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Draft:DGNP AI

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DGNP AI

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DGNP (Digital Generator of Neuro Pattern) is an innovative artificial intelligence (AI) framework inspired by the subconscious behavior of the human mind. It is designed to understand sentence structures like a human, allowing it to functionally learn from text and store knowledge based on subjects, features, and relational logic.

The project was officially initiated in early 2023. The lead researcher and developer of DGNP is Nazmul Haque, born in 1996, from Bangladesh.

Overview

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Unlike traditional AI models such as GPT, which are based on pattern recognition and massive datasets, DGNP focuses on functional and logical understanding. It processes sentences by identifying the subject, the supporting verb (or relational function), and feature-based information — similar to how the subconscious human mind interprets language.

Core Objectives

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  • Understand language through logical structure, not just word frequency.
  • Learn independently by forming internal questions when encountering unknown words or concepts.
  • Store knowledge in a dynamic, feature-based way linked to subjects.
  • Continuously update knowledge as new input is processed.

Key Features

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  • Custom-built without third-party NLP libraries like spaCy or NLTK.
  • Built-in logic to detect subject-verb-feature relationships.
  • Self-questioning and self-updating abilities for deeper comprehension.

Comparison with Traditional AI Models

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Feature Traditional AI (e.g. GPT) DGNP
Learning Method Pattern-based (statistical) Structure-based (logical)
Data Requirement Massive datasets Minimal, human-style learning
Understanding Word predictions Sentence structure and meaning
Adaptability Needs retraining Self-expanding logic

Use Cases

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  • Autonomous question-answering systems
  • Human-like AI chat assistants
  • Educational tools for grammar and logic learning
  • Knowledge engines for specialized domains

About the Developer

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Nazmul Haque, born in 1996 in Bangladesh, is the founder and primary architect of the DGNP project. With a vision to create an AI that truly thinks like a human, he has designed DGNP to go beyond typical machine learning and into the realm of structured, conscious-like intelligence.

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