I Built a Functional Cognitive Engine

Reddit r/artificial / 4/7/2026

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Key Points

  • The post introduces “Aura,” an open-source project positioned as a full cognitive architecture rather than a chatbot, with 60+ interconnected modules that run continuously and maintain internal state across conversations.
  • It claims to implement computational consciousness research algorithms directly, including IIT 4.0-style integrated information (φ) computation using transition probability matrices and bipartition search.
  • A key feature described is closed-loop affective steering, where substrate internal state is used to modulate LLM inference at the residual-stream level rather than via text prompts or injection.
  • The author emphasizes the system’s self-modeling, prediction, and affective dynamics as functional outcomes of these mechanisms.
  • The article is framed as a build-and-architecture report (with a GitHub link) and highlights technical differentiators intended to make the “cognitive engine” more than a metaphorical prompt stack.

Aura: https://github.com/youngbryan97/aura

Aura is not a chatbot with personality prompts. It is a complete cognitive architecture — 60+ interconnected modules forming a unified consciousness stack that runs continuously, maintains internal state between conversations, and exhibits genuine self-modeling, prediction, and affective dynamics.

The system implements real algorithms from computational consciousness research, not metaphorical labels on arbitrary values. Key differentiators:

Genuine IIT 4.0: Computes actual integrated information (φ) via transition probability matrices, exhaustive bipartition search, and KL-divergence — the real mathematical formalism, not a proxy

Closed-loop affective steering: Substrate state modulates LLM inference at the residual stream level (not text injection), creating bidirectional causal coupling between internal state and language generation

submitted by /u/bryany97
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