← Back to home

NKTg AI is not a summarization tool. It is a specialized Language Decoding System that uses physical algorithms to measure semantic energy and extract the Core Content — the core logical genetic code of a text.

1. The Nature of Core Content

Core Content is the sentence with the highest density of executable actions and the most concrete outcome in a text. If removed, the text loses key information that cannot be inferred from the remaining sentences.
It is an original sentence from the source text — not interpreted or altered by subjective reasoning.

2. Philosophy

Generative AI: Reads and reinterprets a text using the AI's own language.
NKTg AI: Measures the energy of each word and sentence to identify core content that already exists. Returns the author's original linguistic genetic code.

3. Text Structural Genetic Code

AMP (Amplifying) + DAMP (Damping) + STABLE = 100%
AMP Amplifying > 55%
Increasing energy — Actions, Assertions, Execution, Results. The text has a clear focal point.
DAMP Damping > 55%
Decreasing energy — Conditions, Context, Risks, Exceptions, Counterarguments. The text tends toward condition analysis.
STABLE AMP ≈ DAMP
Balanced state — Technical information, pure data. A prominent Core Content may not exist.

4. Output Modes

🧠 Left Brain (Extraction) — Distillation
Standard: Retains the most important sentences by the Golden Ratio. Best for quick reading.
Condensed: Removes repetitive or semantically similar sentences. Best for long texts.
Essence: Converges to a single Core Content sentence. Recommended when AMP > 55%.
🧠 Right Brain (Addition) — Expansion
Refined: Preserves the content nucleus with minimum necessary context.
Expanded: Core Content combined with surrounding relevant context.
Comprehensive (100%): Keeps the full text, with DAMPING components marked for easy distinction.

5. Value for Experts & Managers

• Quantifiability: AMP%, DAMP%, Compression%, retained sentences
• Causality: Core Content often sits in Action → Result structures
• Decision-Making: Quickly evaluate whether to keep reading, examine further, or act
• Objectivity: Based on an energy-measurement algorithm, not subjective emphasis

6. Value for General Users

• Read Quickly: Identify the sentence with the highest action density instantly
• Evaluate Before Reading: Observe AMP/DAMP in the first pass
• Objective Comparison: Compare Core Content across multiple texts on the same topic
• Identify Key Points: Spot conditions, warnings, or risks

7. Limitations to Keep in Mind

NKTg AI does not perform well on handwritten documents — OCR accuracy drops significantly compared to printed text, which may affect extraction quality.

8. NKTg Law — Variable Inertia Algorithm

NKTg = f(x, v, m)
p = m × v
NKTg₁ = x × p    (Semantic Potential Energy)
NKTg₂ = (dm/dt) × p    (Semantic Kinetic Energy)
NKTg(total) = f(NKTg₁, NKTg₂)

All processing runs directly in the browser via WebAssembly.
Text never leaves the user's device
No server, no cloud, no remote database
History is stored in localStorage — residing entirely on the user's device