{"title":"计算自然哲学:从前苏格拉底到图灵再到ChatGPT的一条线索","authors":"Gordana Dodig-Crnkovic","doi":"arxiv-2309.13094","DOIUrl":null,"url":null,"abstract":"Modern computational natural philosophy conceptualizes the universe in terms\nof information and computation, establishing a framework for the study of\ncognition and intelligence. Despite some critiques, this computational\nperspective has significantly influenced our understanding of the natural\nworld, leading to the development of AI systems like ChatGPT based on deep\nneural networks. Advancements in this domain have been facilitated by\ninterdisciplinary research, integrating knowledge from multiple fields to\nsimulate complex systems. Large Language Models (LLMs), such as ChatGPT,\nrepresent this approach's capabilities, utilizing reinforcement learning with\nhuman feedback (RLHF). Current research initiatives aim to integrate neural\nnetworks with symbolic computing, introducing a new generation of hybrid\ncomputational models.","PeriodicalId":501533,"journal":{"name":"arXiv - CS - General Literature","volume":"64 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT\",\"authors\":\"Gordana Dodig-Crnkovic\",\"doi\":\"arxiv-2309.13094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modern computational natural philosophy conceptualizes the universe in terms\\nof information and computation, establishing a framework for the study of\\ncognition and intelligence. Despite some critiques, this computational\\nperspective has significantly influenced our understanding of the natural\\nworld, leading to the development of AI systems like ChatGPT based on deep\\nneural networks. Advancements in this domain have been facilitated by\\ninterdisciplinary research, integrating knowledge from multiple fields to\\nsimulate complex systems. Large Language Models (LLMs), such as ChatGPT,\\nrepresent this approach's capabilities, utilizing reinforcement learning with\\nhuman feedback (RLHF). Current research initiatives aim to integrate neural\\nnetworks with symbolic computing, introducing a new generation of hybrid\\ncomputational models.\",\"PeriodicalId\":501533,\"journal\":{\"name\":\"arXiv - CS - General Literature\",\"volume\":\"64 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - General Literature\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2309.13094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - General Literature","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2309.13094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT
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.