Imitating the Brain with Neurocomputer A "New" Way Towards Artificial General Intelligence

来源 :International Journal of Automation and Computing | 被引量 : 0次 | 上传用户:novi005
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
To achieve the artificial general intelligence(AGI),imitate the intelligence? or imitate the brain? This is the question!Most artificial intelligence(AI) approaches set the understanding of the intelligence principle as their premise.This may be correct to implement specific intelligence such as computing,symbolic logic,or what the Alpha Go could do.However,this is not correct for AGI,because to understand the principle of the brain intelligence is one of the most difficult challenges for our human beings.It is not wise to set such a question as the premise of the AGI mission.To achieve AGI,a practical approach is to build the so-called neurocomputer,which could be trained to produce autonomous intelligence and AGI.A neurocomputer imitates the biological neural network with neuromorphic devices which emulate the bio-neurons,synapses and other essential neural components.The neurocomputer could perceive the environment via sensors and interact with other entities via a physical body.The philosophy under the “new” approach,so-called as imitationalism in this paper,is the engineering methodology which has been practiced for thousands of years,and for many cases,such as the invention of the first airplane,succeeded.This paper compares the neurocomputer with the conventional computer.The major progress about neurocomputer is also reviewed. To achieve the artificial general intelligence (AGI), imitate the intelligence? Or imitate the brain? This is the question! Most artificial intelligence (AI) approaches set the understanding of the intelligence principle as their premise. This may be correct to implement specific intelligence such as computing, symbolic logic, or what the Alpha Go could do.However, this is not correct for AGI, because to understand the principle of the brain intelligence is one of the most difficult challenges for our human beings. It is not wise to set such a question as the premise of the AGI mission.To achieve AGI, a practical approach is to build the so-called neurocomputer, which could be trained to produce autonomous intelligence and AGI. A neurocomputer imitates the biological neural network with neuromorphic devices which emulate the bio-neurons, synapses and other essential neural components. The neurocomputer could not be in the environment via sensors and interact with other entities via a physical body. philosophy under the “new ” approach, so-called as imitationalism in this paper, is the engineering methodology which has been practiced for thousands of years, and for many cases, such as the the invention of the first airplane, succeeded.This paper compares the neurocomputer with the conventional computer. major in about neurocomputer is also reviewed.
其他文献
Surface particles growing in large aperture optical element(LAOE) have significant impact on LAOE s stable operation.It is a challenge for the online system to
In order to solve the problem of indoor place recognition for indoor service robot, a novel algorithm, clustering of features and images(CFI), is proposed in this work. Different from traditional indo
该文从挂篮荷载计算、施工流程、支座及临时固结施工、挂篮安装及试验、合拢段施工、模板制作安装、钢筋安装、混凝土的浇筑及养生、测量监控等方面人手,介绍了S226海滨大桥
A new semi-blind adaptive beamforming scheme is proposed for multi-input multi-output(MIMO) induced and spacedivision multiple-access based wireless systems tha
在治疗法则中,有常法,亦有变法.医者需要知其常,更要达其变.我们在临床实践中,对某些疾病,使用变法,皆取得了满意疗效.兹将验案实录,略陈管见如下,以期抛砖引玉.
In this paper, a mathematical model of the photovoltaic(PV) pumping system s main components is firstly established.Then, the design of maximum power point trac
期刊
This paper presents the design of sliding mode controller for the output regulation of single input single output(SISO)nonlinear systems. The sliding surfaces a
The paper reviews and extends an emerging body of theoretical results on deep learning including the conditions under which it can be exponentially better than