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 rest.
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 without generating new content.
3. Text Structural Genetic Code
AMP (Amplifying) + DAMP (Damping) + STABLE = 100%
AMP Amplifying > 55%
Increasing energy — Actions, Assertions, Execution, Results. Text has a clear focal point; Core Content has high reliability.
DAMP Damping > 55%
Decreasing energy — Conditions, Context, Risks, Exceptions, Counterarguments. Text tends toward condition analysis or risk assessment.
STABLE AMP ≈ DAMP
Balanced state — Technical info, Pure data, Data tables, Descriptive content. 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 content nucleus with minimum necessary context.
Expanded
Core Content combined with surrounding relevant context.
Comprehensive (100%)
Full text with DAMPING components marked for easy distinction.
5. Value for Experts & Managers
- Quantifiability: AMP%, DAMP%, Compression%, retained sentences
- Causality: Core Content often in Action → Result structures
- Decision-Making: Quickly evaluate whether to read, examine, or act
- Objectivity: Algorithm-based, not subjective emphasis
6. Value for General Users
- Read Quickly: Identify the highest-action-density sentence instantly
- Evaluate Before Reading: Observe AMP/DAMP in round 1
- Objective Comparison: Compare Core Content across multiple texts
- Identify Key Points: Spot conditions, warnings, or risks
7. Limitations
If Compression > 90% in Standard or Refined mode, manually copy or upload a file to ensure input integrity.
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
