Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT

Gordana Dodig-Crnkovic
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Abstract

Modern computational natural philosophy conceptualizes the universe in terms of information and computation, establishing a framework for the study of cognition and intelligence. Despite some critiques, this computational perspective has significantly influenced our understanding of the natural world, leading to the development of AI systems like ChatGPT based on deep neural networks. Advancements in this domain have been facilitated by interdisciplinary research, integrating knowledge from multiple fields to simulate complex systems. Large Language Models (LLMs), such as ChatGPT, represent this approach's capabilities, utilizing reinforcement learning with human feedback (RLHF). Current research initiatives aim to integrate neural networks with symbolic computing, introducing a new generation of hybrid computational models.
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计算自然哲学:从前苏格拉底到图灵再到ChatGPT的一条线索
现代计算自然哲学从信息和计算的角度对宇宙进行概念化,为研究认知和智能建立了框架。尽管有一些批评,但这种计算视角极大地影响了我们对自然世界的理解,导致了基于深度神经网络的ChatGPT等人工智能系统的发展。跨学科研究促进了这一领域的进步,整合了多个领域的知识来模拟复杂系统。大型语言模型(llm),如ChatGPT,代表了这种方法的能力,利用强化学习与人类反馈(RLHF)。目前的研究计划旨在将神经网络与符号计算相结合,引入新一代混合计算模型。
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A guideline for the methodology chapter in computer science dissertations Eternal Sunshine of the Mechanical Mind: The Irreconcilability of Machine Learning and the Right to be Forgotten A Comprehensive Overview of Fish-Eye Camera Distortion Correction Methods The 4+1 Model of Data Science Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT
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