SOFTWARE-BASED MASS CUSTOMIZATION OF ARTIFICIAL NEURAL NETWORKS AND ITS BENEFITS

Invention Summary

Artificial intelligence (AI) and machine learning (ML) technologies are transforming various industries by enabling sophisticated data analysis and decision-making. The adaption of these technologies is often hindered by complexity, the lack of explainability, and resource requirements. This technology supports providing a user-friendly software platform designed for the mass customization of artificial neural networks (ANNs). The platform employs a diagramming interface, allowing users to create, visualize, and customize neural network models with ease.

computer monitors imaging neural networks| NDSU Research Foundation

Key Features

  • Enables a Drag-and-Drop Interface: users can construct neural networks by dragging and dropping neuron and link objects, streamlining the model creation process
  • Batch Creation: allows the generation of multiple neurons and layers simultaneously, simplifying the development of complex models
  • Neuron-Level Customization: users can modify individual neurons' activation functions, weight initializations, and connectivity, facilitating the creation of heterogeneous neural networks
  • Coordinate Mapping System: a Cartesian plane coordinate system helps users keep track of neural network components, improving model management

Benefits

  • Accessibility: simplifies the process of building and customizing neural networks, making advanced AI and deep learning (DL) technologies accessible to users with varying levels of expertise
  • Flexibility: enables detailed customization at the neuron level, allowing users to tailor models to specific applications and experiment with different configurations
  • Efficiency: automates the creation of backend logic, saving time and reducing the need for extensive technical knowledge
  • Scalability: supports the creation of large-scale, complex models through batch creation and easy visualization tools

Applications

  • Healthcare: developing diagnostic models and personalized treatment plans
  • Finance: fraud detection, risk assessment, and predictive analytics
  • Autonomous Vehicles: enhancing decision-making processes for vehicle navigation and safety systems
  • Cybersecurity: intrusion detection and threat analysis
  • Natural Language Processing: improving language translation, sentiment analysis, and conversational AI

Patent

This technology has a U.S. Patent Pending and is available for licensing/partnering opportunities.

Contact

NDSU Research Foundation
info(at)ndsurf(dot)org
(701) 231-8173

NDSURF Tech Key

RFT, 681, RFT681

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