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.

翻译：现代计算自然哲学将宇宙概念化为信息和计算，为认知与智能研究建立了框架。尽管存在一些批评，但这种计算视角已显著影响了我们对自然世界的理解，推动了基于深度神经网络的AI系统（如ChatGPT）的发展。该领域的进步通过跨学科研究得以促进，整合了来自多个领域的知识以模拟复杂系统。大型语言模型（LLMs），例如ChatGPT，代表了这种方法的能力，并利用了基于人类反馈的强化学习（RLHF）。当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。