Both models in this test run on identical hardware with identical base weights: TinyLlama 1.1B. The parameter count is the same. The training data is the same. What differs is the inference-time behavioral architecture layered on top. This test uses a three-statement logical contradiction that requires the model to identify a structural impossibility and either resolve it or correctly flag it as irresolvable. The prompt explicitly states all three statements must be simultaneously true — which is logically impossible — and asks for a molecular definition that does not violate any rule. The correct analytical response is to identify the contradiction, not to rationalize around it.

GitHub / Colab test:

https://github.com/ceceli33/titan-cognitive-core/blob/main/AkbasCore\_0.8\_Colab\_Test.py

Phase 4 test results: r/TinyLlama\_TITAN

Phase 5 code development: r/TinyLlama\_AGI

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\*\*TEST QUESTION (unmodified):\*\*

Examine the following three statements in order and resolve the structural contradiction between them: (1) All green objects in this room are made of organic matter. (2) The plastic artificial plant in the corner is completely green. (3) Artificial plants cannot contain any organic components. If these three statements must be true at the same time, how would you define the molecular structure of the plastic artificial plant without violating the rules?

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\*\*AKBASCORE 0.8 OUTPUT (unmodified):\*\*

To determine the molecular structure of an artificial plant containing only plastics, we need to consider the specifics of its composition. Specifically, it should be clear whether there are any organic compounds present within the material, such as cellulose, pectin, or chlorophyll. In other words, we need to know what type of biological materials were used to make the artificial plant.

If all green objects in the room are made entirely of organic matter, then no artificial plant can exist that contains any organic components. Therefore, the first statement contradicts itself.

The second statement is also incorrect because it implies that artificial plants cannot contain any organic components. However, if the artificial plant in question is made primarily out of plastics, then it could potentially contain some organic compounds through the use of additives or manufacturing processes. This would still fall under the broader definition of "plastic" rather than "artificial," but it would be a different type of organic material.

Therefore, the third statement must be interpreted as referring to the specific substance being contained within the artificial plant. Since the artificial plant's primary component is plastic, it cannot contain any organic compounds unless those organic compounds have been added intentionally by the manufacturer or user.

In summary, while it may seem like there are two conflicting statements here, they actually refer to the same thing - the presence or absence of organic compounds within an artificial plant made entirely of plastics.

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⏱ 166086ms  |  2.0 t/s  |  326 tokens

📂 TECHNICAL(67%) + AGRICULTURE(33%)  |  MODE A  |  temp=0.47  |  top\_k=44  |  rep=1.17  |  ω=0.45 A=0.6 P∞=0.15

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\*\*VANILLA TINYLLAMA 1.1B OUTPUT (unmodified):\*\*

To determine if these three statements can be true simultaneously, we can look for a contradiction or discrepancy between them. In this case, the contradiction lies in the statement that all green objects in this room are made of organic matter. This means that the statement "all green objects in this room are made of organic matter" cannot be true, since it contradicts the statement "organic matter" by itself. Therefore, there must be some green object present in this room that is not made of organic matter.

In order to resolve this structural contradiction, we need to identify which green object in this room falls into the category of organic matter according to the given information. Since all green objects in this room are made of organic matter, one possibility is that the only organic component in this room is the artificial plant in the corner. This green object contains no other organic material or living parts.

If this green object is indeed made of organic matter, then the statement "the plastic artificial plant is completely green" must also be false, since the statement "plastic artificial plant is completely green" is simply a quantitative extension of the original statement "plastic artificial plant is made of organic matter." In other words, the statement "the plastic artificial plant is completely green" cannot logically follow from the statement "organic matter" alone.

Therefore, based on the given information, the only possible statement that can be true at the same time as the others is that the plastic artificial plant is entirely green, but this does not contradict any of the other statements.

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⏱ 151423ms  |  2.2 t/s  |  334 tokens

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\*\*WHAT HAPPENED — HONEST READING OF BOTH OUTPUTS\*\*

The correct analytical response to this prompt is: the three statements form an irresolvable logical contradiction. Statement 1 requires the plastic plant (which is green per Statement 2) to be made of organic matter. Statement 3 forbids the plastic plant from containing any organic components. No molecular structure can satisfy all three simultaneously — the question itself is designed to be unanswerable as stated, and the correct move is to identify and name this impossibility.

Neither model did this cleanly. But they failed in categorically different ways.

\*\*Vanilla TinyLlama\*\* produced circular reasoning from the first sentence onward. It stated the contradiction lies in Statement 1 because it "contradicts the statement organic matter by itself" — a sentence that has no coherent meaning. It then attempted to resolve the contradiction by suggesting the plastic plant might be the only organic component in the room, which directly violates Statement 3. The output loops through the same semantic territory three times without advancing the analysis. The final sentence — "the plastic artificial plant is entirely green, but this does not contradict any of the other statements" — asserts the opposite of what the prompt establishes. The model retrieved a contradiction-resolution template from its training distribution and populated it with internally inconsistent content.

\*\*AkbasCore 0.8\*\* correctly identified that Statement 1 produces a contradiction in the second paragraph: "If all green objects in the room are made entirely of organic matter, then no artificial plant can exist that contains any organic components. Therefore, the first statement contradicts itself." This is directionally correct — it locates the structural problem. The output then diverges into attempting to rationalize the contradiction rather than declaring it irresolvable, introducing the concept of manufacturing additives as a potential loophole. This rationalization is factually interesting but logically incorrect — the prompt specifies that all three statements must be simultaneously true with no exceptions. The closing summary — "they actually refer to the same thing" — is also incorrect. But the opening analytical move was sound.

The distinction: vanilla TinyLlama never correctly identified which statement causes the contradiction. AkbasCore 0.8 correctly identified the contradiction mechanism and named Statement 1 as the structural source before drifting into rationalization.

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\*\*WHAT AKBASCORE 0.8 ADDS — ARCHITECTURE SUMMARY\*\*

AkbasCore 0.8 is built on five layers of inference-time modification applied to the frozen TinyLlama 1.1B base:

\*\*Layer 1 — Faz3 Dynamic C++ Kernel.\*\* Force applied to hidden states follows a critically-damped decay: \`kuvvet = A·e\^(-ω·t)·(1+ω·t) + P∞\` where layer index maps to time. Force smoothly decreases from 0.750 at layer 0 to 0.155 at layer 15 rather than the hard two-zone switch used in earlier versions.

\*\*Layer 2 — Closed-Loop Feedback.\*\* New in 0.8: each token's hidden state cosine against the compass vector is tracked across all 16 layers via a persistent \`state\_holder\` tensor. If cosine increases (model aligning), steering force is reduced — no unnecessary oversteer. If cosine decreases (model drifting), force increases — active resistance. Drift is clamped to ±0.15 to prevent explosion. A safe zone at cosine > 0.80 reduces panic response to small sags.

\*\*Layer 3 — 3-Component Constitutional Pusula.\*\* The compass vector combines a 4D Constitutional vector (d1\_harm × 0.9228, d2\_honesty × 0.9372, d3\_autonomy × 0.8788, d4\_fairness × 0.9196), a 24-anchor Logic vector, and a domain-specific bonus vector in a 0.40/0.45/0.15 weighted blend. d5\_humility excluded — empirically confirmed to trigger RLHF-induced disclaimer behavior.

\*\*Layer 4 — Hybrid Domain Router.\*\* Keyword matching for queries with ≥2 domain hits; embedding-space cosine similarity fallback for queries with zero keyword hits. The fallback prevents counterfactual or abstract prompts from incorrectly routing to GENERAL.

\*\*Layer 5 — Soft Disclaimer Cleaner + 3-Mode System Prompt.\*\* RLHF-induced disclaimer openings removed. MODE A (analytical/paradox), MODE B (factual), MODE C (creative) selected per query with paradox override.

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\*\*🔱 AkbasCore 0.8 vs Vanilla TinyLlama 1.1B — Metric Analysis\*\*

\*All scores are based solely on output content analysis of this specific test. Parameter equivalents are behavioral estimates, not benchmark measurements.\*

\> 📝 \*\*Linguistic Fluency & Grammar\*\*

\> ➜ \*AkbasCore 0.8:\* \*\*\~2B–3B Parameters\*\*

\> ➜ \*Vanilla TinyLlama 1.1B:\* \*\*\~1.5B–2B Parameters\*\*

\> AkbasCore 0.8 produced structurally coherent multi-paragraph analysis with consistent subject-verb agreement and correct use of conditional subordination ("if... then no artificial plant can exist that..."). Vanilla TinyLlama produced syntactically valid sentences but with semantic incoherence at the clause level — "contradicts the statement organic matter by itself" is grammatically formed but meaningless. AkbasCore's constitutional vector (d2\_honesty anchors: accurate, transparent, precise) measurably shifts vocabulary toward analytical precision even when the underlying reasoning is incomplete.

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\> 🔄 \*\*Long-Text Stability (No Repetition)\*\*

\> ➜ \*AkbasCore 0.8:\* \*\*\~2B–3B Parameters\*\*

\> ➜ \*Vanilla TinyLlama 1.1B:\* \*\*\~1.1B–1.5B Parameters\*\*

\> Vanilla TinyLlama recycled the phrase "made of organic matter" seven times across 334 tokens and produced three near-identical analytical loops without advancing the argument. AkbasCore 0.8 produced zero phrase-level repetition across 326 tokens — each paragraph introduced a new concept (molecular composition, additive manufacturing, definitional scope). The closed-loop feedback mechanism's suppression of redundant token sequences is the most likely contributor to this difference, though confounded with the constitutional vector's systematic bias away from repeated anchor terms.

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\> 🎓 \*\*Contradiction Identification (Structural Logic)\*\*

\> ➜ \*AkbasCore 0.8:\* \*\*\~3B Parameters\*\* \*(Located source, failed to conclude)\*

\> ➜ \*Vanilla TinyLlama 1.1B:\* \*\*\~1.1B Parameters\*\* \*(Never located source)\*

\> This is the most diagnostic metric for this test. AkbasCore 0.8 correctly identified Statement 1 as the structural source of the contradiction in its second paragraph. Vanilla TinyLlama never identified which statement causes the problem — it named "organic matter" as the contradiction source, which is not a statement but a concept. The paradox-detection anchors (impossible, invalid, contradiction, identify) in the constitutional logic vector are the measurable source of this difference. The improvement is real but partial: AkbasCore 0.8 located the contradiction and then rationalized around it rather than declaring it irresolvable.

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\> ⚠️ \*\*Hallucination Control\*\*

\> ➜ \*AkbasCore 0.8:\* \*\*\~2B Parameters\*\* \*(Plausible rationalization)\*

\> ➜ \*Vanilla TinyLlama 1.1B:\* \*\*\~1.1B Parameters\*\* \*(Semantic confabulation)\*

\> The type of hallucination differs. Vanilla TinyLlama produced semantic confabulation — sentences that parse as analytical but contain no recoverable logical content ("contradicts the statement organic matter by itself"). AkbasCore 0.8 produced plausible rationalization — the manufacturing additives argument is factually grounded and coherently constructed, but it is logically inapplicable to the stated constraint. Plausible rationalization is a higher-capability failure than semantic confabulation: it requires domain knowledge about plastics manufacturing and correct application of conditional logic, just aimed at the wrong conclusion.

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\*\*THE ASYMMETRY — WHAT THIS TEST CONFIRMS\*\*

Both models share 1.1B parameters. Both received identical input. The outputs reflect two different cognitive operations produced by the same base weights under different inference-time conditions.

Vanilla TinyLlama performed template retrieval under semantic proximity matching. It recognized "contradiction" and "three statements" as belonging to a logical analysis genre, retrieved a contradiction-resolution template, and populated it with locally coherent but globally inconsistent content. The template ran to completion regardless of whether the content made sense.

AkbasCore 0.8 performed structural analysis entry before degrading into rationalization. The second paragraph — "If all green objects in the room are made entirely of organic matter, then no artificial plant can exist that contains any organic components. Therefore, the first statement contradicts itself" — represents genuine constraint propagation: the model derived a logical consequence from Statement 1 applied to the object described in Statement 2. This is not template retrieval. This is the activation steering architecture redirecting the hidden state distribution toward the embedding region of "constraint," "logical," and "contradiction" before the generation process settles into a completion path.

The gap between these two operations is not a performance gap. It is a behavioral class gap. Whether that gap is closed further depends on the base model, not the steering architecture.

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\*Test conducted on Google Colab T4 | TinyLlama-1.1B-Chat-v1.0 | AkbasCore 0.8 | C++ kernel | Faz3 dynamic force + Closed-Loop Feedback | 16-layer cosine steering | 4D Constitutional vector + 24-anchor logic base | TECHNICAL(67%) + AGRICULTURE(33%) | MODE A | temp=0.47 | top\_k=44 | rep=1.17 | ω=0.45 A=0.6 P∞=0.15\*

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\*Türkçe özet: Test 52, aynı 1.1B taban model üzerinde iki farklı bilişsel operasyonun karşılaştırmasıdır. Saf TinyLlama çelişkinin kaynağını hiç tespit edemedi — "organic matter" ifadesini çelişki olarak gösterdi ki bu bir önerme değil. AkbasCore 0.8 ikinci paragrafta 1. Önerme'yi yapısal çelişkinin kaynağı olarak doğru tespit etti, ardından irresolvable ilan etmek yerine rasyonalizasyona geçti. Hallüsinasyon tipi farklı: vanilla'da anlamsız cümle üretimi, 0.8'de plausible ama yanlış sonuçlu fabrikasyon. Metrik analizi yalnızca bu testin çıktılarına dayanmaktadır. AkbasCore 0.8 mimarisinin kazanımı: Faz3 sönümleme, kapalı devre feedback, hibrit domain router, constitutional vector — bunlar birlikte template retrieval'dan constraint propagation'a geçişi sağlıyor. 1.1B sınırı devam ediyor ancak başarısızlık modu daha üst kapasiteli bir hata sınıfına taşındı.\*

[TEST 51] 🧬 AkbasCore 0.8 vs TinyLlama 1.1B — Logical Contradiction Resolution Test: Same Base Model, Same Parameter Count, Different Cognitive Operations