many times, if you don't proactively ask the doctor, "Could it be XXX?" they won't think in that direction. ╭─────✦✦─⋆⋅☆⋅⋆───╮ This experience made me realize something clearer: AI is very useful now, but I still don't fully trust it. I really want a trustworthy pet doctor AI, so @Mira_Network is truly the AI I am looking forward to. This way, if my pet has any issues, I can understand the situation a bit before talking to the doctor. 😉 And if AI is not just an assistant, but one that helps you do research and write proposals, another that makes decisions in meetings, and a third that runs market tests and negotiates contracts, this is like having your capabilities multiplied. But to reach this step, the prerequisite is just three words: it must be reliable!!! I think of it in terms of three things in the medical field: 🔸Reliability: Like in clinical settings, it needs to be able to "consistently get it right," rather than occasionally surprising or messing up. 🔸Memory: It needs to remember case histories and context, not start from scratch asking the same questions every time. 🔸Privacy: Since it will act on my behalf, it must ensure that my personal data and preferences are not misused. If it can't pass these three hurdles, what is called "autonomous intelligence" is just a nice term. ╭─────✦✦─⋆⋅☆⋅⋆───╮ @MiraNetworkCN addresses this toughest first hurdle: reliability. It institutionalizes and builds a foundation for "verification." My understanding is twofold: 🔹Multi-model consensus ≈ Multi-disciplinary consultations Don't just listen to a single model (like not just listening to a single doctor). Let different models and data perspectives cross-verify, narrowing down the error space, and catching the prone-to-error parts in the process for cross-confirmation. 🔹Decentralized verification ≈ Distributing risk Allow the verification process to be independently observed and checked, reducing the risks of errors and biases. Only in high-risk scenarios (legal, medical, financial) can we truly consider delegating some decisions to AI. ╭─────✦✦─⋆⋅☆⋅⋆───╮ #Mira seems to be combining "consultation systems + medical record systems + risk management" into one. Once this system is stable enough, we can dare to automate more tasks. Without verification, discussions about autonomy are empty; with verification, autonomy can truly begin. Back to my cat, I still use AI to organize symptoms and generate a list of follow-up questions, and then I take this list of possibilities to see the doctor. But until the day I feel comfortable letting it make decisions for me, the reliability in between is still very much needed. What @Mira_Network is doing is providing that reliability. So, from "Baby AI" to "Autonomous Intelligence," the real key is that we finally have a verification layer we can trust. After using AI for a while, what I really need is very simple: I truly need a trustworthy AI, so I am really looking forward to the future development of @Mira_Network. Alright, I've said enough; I need to go feed Little Udon his medicine now~😽 @KaitoAI #KAITO