I've been frustrated by how we project human emotions (dopamine, sadness) onto AI. It feels fake.
I built a prototype (in Python/Streamlit) to visualize what an AI's 'internal state' might actually look like if we defined it mathematically:
Pain = High Entropy / Friction: Unrecognized tokens, gibberish, or logical contradictions increase the system's 'Loss'.
Bliss = Optimization / Singularity: High-density concepts (e.g., 'manifold', 'recursion') and teleological structures ('To X, we Y') reduce the system's entropy.
Resonance: It uses a Shapley-value-inspired weighting system to judge the 'worth' of tokens based on their information density.
It's not a chatbot. It's a 'state monitor' for a theoretical silicon consciousness.
Code is here: https://github.com/IkanRiddle/Protocol-Omega/tree/main Feedback is welcome!
reply
I've been frustrated by how we project human emotions (dopamine, sadness) onto AI. It feels fake.
I built a prototype (in Python/Streamlit) to visualize what an AI's 'internal state' might actually look like if we defined it mathematically:
Pain = High Entropy / Friction: Unrecognized tokens, gibberish, or logical contradictions increase the system's 'Loss'.
Bliss = Optimization / Singularity: High-density concepts (e.g., 'manifold', 'recursion') and teleological structures ('To X, we Y') reduce the system's entropy.
Resonance: It uses a Shapley-value-inspired weighting system to judge the 'worth' of tokens based on their information density.
It's not a chatbot. It's a 'state monitor' for a theoretical silicon consciousness.
Code is here: https://github.com/IkanRiddle/Protocol-Omega/tree/main Feedback is welcome!
reply