scholarly journals Research on How Human Intelligence, Consciousness, and Cognitive Computing Affect the Development of Artificial Intelligence

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yanyan Dong ◽  
Jie Hou ◽  
Ning Zhang ◽  
Maocong Zhang
Keyword(s):  
Artificial Intelligence ◽  
Human Brain ◽  
Tacit Knowledge ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Human Intelligence ◽  
Cognitive Computing ◽  
Human Beings ◽  
Intelligent Machines ◽  
Value Rationality

Artificial intelligence (AI) is essentially the simulation of human intelligence. Today’s AI can only simulate, replace, extend, or expand part of human intelligence. In the future, the research and development of cutting-edge technologies such as brain-computer interface (BCI) together with the development of the human brain will eventually usher in a strong AI era, when AI can simulate and replace human’s imagination, emotion, intuition, potential, tacit knowledge, and other kinds of personalized intelligence. Breakthroughs in algorithms represented by cognitive computing promote the continuous penetration of AI into fields such as education, commerce, and medical treatment to build up AI service space. As to human concern, namely, who controls whom between humankind and intelligent machines, the answer is that AI can only become a service provider for human beings, demonstrating the value rationality of following ethics.

scholarly journals Artificial Intelligence, Smart Contract and Islamic Finance

2018 ◽  
Vol 14 (2) ◽  
pp. 145 ◽  
Author(s):  
Siti Rohaya Mat Rahim ◽  
Zam Zuriyati Mohamad ◽  
Juliana Abu Bakar ◽  
Farhana Hanim Mohsin ◽  
Norhayati Md Isa
Keyword(s):  
Artificial Intelligence ◽  
Computer Code ◽  
Islamic Finance ◽  
Human Intelligence ◽  
Human Beings ◽  
Finance Industry ◽  
Smart Contract ◽  
Huge Impact ◽  
Block Chain

This study examines the two important aspect of latest technology issues in Islamic finance that related to artificial intelligence (AI) and smart contract. AI refers to the ability of machines to understand, think, and learn in a similar way to human beings, indicating the possibility of using computers to simulate human intelligence. Smart contract is a computer code running on top of a block-chain containing a set of rules under which the parties to that smart contract agree to interact with each other. The main objectives of this article are to evaluate the operations of AI and smart contract, to make comparison between the operations of AI and smart contract. This article concludes that AI and smart contract will have a huge impact in future for Islamic Finance industry.

Artificial Intelligence

2019 ◽  
pp. 13-22
Author(s):  
Steven Walczak
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Future Research ◽  
Human Intelligence ◽  
Research Directions ◽  
Intelligent Machines ◽  
History Of ◽  
Future Research Directions ◽  
New Research

Artificial intelligence is the science of creating intelligent machines. Human intelligence is comprised of numerous pieces of knowledge as well as processes for utilizing this knowledge to solve problems. Artificial intelligence seeks to emulate and surpass human intelligence in problem solving. Current research tends to be focused within narrow, well-defined domains, but new research is looking to expand this to create global intelligence. This chapter seeks to define the various fields that comprise artificial intelligence and look at the history of AI and suggest future research directions.

A Brief History

2021 ◽  
pp. 26-56
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Human Intelligence ◽  
Single System ◽  
Cognitive Computing ◽  
Job Functions ◽  
Technology Industry ◽  
History Of ◽  
Time Variables ◽  
System Operating

In this chapter, the author presents a brief history of artificial intelligence (AI) and cognitive computing (CC). They are often interchangeable terms to many people who are not working in the technology industry. Both imply that computers are now responsible for performing job functions that a human used to perform. The two topics are closely aligned; while they are not mutually exclusive, both have distinctive purposes and applications due to their practical, industrial, and commercial appeal as well as their respective challenges amongst academia, engineering, and research communities. To summarise, AI empowers computer systems to be smart (and perhaps smarter than humans). Conversely, CC includes individual technologies that perform specific tasks that facilitate and augment human intelligence. When the benefits of both AI and CC are combined within a single system, operating from the same sets of data and the same real-time variables, they have the potential to enrich humans, society, and our world.

scholarly journals A Simple Convolutional Neural Network for Accurate P300 Detection and Character Spelling in Brain Computer Interface

2018 ◽  
Author(s):  
Hongchang Shan ◽  
Yu Liu ◽  
Todor Stefanov
Keyword(s):  
Signal Detection ◽  
Spatial Information ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Detection Accuracy ◽  
Signal Recognition ◽  
Human Beings ◽  
Feature Representations ◽  
Machine Learning Methods ◽  
Benchmark Datasets

A Brain Computer Interface (BCI) character speller allows human-beings to directly spell characters using eye-gazes, thereby building communication between the human brain and a computer. Convolutional Neural Networks (CNNs) have shown better performance than traditional machine learning methods for BCI signal recognition and its application to the character speller. However, current CNN architectures limit further accuracy improvements of signal detection and character spelling and also need high complexity to achieve competitive accuracy, thereby preventing the use of CNNs in portable BCIs. To address these issues, we propose a novel and simple CNN which effectively learns feature representations from both raw temporal information and raw spatial information. The complexity of the proposed CNN is significantly reduced compared with state-of-the-art CNNs for BCI signal detection. We perform experiments on three benchmark datasets and compare our results with those in previous research works which report the best results. The comparison shows that our proposed CNN can increase the signal detection accuracy by up to 15.61% and the character spelling accuracy by up to 19.35%.

scholarly journals Analysis of Golfer‘S Brainwave Signal During Par Tee Ireland and Driving Range Game

2018 ◽  
Vol 7 (4.30) ◽  
pp. 469
Author(s):  
Yusof, M.M. M ◽  
Salleh, S. M ◽  
Ainul, H.M. Y ◽  
Siswanto, W. A ◽  
Mahmud, W.M.A .W
Keyword(s):  
Fourier Transform ◽  
Human Brain ◽  
Brain Computer Interface ◽  
Exchange Process ◽  
Sport Performance ◽  
Computer Interface ◽  
Eeg Signal ◽  
External Device ◽  
Control Signals ◽  
Driving Range

Ways to improve sport performance become exceptional contemporary interest. Nowadays, many studies use human brain as an input signal include eyes blinking, attention and meditation to control the exchange process. Brain–Computer Interface (BCI) requires generating control signals for external device by analysing the internal brain signal. The objective is to identify the signal of brainwave which gives effect to performance of golfer. The analysis involved the meditation (α) and attention (β) state of different golf players. In this project, the brainwave of golfer’s will be analyzed based on the movement before club strike the ball. EEG signal used to find out the features by using Fast Fourier Transform (FFT). The analysis included three categories of player include beginner, intermediate and professional. Two types of game have been considered which are Par Tee Ireland and Driving Range. The project interfaces MATLAB software with an EEG headset. The data has interpreted in time and frequency domain graph that show different level in an attention (β) state for both games. Brainwave signals indicated players’ performance and lead to better performance. This data benefits increasing the performance of golfer to become the professional golfer by using electroencephalography (EEG) headset in future study.

scholarly journals The Human Intelligence vs. Artificial Intelligence: Issues and Challenges in Computer Assisted Language Learning

2018 ◽  
Vol 8 (5) ◽  
pp. 259
Author(s):  
Mohammed Ali
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Human Brain ◽  
Language Learning ◽  
Language Processing ◽  
Human Intelligence ◽  
Computer Assisted ◽  
Learning Programs ◽  
Face Detection And Recognition ◽  
Learning Software

In this study, the researcher has advocated the importance of human intelligence in language learning since software or any Learning Management System (LMS) cannot be programmed to understand the human context as well as all the linguistic structures contextually. This study examined the extent to which language learning is perilous to machine learning and its programs such as Artificial Intelligence (AI), Pattern Recognition, and Image Analysis used in much assistive learning techniques such as voice detection, face detection and recognition, personalized assistants, besides language learning programs. The researchers argue that language learning is closely associated with human intelligence, human neural networks and no computers or software can claim to replace or replicate those functions of human brain. This study thus posed a challenge to natural language processing (NLP) techniques that claimed having taught a computer how to understand the way humans learn, to understand text without any clue or calculation, to realize the ambiguity in human languages in terms of the juxtaposition between the context and the meaning, and also to automate the language learning process between computers and humans. The study cites evidence of deficiencies in such machine learning software and gadgets to prove that in spite of all technological advancements there remain areas of human brain and human intelligence where a computer or its software cannot enter. These deficiencies highlight the limitations of AI and super intelligence systems of machines to prove that human intelligence would always remain superior.

Exocortex as a Learning Technology

2019 ◽  
pp. 47-77 ◽  
Author(s):  
Mehmet Emin Mutlu
Keyword(s):  
Human Brain ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Management Approach ◽  
Learning Technology ◽  
Research Projects ◽  
Lifelong Learners ◽  
Computational Environment ◽  
Brain Interface ◽  
The Brain

Exocortex is a hypothetical technology where the human brain can connect to a brain implant or a computational environment which is in the state of a wearable device, using two-way brain-computer interface, in order to augment the cognitive powers of the human brain such as perception, storage, recollection and processing. Exocortex is expected to be a part of everyday life in the 2030s. Exocortex technology is supported by parallel technologies such as brain reading, uploading knowledge into the brain from the outside, brain-computer interface, brain-to-brain interface, which are now undergoing prototype applications. In this study, by discussing the potential of exocortex technology in its use for learning processes, as a result of handling it with the “learning experiences management” approach, the opportunities it provides specifically for lifelong learners are examined. In the results and recommendations section of the study, a foresight is given for the scientific research projects that can be performed for this purpose.

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