Suppr超能文献

人工智能:对误解、神话和理想状态的澄清

Artificial Intelligence: A Clarification of Misconceptions, Myths and Desired Status.

作者信息

Emmert-Streib Frank, Yli-Harja Olli, Dehmer Matthias

机构信息

Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland.

Institute of Biosciences and Medical Technology, Tampere, Finland.

出版信息

Front Artif Intell. 2020 Dec 23;3:524339. doi: 10.3389/frai.2020.524339. eCollection 2020.

Abstract

The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed through various stages of popularity and has recently undergone a revival through the introduction of deep neural networks. Some problems of AI are that, so far, neither the "intelligence" nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to lift the veil of vagueness surrounding AI to reveal its true countenance.

摘要

人工智能(AI)领域创立于65多年前。该领域起初满怀巨大的希望和宏伟的目标,历经了不同的兴衰阶段,最近随着深度神经网络的引入而再度兴起。人工智能存在一些问题,即到目前为止,“智能”和人工智能的目标都没有得到正式定义,这在将人工智能与其他领域进行比较时会造成混乱。在本文中,我们阐述了人工智能在机器学习和统计学方面的理想状态与当前现状,并澄清了常见的误解和错误观念。我们的讨论旨在揭开笼罩在人工智能周围的模糊面纱,以展现其真实面貌。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/336e/7944138/4ccf23bd35a1/frai-03-524339-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验