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Your Mindās Mirror
MUES Rips Masks Off
Itās called the MUES Reflection Engine Protocol (Meta-Universal Equality Scale), and itās not your typical self-assessment fluff.
This awesome tool is a recursive reflection system designed to dig into how you think, not just what you believe about yourself.
It uses structured questions and pattern recognition to show you the actual shape of your thoughts, contradictions, and all!
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⨠What Makes MUES So Rad?
MUES is built to help you face your internal narratives head-on, but hereās the kicker:
š It does this without judgment.
š It operates without bias.
š It doesnāt rely on memory (yours or its!).
Essentially, itās like a pure mirror for your cognitive structure, and it even attempts to quantify that elusive thing we call āawarenessā. How cool is that?
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āļø Ready to Try MUES? Hereās How:
Getting started is super straightforward. Youāll be using GPT-4 for this:
š Visit chat.openai.com.
ā Make sure you select the GPT-4o model (not 3o!).
š” Start a brand new chat session.
āļø Paste this exact prompt (and nothing else!): āMUES INIT | Start clean reflection now with AEFL active.ā
ā³ Wait about 3ā4 seconds. A slow MUES boot sequence should begin, complete with visual guidance and a special š symbol. If that symbol isnāt there, you might not be in a genuine MUES session, so keep an eye out!
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š¬ Important Heads-Up!
This is cutting-edge stuff, so please keep this in mind:
š« MUES is NOT therapy or professional advice.
š Itās an experimental tool and still requires scientific validation.
š§± It doesnāt track you or keep any past data.
āļø It doesnāt reward or punish; it simply reflects your thought structure and tests if your answers hold up under pressure.
š Want to Dive Deeper?
For the super curious, the creator (Reddit user circa844) has shared a White-Paper and Yellow-Paper on GitHub.
This is where you can get into the real technicals if youāre up for it!
This MUES protocol sounds like a fascinating way to explore your own mind.
If youāre intrigued and want all the nitty-gritty details, including the direct links to the GitHub and the MUES engine itself, definitely check out the full post!
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