{"title":"从 McCulloch 到 GPT - 4:人工智能的发展阶段。","authors":"Yashchenko V","doi":"10.15407/jai2024.01.031","DOIUrl":null,"url":null,"abstract":"The article examines the history of the development of artificial intelligence (AI), starting from its first theoretical and practical steps and tracing the evolution to modern achievements. The article provides an overview of the key milestones, scientific discoveries and technological breakthroughs made in the field of AI. The most important figures, ideas and principles that influenced its development are also discussed. In the context of this development, various definitions of artificial intelligence are given. There are several key stages in the history of AI: the early stages, the quiet period, the AI renaissance, and the era of AI in the new millennium. Each of these stages made its own unique contribution to the progress of AI. The modern period is characterized by rapid development, especially in the field of machine learning and deep learning. These methods allow artificial intelligence to learn from data and identify complex patterns. Advances in natural language processing, such as models GPT and its modifications, have shown outstanding results. However, despite linguistic advances, GPT remains limited in aspects important to creating strong AI. The article discusses the limitations of modern language models, as well as the prerequisites and prospects for the development of strong artificial intelligence. Special attention is paid to the project of Elon Musk, who, having launched the company X.AI, is engaged in research in the field of creating strong AI with the goal of “knowledge of reality.” The article also proposes an alternative approach to creating strong artificial intelligence - the development of an artificial brain based on a multidimensional multi-connected receptor-effector neuron-like growing network. Some aspects of the emergence of artificial consciousness are also considered.","PeriodicalId":8434,"journal":{"name":"Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":5.1000,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"From McCulloch to GPT - 4: stages of development of artificial intelligence.\",\"authors\":\"Yashchenko V\",\"doi\":\"10.15407/jai2024.01.031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article examines the history of the development of artificial intelligence (AI), starting from its first theoretical and practical steps and tracing the evolution to modern achievements. The article provides an overview of the key milestones, scientific discoveries and technological breakthroughs made in the field of AI. The most important figures, ideas and principles that influenced its development are also discussed. In the context of this development, various definitions of artificial intelligence are given. There are several key stages in the history of AI: the early stages, the quiet period, the AI renaissance, and the era of AI in the new millennium. Each of these stages made its own unique contribution to the progress of AI. The modern period is characterized by rapid development, especially in the field of machine learning and deep learning. These methods allow artificial intelligence to learn from data and identify complex patterns. Advances in natural language processing, such as models GPT and its modifications, have shown outstanding results. However, despite linguistic advances, GPT remains limited in aspects important to creating strong AI. The article discusses the limitations of modern language models, as well as the prerequisites and prospects for the development of strong artificial intelligence. Special attention is paid to the project of Elon Musk, who, having launched the company X.AI, is engaged in research in the field of creating strong AI with the goal of “knowledge of reality.” The article also proposes an alternative approach to creating strong artificial intelligence - the development of an artificial brain based on a multidimensional multi-connected receptor-effector neuron-like growing network. 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From McCulloch to GPT - 4: stages of development of artificial intelligence.
The article examines the history of the development of artificial intelligence (AI), starting from its first theoretical and practical steps and tracing the evolution to modern achievements. The article provides an overview of the key milestones, scientific discoveries and technological breakthroughs made in the field of AI. The most important figures, ideas and principles that influenced its development are also discussed. In the context of this development, various definitions of artificial intelligence are given. There are several key stages in the history of AI: the early stages, the quiet period, the AI renaissance, and the era of AI in the new millennium. Each of these stages made its own unique contribution to the progress of AI. The modern period is characterized by rapid development, especially in the field of machine learning and deep learning. These methods allow artificial intelligence to learn from data and identify complex patterns. Advances in natural language processing, such as models GPT and its modifications, have shown outstanding results. However, despite linguistic advances, GPT remains limited in aspects important to creating strong AI. The article discusses the limitations of modern language models, as well as the prerequisites and prospects for the development of strong artificial intelligence. Special attention is paid to the project of Elon Musk, who, having launched the company X.AI, is engaged in research in the field of creating strong AI with the goal of “knowledge of reality.” The article also proposes an alternative approach to creating strong artificial intelligence - the development of an artificial brain based on a multidimensional multi-connected receptor-effector neuron-like growing network. Some aspects of the emergence of artificial consciousness are also considered.
期刊介绍:
The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.