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RESEARCH ARTICLE
Do Artificial Neural Network-Based Language Models Fulfill the Foundational Requirements of General Intelligence?
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1 Ankara Sosyal Bilimler Üniversitesi, Sosyal ve Beşeri Bilimler Fakültesi, Felsefe Bölümü 06050, Ankara,
Türkiye
Received: 3 November 2024 | Published online: 30 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract
Today's large-scale language models are based on artificial neural networks. Since 2020, large language models like the GPT series have captured the attention of academia, business, and the public, focusing their interest on neural network-based natural language processing technologies. While machine learning researchers hold diverse views on the GPT series’ success in natural language processing and its significance regarding artificial general intelligence, there is consensus that its language processing capabilities have exceeded expectations. This study examines whether artificial neural networks can achieve general intelligence. It evaluates whether some fundamental cognitive skills necessary for general intelligence can be simulated by current artificial neural networks. To address this, the paper discusses how artificial neural networks operate through statistical processes and explores the relationship between these processes and key components of general intelligence and understanding.
Keywords
Artificial Neural Networks
Artificial General Intelligence
Natural Language Processing
Artificial Understanding
Functionalism.
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