Neural Networks and the Emergence of Learning (SDETTI, 2023)
Info
- Project type Scientific Research Paper
- Date 6th of Oct 2023
- My Role Author
- Topics Emergent phenomenons in the realm of machines
- Keywords AI, Consciousness, Continual Learning, Knowledge representation, Neural Networks
- Skills developed General ML and Math knowledge, Better understanding of consciousness studies
- My ORCID 0009-0007-8424-4895
- Paper Download PDF
- Presentation Slides
- GitHub Open Source Code
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Photo
Description
My paper at the Doctoral Symposium on Electronics, Telecommunications & Information Technology, October 2023.
Abstract
This paper introduces a tri-component framework for studying neural networks, focusing on the phenomenon of emergent learning. Built on Java, Python, and JavaScript, the framework aids in the visualization and analysis of network behaviours.
We employ a single-neuron model to examine mathematical functions and learning algorithms, such as Sigmoid activation and backpropagation.
The paper challenges reductionist approaches and calls for integrative methods to understand the complex dynamics underlying both artificial and natural learning systems.
Resources
Tech stack
- Programming Languages: Java 17, Python 3.11, Javascript
- Java stack: Spring Boot, Spring Web, Thymeleaf, Lombok, org.json, Log4j
- Python stack: numpy, tensorflow, matplotlib, scikit-image
- Javascript stack: D3js
