QIIE (Quantum-Inspired Intuition Engine)

Quantum-Inspired Intuition Engine (QIIE)

QIIE is a quantum-inspired inference layer that quantifies intuition ahead of LLMs.
It captures latent tension and subtle mismatch beyond literal meaning, improving decisions and responses.

1. Answering an Unresolved AI Problem

Modern LLMs excel at System 2 (deliberate reasoning) but lack System 1 (intuition).
QIIE externalizes System 1 and adds the ability to read context and detect suspicious cues.

2. Core Technology (The "Secret Sauce")

We apply tensor networks to NLP instead of relying solely on word probabilities.
By leveraging entanglement entropy, QIIE quantifies the invisible tension between words and contexts.
This approach is patent pending.

3. Performance and Efficiency

  • Parameters: ~2.3M (about 1/48 of BERT-base)
  • Inference: ~3.75x faster on CPU
  • Acts as a gate before LLMs to reduce API/GPU cost, suitable for edge and mobile

4. Use Cases and Internal Benchmarks

  • Fraud detection: flags suspicious context like “guaranteed returns” +20.7%
  • Mental health: detects tension and grief instead of surface-level logic +17.5%
  • Abuse handling: detects unstable tone and escalates to a human operator +21.4%

* Improvements measured in internal benchmarks.

5. Architecture and Integration

  • Layer 1 (QIIE): outputs scores for skepticism, emotion, tension
  • Layer 2 (LLM): adjusts system prompts, routing, and tool use based on scores
  • Integrates via API with GPT, Gemini, Claude, and open-source models

6. Scalability and Market Potential

QIIE can serve as a gatekeeper for the emotion AI and conversational AI market, forecast at ~27 trillion yen by 2032.

  • Control of “Ma” (timing): optimize response latency when tension or sadness is high
  • Bond-dimension rapport: scale contextual depth as trust grows
  • Voice and avatar control: use scores to drive TTS tone and expression
  • TRPG and interactive fiction: adapt scenario difficulty based on boredom/confusion
  • Group chat facilitation: detect atmosphere shifts and intervene

QIIE acts as a director for LLMs, separating script generation from performance guidance.

FAQ

Q. Does it use quantum computers?
A. No. We optimize tensor-network mathematics to run on current hardware.

Q. Is “quantum-inspired” just marketing?
A. No. We use MPS/TT bond dimension as a quantitative measure of contextual complexity.

Q. Does it increase LLM cost?
A. It reduces unnecessary LLM calls by acting as a front-end filter.

Q. What about hallucinations?
A. QIIE does not generate text; it outputs scores, so generative hallucinations do not occur.

Q. Can others replicate it?
A. Training stabilization, proprietary annotation data, and know-how form a high barrier to replication.