scholarly journals A Generic Model of the World and Intelligence

10.29007/s6vh ◽  
2019 ◽  
Author(s):  
Harris Wang

The resurgence of interest in Artificial Intelligence and advances in several fronts of AI, machine learning with neural network in particular, have made us think again about the nature of intelligence, and the existence of a generic model that may be able to capture what human beings have in their mind about the world to empower them to present all kinds of intelligent behaviors. In this paper, we present Constrained Object Hierarchies (COHs) as such a generic model of the world and intelligence. COHs extend the well-known object-oriented paradigm by adding identity constraints, trigger constraints, goal constraints, and some primary methods that can be used by capable beings to accomplish various intelligence, such as deduction, induction, analogy, recognition, construction, learning and many others.In the paper we will first argue the need for such a generic model of the world and intelligence, and then present the generic model in detail, including its important constructs, the primary methods capable beings can use, as well as how different intelligent behaviors can be implemented and achieved with this generic model.

Author(s):  
Sercan Demirci ◽  
Durmuş Özkan Şahin ◽  
Ibrahim Halil Toprak

Skin cancer, which is one of the most common types of cancer in the world, is a malignant growth seen on the skin due to various reasons. There was an increase in the number of the cases of skin cancer nearly 200% between 2004-2009. Since the ozone layer is depleting, harmful rays reflected from the sun cannot be filtered. In this case, the likelihood of skin cancer will increase over the years and pose more risks for human beings. Early diagnosis is very significant as in all types of cancers. In this study, a mobile application is developed in order to detect whether the skin spots photographed by using the machine learning technique for early diagnosis have a suspicion of skin cancer. Thus, an auxiliary decision support system is developed that can be used both by the clinicians and individuals. For cases that are predicted to have a risk higher than a certain rate by the machine learning algorithm, early diagnosis could be initiated for the patients by consulting a physician when the case is considered to have a higher risk by machine learning algorithm.


Author(s):  
Sailesh Suryanarayan Iyer ◽  
Sridaran Rajagopal

Knowledge revolution is transforming the globe from traditional society to a technology-driven society. Online transactions have compounded, exposing the world to a new demon called cybercrime. Human beings are being replaced by devices and robots, leading to artificial intelligence. Robotics, image processing, machine vision, and machine learning are changing the lifestyle of citizens. Machine learning contains algorithms which are capable of learning from historical occurrences. This chapter discusses the concept of machine learning, cyber security, cybercrime, and applications of machine learning in cyber security domain. Malware detection and network intrusion are a few areas where machine learning and deep learning can be applied. The authors have also elaborated on the research advancements and challenges in machine learning related to cyber security. The last section of this chapter lists the future trends and directions in machine learning and cyber security.


Author(s):  
Anuraag Velamati Et.al

The world is quickly and continuously advancing towards better technological advancements that will make life quite easier for us, human beings [22]. Humans are looking for more interactive and advanced ways to improve their learning. One such dream is making a machine think like a computer, which lead to innovations like AI and deep learning [25]. The world is running at a higher pace in the domain of AI, deep learning, robotics and machine learning Using this knowledge and technology, we could develop anything right now [36]. As a part of sub-domain, the introduction of Convolution Neural Networks made deep learning extensively strong in the domain of image classification and detection [1]..The research that we have conducted is one of its kind. Our research used Convolution Neural Network, TensorFlow and Keras.


Author(s):  
Sanjay Saxena ◽  
Sudip Paul ◽  
Adhesh Garg ◽  
Angana Saikia ◽  
Amitava Datta

Computational neuroscience is inspired by the mechanism of the human brain. Neural networks have reformed machine learning and artificial intelligence. Deep learning is a type of machine learning that teaches computers to do what comes naturally to individuals: acquire by example. It is inspired by biological brains and became the essential class of models in the field of machine learning. Deep learning involves several layers of computation. In the current scenario, researchers and scientists around the world are focusing on the implementation of different deep models and architectures. This chapter consists the information about major architectures of deep network. That will give the information about convolutional neural network, recurrent neural network, multilayer perceptron, and many more. Further, it discusses CNN (convolutional neural network) and its different pretrained models due to its major requirements in visual imaginary. This chapter also deliberates about the similarity of deep model and architectures with the human brain.


Author(s):  
Madhura Kartik Naidu

The COVID-19 pandemic has not only affected the common man's life, but it has also affected many science, space, and technology institutions and government agencies all over the world. It has also resulted in reduced productivity of human beings and affected several organizations and government programs. The normal life of human beings came under a lot of restrictions and pressure due to lockdown. Many people lost their jobs and suffered financially as well as emotionally. The contribution of science and technology in this period of coronavirus crisis is key for facing current health challenges. Technological fields like data science, machine learning, and artificial intelligence have majorly contributed towards COVID-19. The present study aims to discuss the advancement and importance of technology used worldwide to fight against the COVID-19 pandemic at different levels.


Author(s):  
J.-M. Deltorn ◽  
Franck Macrez

A new generation of machine learning (ML) and artificial intelligence (AI) creative tools are now at the disposal of musicians, professionals and amateurs alike. These new technical intermediaries allow the production of unprecedented forms of compositions, from generating new works by mimicking a style or by mixing a curated ensemble of musical works to letting an algorithm complete one’s own creation in unexpected directions or by letting an artist interact with the parameters of a neural network to explore fresh musical avenues. Unsurprisingly, this new spectrum of algorithmic compositions question both the nature and the degree of involvement of the creator in the musical work. As a consequence, the issue of authorship and, in particular, the assessment of the specific contribution of a (human) creator through the algorithmic pipeline may require special scrutiny when AI and ML tools are used to produce musical works.


2019 ◽  
Author(s):  
Xia Huiyi ◽  
◽  
Nankai Xia ◽  
Liu Liu ◽  
◽  
...  

With the development of urbanization and the continuous development, construction and renewal of the city, the living environment of human beings has also undergone tremendous changes, such as residential community environment and service facilities, urban roads and street spaces, and urban public service formats. And the layout of the facilities, etc., and these are the real needs of people in urban life, but the characteristics of these needs or their problems will inevitably have a certain impact on the user's psychological feelings, thus affecting people's use needs. Then, studying the ways in which urban residents perceive changes in the living environment and how they perceive changes in psychology and emotions will have practical significance and can effectively assist urban management and builders to optimize the living environment of residents. This is also the long-term. One of the topics of greatest interest to urban researchers since then. In the theory of demand hierarchy proposed by American psychologist Abraham Maslow, safety is the basic requirement second only to physiological needs. So safety, especially psychological security, has become one of the basic needs of people in the urban environment. People's perception of the psychological security of the urban environment is also one of the most important indicators in urban environmental assessment. In the past, due to the influence of technical means, the study of urban environmental psychological security often relied on the limited investigation of a small number of respondents. Low-density data is difficult to measure the perceptual results of universality. With the leaping development of the mobile Internet, Internet image data has grown geometrically over time. And with the development of artificial intelligence technology in recent years, image recognition and perception analysis based on machine learning has become possible. The maturity of these technical conditions provides a basis for the study of the urban renewal index evaluation system based on psychological security. In addition to the existing urban visual street furniture data obtained through urban big data collection combined with artificial intelligence image analysis, this paper also proposes a large number of urban living environment psychological assessment data collection strategies. These data are derived from crowdsourcing, and the collection method is limited by the development of cost and technology. At present, the psychological security preference of a large number of users on urban street images is collected by forced selection method, and then obtained by statistical data fitting to obtain urban environmental psychology. Security sense training set. In the future, when the conditions are mature, the brainwave feedback data in the virtual reality scene can be used to carry out the machine learning of psychological security, so as to improve the accuracy of the psychological security data.


2020 ◽  
Author(s):  
Sandeep Reddy ◽  
Sonia Allan ◽  
Simon Coghlan ◽  
Paul Cooper

The re-emergence of artificial intelligence (AI) in popular discourse and its application in medicine, especially via machine learning (ML) algorithms, has excited interest from policymakers and clinicians alike. The use of AI in clinical care in both developed and developing countries is no longer a question of ‘if?’ but ‘when?’. This creates a pressing need not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort?


2021 ◽  
Vol 2021 (2) ◽  
pp. 19-23
Author(s):  
Anastasiya Ivanova ◽  
Aleksandr Kuz'menko ◽  
Rodion Filippov ◽  
Lyudmila Filippova ◽  
Anna Sazonova ◽  
...  

The task of producing a chatbot based on a neural network supposes machine processing of the text, which in turn involves using various methods and techniques for analyzing phrases and sentences. The article considers the most popular solutions and models for data analysis in the text format: methods of lemmatization, vectorization, as well as machine learning methods. Particular attention is paid to the text processing techniques, after their analyzing the best method was identified and tested.


2020 ◽  
pp. 97-102
Author(s):  
Benjamin Wiggins

Can risk assessment be made fair? The conclusion of Calculating Race returns to actuarial science’s foundations in probability. The roots of probability rest in a pair of problems posed to Blaise Pascal and Pierre de Fermat in the summer of 1654: “the Dice Problem” and “the Division Problem.” From their very foundation, the mathematics of probability offered the potential not only to be used to gain an advantage (as in the case of the Dice Problem), but also to divide material fairly (as in the case of the Division Problem). As the United States and the world enter an age driven by Big Data, algorithms, artificial intelligence, and machine learning and characterized by an actuarialization of everything, we must remember that risk assessment need not be put to use for individual, corporate, or government advantage but, rather, that it has always been capable of guiding how to distribute risk equitably instead.


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