Artificial intelligence-powered code generation is revolutionizing system software development through the use of machine learning. Neural network generation of software modules of the system is carried out according to prompts in natural language. A trend of vibe coding has emerged in the world of technology – code generation by neural networks from natural language. For example, Cursor via ChatGPT 4.1 can generate various software modules based on descriptions of their functions in natural language. Creating large software systems from generated modules requires integration. Neurocomplexation of software modules is the process of integrating or combining various software modules to create complex systems based on neural models or artificial neural networks. This approach is proposed to be used in the field of artificial intelligence and machine learning to build complex systems where individual modules interact and jointly perform tasks. Promising areas of application are, firstly, the creation of cognitive systems and intelligent ensembles of agents and assistants. Secondly, modeling of thinking and brain function for research in neuroscience, and thirdly, the development of complex solutions in the field of automation and robotics. The key features of the neural network integration process are, firstly, the integration of modules with different functions (recognition, data processing, training). Secondly, the use of neural network algorithms for adaptation and self-training. Thirdly, ensuring the flexibility and scalability of the system.
| Published in | American Journal of Embedded Systems and Applications (Volume 10, Issue 1) |
| DOI | 10.11648/j.ajesa.20251001.12 |
| Page(s) | 17-23 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Neural Network Technology, AI Generation, System Program Code, Modular Neural Integration
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APA Style
Bryndin, E. (2025). Technological Stages of Neural Network AI Generation of System Program Code Based on Modular Neuro Integration. American Journal of Embedded Systems and Applications, 10(1), 17-23. https://doi.org/10.11648/j.ajesa.20251001.12
ACS Style
Bryndin, E. Technological Stages of Neural Network AI Generation of System Program Code Based on Modular Neuro Integration. Am. J. Embed. Syst. Appl. 2025, 10(1), 17-23. doi: 10.11648/j.ajesa.20251001.12
AMA Style
Bryndin E. Technological Stages of Neural Network AI Generation of System Program Code Based on Modular Neuro Integration. Am J Embed Syst Appl. 2025;10(1):17-23. doi: 10.11648/j.ajesa.20251001.12
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Download@article{10.11648/j.ajesa.20251001.12,
author = {Evgeny Bryndin},
title = {Technological Stages of Neural Network AI Generation of System Program Code Based on Modular Neuro Integration
},
journal = {American Journal of Embedded Systems and Applications},
volume = {10},
number = {1},
pages = {17-23},
doi = {10.11648/j.ajesa.20251001.12},
url = {https://doi.org/10.11648/j.ajesa.20251001.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajesa.20251001.12},
abstract = {Artificial intelligence-powered code generation is revolutionizing system software development through the use of machine learning. Neural network generation of software modules of the system is carried out according to prompts in natural language. A trend of vibe coding has emerged in the world of technology – code generation by neural networks from natural language. For example, Cursor via ChatGPT 4.1 can generate various software modules based on descriptions of their functions in natural language. Creating large software systems from generated modules requires integration. Neurocomplexation of software modules is the process of integrating or combining various software modules to create complex systems based on neural models or artificial neural networks. This approach is proposed to be used in the field of artificial intelligence and machine learning to build complex systems where individual modules interact and jointly perform tasks. Promising areas of application are, firstly, the creation of cognitive systems and intelligent ensembles of agents and assistants. Secondly, modeling of thinking and brain function for research in neuroscience, and thirdly, the development of complex solutions in the field of automation and robotics. The key features of the neural network integration process are, firstly, the integration of modules with different functions (recognition, data processing, training). Secondly, the use of neural network algorithms for adaptation and self-training. Thirdly, ensuring the flexibility and scalability of the system.
},
year = {2025}
}
TY - JOUR T1 - Technological Stages of Neural Network AI Generation of System Program Code Based on Modular Neuro Integration AU - Evgeny Bryndin Y1 - 2025/10/09 PY - 2025 N1 - https://doi.org/10.11648/j.ajesa.20251001.12 DO - 10.11648/j.ajesa.20251001.12 T2 - American Journal of Embedded Systems and Applications JF - American Journal of Embedded Systems and Applications JO - American Journal of Embedded Systems and Applications SP - 17 EP - 23 PB - Science Publishing Group SN - 2376-6085 UR - https://doi.org/10.11648/j.ajesa.20251001.12 AB - Artificial intelligence-powered code generation is revolutionizing system software development through the use of machine learning. Neural network generation of software modules of the system is carried out according to prompts in natural language. A trend of vibe coding has emerged in the world of technology – code generation by neural networks from natural language. For example, Cursor via ChatGPT 4.1 can generate various software modules based on descriptions of their functions in natural language. Creating large software systems from generated modules requires integration. Neurocomplexation of software modules is the process of integrating or combining various software modules to create complex systems based on neural models or artificial neural networks. This approach is proposed to be used in the field of artificial intelligence and machine learning to build complex systems where individual modules interact and jointly perform tasks. Promising areas of application are, firstly, the creation of cognitive systems and intelligent ensembles of agents and assistants. Secondly, modeling of thinking and brain function for research in neuroscience, and thirdly, the development of complex solutions in the field of automation and robotics. The key features of the neural network integration process are, firstly, the integration of modules with different functions (recognition, data processing, training). Secondly, the use of neural network algorithms for adaptation and self-training. Thirdly, ensuring the flexibility and scalability of the system. VL - 10 IS - 1 ER -
Scientific Department, Research Center Nature Informatic, Novosibirsk, Russia
