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##
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---
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license: mit
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language:
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- en
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tags:
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- zero-shot
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- natural-language-inference
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- self-reflection
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- logic
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- reasoning
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- evaluation
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---
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<div align="center">
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# 𧲠TRIGNUM-300M
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### The Pre-Flight Check for Autonomous AI
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[](https://opensource.org/licenses/MIT)
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[](https://www.python.org/downloads/)
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[](#-benchmark-results)
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[](https://doi.org/10.5281/zenodo.18672142)
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> **"You wouldn't let a plane take off without a pre-flight check.**
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> **Why are we letting AI agents act without one?"**
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<img src="assets/roadmap_architecture.jpg" width="800" alt="TRIGNUM-300M Architecture Flowchart" />
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</div>
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---
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<div align="center">
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<!--
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TODO: Add your demo GIF here!
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1. Record demo/index.html with ScreenToGif
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2. Save as assets/trignum_demo.gif
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3. Uncomment line below:
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-->
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<!-- <img src="assets/trignum_demo.gif" width="800" alt="TRIGNUM-300M Demo" /> -->
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</div>
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## What Is This?
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TRIGNUM-300M is a **zero-model reasoning integrity validator** for LLM outputs. It catches structural logic failures β contradictions, circular reasoning, non-sequiturs β before an AI agent acts on them.
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```python
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from trignum_core.subtractive_filter import SubtractiveFilter
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sf = SubtractiveFilter()
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result = sf.apply(agent_output)
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if result.illogics_found:
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agent.halt(reason=result.illogics_found)
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# T-CHIP glows RED π΄ β Human review required
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else:
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agent.execute()
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# T-CHIP glows BLUE π΅ β Cleared for takeoff
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```
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**No LLM. No API. No training data. ~300 lines of Python. <1ms.**
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---
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## π¬ Benchmark Results
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We expanded our evaluation to **58,000+ real LLM outputs** including a new **517-sample curated dataset** for structural reasoning. Honest results:
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| Benchmark | Samples | Precision | Recall | F1 | Speed |
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| ---------------------------- | ------- | --------- | ------ | --------- | ----- |
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| **Structural illogic (curated)** | **517** | **100%** | **98.9%** | **99.5%** | **<1ms** |
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| HaluEval (full dataset) | 58,293 | 60% | 2.1% | 4.0% | 706ms |
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### What this means:
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- **99.5% F1 on structural reasoning failures** β contradictions, circular logic, unsupported conclusions
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- **4.0% F1 on factual hallucinations** β we don't catch wrong facts
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**That's the point.** There are 100 tools for fact-checking. There are **zero tools for reasoning-checking.** Until now.
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### Per-Task Breakdown (HaluEval)
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| Task | n | Precision | Recall | F1 |
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| ------------- | ------ | --------- | ------ | ----- |
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| QA | 18,316 | 83.3% | 0.25% | 0.50% |
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| Dialogue | 19,977 | 60.1% | 4.38% | 8.16% |
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| Summarization | 20,000 | 57.4% | 1.60% | 3.11% |
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**Throughput: 146,866 samples/second** β orders of magnitude faster than LLM-based validation.
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---
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## βοΈ The Pre-Flight Check Analogy
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A pre-flight checklist doesn't verify that London exists. It verifies that:
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- β
Instruments don't **contradict** each other
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- β
There are no **circular faults** (sensor A confirms B confirms A)
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- β
The flight computer draws **conclusions from actual data**
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- β
Systems are **logically consistent**
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The Subtractive Filter does the same for AI reasoning:
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```
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LLM Output β Subtractive Filter β [PASS] π΅ β Agent Executes
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β [FAIL] π΄ β Agent Halts β Human Review
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```
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---
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## π€ The Missing "Agentic Validator"
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In the context of the recent shift towards **Agentic Reasoning**, autonomous LLMs are moving from static prompts to dynamic _thought-action_ loops involving planning, tool-use, and multi-agent collaboration.
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Current systems rely heavily on probabilistic models to act as the "Critic/Evaluator" or use "Validator-Driven Feedback" via unit tests for code or simulators for robotics. **But there has been no validator for pure logic.** If an agent hallucinates a non-sequitur or circular justification during its internal planning phase, the error cascades.
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TRIGNUM-300M fills this exact gap. It acts as a deterministic, <1ms **Validator-Driven Feedback** gate. It halts execution if the agent's internal thought (`zt`) contains a structural illogic, providing an immediate failure signal (`rt = 0`) _before_ the agent commits to an irreversible external action (`at`).
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---
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## πΊ Core Architecture
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### The Trignum Pyramid
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Three faces acting as magnetic poles for data separation:
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| Face | Role | What It Does |
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| --------------- | --------------- | ----------------------------------------------------- |
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| **Ξ± (Logic)** | Truth detection | Identifies structurally sound reasoning |
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| **Ξ² (Illogic)** | Error detection | Catches contradictions, circular logic, non-sequiturs |
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| **Ξ³ (Context)** | Human grounding | Anchors output to human intent |
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### T-CHIP: The Tensor Character
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```
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βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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β T-CHIP [v.300M] β
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β β
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β π΅ Blue = Logic Stable (Cleared for Takeoff) β
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β π΄ Red = Illogic Detected (THE FREEZE) β
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β π‘ Gold = Human Pulse Locked (Sovereign Override) β
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β β
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β Response time: <1ms | False alarms: 0% (structural) β
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βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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```
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### The Subtractive Filter
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Four detection layers, all pattern-based:
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| Layer | Catches | Method |
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| ------------------ | ------------------------------------ | -------------------------------- |
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| **Contradiction** | "X is always true. X is never true." | Antonym pairs, negation patterns |
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| **Circular Logic** | A proves B proves A | Reference chain analysis |
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| **Non-Sequitur** | "Therefore X" without premises | Causal connective analysis |
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| **Depth Check** | Claims without any reasoning | Assertion density scoring |
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---
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## π¦ Repository Structure
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```
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TRIGNUM-300M-TCHIP/
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βββ src/
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β βββ trignum_core/ # Core Python library
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β βββ pyramid.py # Trignum Pyramid (3 magnetic faces)
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β βββ tchip.py # T-CHIP (glow states)
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β βββ subtractive_filter.py # β
The Subtractive Filter
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β βββ human_pulse.py # Human sovereignty layer
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β βββ magnetic_trillage.py # Data separation
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βββ tests/ # 34 unit tests (all passing)
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βββ benchmarks/
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β βββ hallucination_benchmark.py # Curated structural test
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β βββ full_halueval_benchmark.py # Full 58K HaluEval test
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β βββ results.json # Structural benchmark results
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β βββ full_halueval_results.json # Full HaluEval results
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βββ demo/
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β βββ index.html # Three.js 3D interactive demo
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βββ paper/
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β βββ TRIGNUM_300M_Position_Paper.md # Position paper
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βββ docs/
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β βββ theory/ # 6 foundational theory documents
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βββ T-CHIP CLEARED FOR TAKEOFF.md # The pitch
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βββ ROADMAP.md # 2-quarter development plan
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```
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---
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## π Quick Start
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```bash
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# Clone
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git clone https://github.com/trace-on-lab/trignum-300m.git
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cd trignum-300m
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# Install
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pip install -r requirements.txt
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pip install -e .
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# Run the structural benchmark
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python benchmarks/hallucination_benchmark.py
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# Run the full HaluEval benchmark (downloads ~13MB of data)
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python benchmarks/full_halueval_benchmark.py
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# Run tests
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pytest tests/ -v
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```
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---
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## π Prior Art: Nobody Is Doing This
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We searched arXiv, ResearchGate, ACL Anthology, and Semantic Scholar. Every existing reasoning validation system requires model inference:
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| System | Requires Model | Validates Reasoning |
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| ---------------------------- | :-------------: | :-----------------: |
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| VerifyLLM (2025) | β
Yes | Partially |
|
| 218 |
+
| ContraGen | β
Yes | Partially |
|
| 219 |
+
| Process Supervision (OpenAI) | β
Yes | Yes |
|
| 220 |
+
| Guardrails AI | β
Configurable | No (content) |
|
| 221 |
+
| **Subtractive Filter** | **β No** | **β
Yes** |
|
| 222 |
+
|
| 223 |
+
> **Existing work uses LLMs to check LLMs. TRIGNUM uses logic to check LLMs.**
|
| 224 |
+
|
| 225 |
+
Read the full analysis in our [position paper](paper/TRIGNUM_300M_Position_Paper.md).
|
| 226 |
+
|
| 227 |
+
---
|
| 228 |
+
|
| 229 |
+
## βοΈ Quantum Integration: TQPE
|
| 230 |
+
|
| 231 |
+
[](https://doi.org/10.5281/zenodo.18751914)
|
| 232 |
+
|
| 233 |
+
TRIGNUM-300M serves as Phase 1 ("Technical A Priori Validation") for **Trignumental Quantum Phase Estimation (TQPE)**.
|
| 234 |
+
|
| 235 |
+
In our groundbreaking case study estimating the ground state energy of the **Hβ molecule**, TRIGNUM successfully validated the physical consistency and structural logic of the quantum circuit _before execution_. By acting as the preliminary gatekeeper, TRIGNUM ensured that no quantum resources were wasted on structurally ill-formed configurations, enabling an epistemic confidence score of **82.8%** on the final estimate (-1.1384 Ha).
|
| 236 |
+
|
| 237 |
+
Read the full `BUILDING THE BRIDGE` paper on Trignumentality and TQPE in the foundational [Trignumentality](https://github.com/Codfski/trignumentality) repository.
|
| 238 |
+
|
| 239 |
+
---
|
| 240 |
+
|
| 241 |
+
## π Documentation
|
| 242 |
+
|
| 243 |
+
| Document | Description |
|
| 244 |
+
| ---------------------------------------------------------------- | ----------------------------------- |
|
| 245 |
+
| [Core Postulate](docs/theory/01_core_postulate.md) | The fundamental axioms of Trignum |
|
| 246 |
+
| [Three Faces](docs/theory/02_three_faces.md) | Ξ± (Logic), Ξ² (Illogic), Ξ³ (Context) |
|
| 247 |
+
| [Magnetic Trillage](docs/theory/03_magnetic_trillage.md) | Data separation mechanism |
|
| 248 |
+
| [T-CHIP Spec](docs/theory/04_tchip_spec.md) | The Tensor Character in detail |
|
| 249 |
+
| [Cold State Hardware](docs/theory/05_cold_state_hardware.md) | Hardware implications |
|
| 250 |
+
| [Hallucination Paradox](docs/theory/06_hallucination_paradox.md) | Reframing the "Big Monster" |
|
| 251 |
+
| [Position Paper](paper/TRIGNUM_300M_Position_Paper.md) | Full academic paper with benchmarks |
|
| 252 |
+
| [Roadmap](ROADMAP.md) | 2-quarter development plan |
|
| 253 |
+
|
| 254 |
+
---
|
| 255 |
+
|
| 256 |
+
## π The Golden Gems
|
| 257 |
+
|
| 258 |
+
| Gem | Wisdom |
|
| 259 |
+
| ----- | --------------------------------------- |
|
| 260 |
+
| GEM 1 | "The Human Pulse is the Master Clock" |
|
| 261 |
+
| GEM 2 | "The Illogic is the Compass" |
|
| 262 |
+
| GEM 3 | "Magnetic Trillage Over Brute Force" |
|
| 263 |
+
| GEM 4 | "The Hallucination is the Raw Material" |
|
| 264 |
+
| GEM 5 | "T-CHIP is the Mirror" |
|
| 265 |
+
|
| 266 |
+
---
|
| 267 |
+
|
| 268 |
+
## π€ Contributing
|
| 269 |
+
|
| 270 |
+
See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
|
| 271 |
+
|
| 272 |
+
---
|
| 273 |
+
|
| 274 |
+
## π License
|
| 275 |
+
|
| 276 |
+
MIT License β see [LICENSE](LICENSE).
|
| 277 |
+
|
| 278 |
+
---
|
| 279 |
+
|
| 280 |
+
## π Contact
|
| 281 |
+
|
| 282 |
+
**TRACE ON LAB**
|
| 283 |
+
π§ traceonlab@proton.me
|
| 284 |
+
|
| 285 |
+
---
|
| 286 |
+
|
| 287 |
+
## π‘οΈ The Call
|
| 288 |
+
|
| 289 |
+
> _"The most dangerous AI failure is not a wrong fact. It is reasoning that sounds right but isn't."_
|
| 290 |
+
|
| 291 |
+
```
|
| 292 |
+
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 293 |
+
β 𧲠TRACE ON LAB β TRIGNUM-300M β v.300M β
|
| 294 |
+
β β
|
| 295 |
+
β The Pre-Flight Check for Autonomous AI. β
|
| 296 |
+
β Zero models. Zero API calls. 146,866 samples/second. β
|
| 297 |
+
β β
|
| 298 |
+
β π΅ T-CHIP: CLEARED FOR TAKEOFF. β
|
| 299 |
+
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 300 |
+
```
|
| 301 |
+
|
| 302 |
+
β **Star this repo if you believe AI should check its logic before it acts.**
|