Artificial Intelligence in Logistics

2019 ◽  
Vol 12 (1) ◽  
pp. 47-60
Author(s):  
László Kota
Keyword(s):  
Artificial Intelligence ◽  
Computing Power ◽  
Self Driving Cars

The artificial intelligence undergoes an enormous development since its appearance in the fifties. The computing power has grown exponentially since then, enabling the use of artificial intelligence applications in different areas. Since then, artificial intelligence applications are not only present in the industry, but they have slowly conquered households as well. Their use in logistics is becoming more and more widespread, just think of self-driving cars and trucks. In this paper, the author attempts to summarize and present the artificial intelligence logistical applications, its development and impact on logistics.

Developing an Artificial Intelligence Project in your Radiology Department

2020 ◽  
Vol 2 ◽  
pp. 58-61 ◽  
Author(s):  
Syed Junaid ◽  
Asad Saeed ◽  
Zeili Yang ◽  
Thomas Micic ◽  
Rajesh Botchu
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Health Care ◽  
Deep Learning ◽  
Learning Algorithms ◽  
Radiology Department ◽  
Short Article ◽  
Computing Power ◽  
Road Map ◽  
Key Concepts

The advances in deep learning algorithms, exponential computing power, and availability of digital patient data like never before have led to the wave of interest and investment in artificial intelligence in health care. No radiology conference is complete without a substantial dedication to AI. Many radiology departments are keen to get involved but are unsure of where and how to begin. This short article provides a simple road map to aid departments to get involved with the technology, demystify key concepts, and pique an interest in the field. We have broken down the journey into seven steps; problem, team, data, kit, neural network, validation, and governance.

The ideological divide in public perceptions of self-driving cars

2020 ◽  
Vol 29 (4) ◽  
pp. 436-451
Author(s):  
Yilang Peng
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Scientific Literacy ◽  
Autonomous Vehicles ◽  
The United States ◽  
Public Perceptions ◽  
New Information ◽  
Nationally Representative ◽  
Self Driving Cars ◽  
Social Conservatism

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars. Compared with liberals and Democrats, conservatives and Republicans express more concern about autonomous vehicles and more support for restrictively regulating autonomous vehicles. This ideological gap is largely driven by social conservatism. Moreover, both familiarity with driverless vehicles and scientific literacy reduce respondents’ concerns over driverless vehicles and support for regulation policies. Still, the effects of familiarity and scientific literacy are weaker among social conservatives, indicating that people may assimilate new information in a biased manner that promotes their worldviews.

Assessment of driving quality and its impact on changes in the technical condition of self-driving cars

2020 ◽  
pp. 24-26
Keyword(s):  
Artificial Intelligence ◽  
Life Cycle ◽  
Computer Technology ◽  
Technical Condition ◽  
Entire Life ◽  
Entire Life Cycle ◽  
Machine Maintenance ◽  
Current Task ◽  
Self Driving Cars

The article describes the current task of developing and improving existing technologies for machine maintenance throughout the entire life cycle. The use of modern achievements in the field of computer technology, digitization of information, as well as the development of artificial intelligence technologies, will allow you to get new scientific and engineering results aimed at managing the technical condition of machines in operation.

Design and Application of Innovative 3DVC in AI Server System

2021 ◽  
Author(s):  
Xianguang Tan ◽  
Yongzhan He ◽  
Bin Liu ◽  
Jiang Yu ◽  
Ahuja Nishi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Power Consumption ◽  
Heat Dissipation ◽  
Air Cooling ◽  
Computing Power ◽  
Advanced Phase ◽  
Cooling Technology ◽  
Saving Effect ◽  
Server System

Abstract With the accelerated application of cloud computing and artificial intelligence, the computing power and power consumption of chips are greatly enhanced, which brings severe challenges to heat dissipation. Based on this, Baidu has adopted advanced phase change cooling technology and successfully developed an innovative 3dvc air cooling scheme for AI server system. This paper introduces the design, test and verification of the innovative scheme in detail. The results show that the scheme can reduce the GPU temperature by more than 5 °C compared with the traditional heat pipe cooling scheme, save 30%+ of the fan power consumption, and achieve good cooling and energy saving effect.

Role of Artificial Intelligence (AI) in Surgery: Introduction, General Principles, and Potential Applications

2020 ◽  
Author(s):  
Alberto Mangano ◽  
Valentina Valle ◽  
Nicolas Dreifuss ◽  
Gabriela Aguiluz ◽  
Mario Masrur
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Tasks ◽  
Future Perspectives ◽  
General Introduction ◽  
Computing Power ◽  
Interdisciplinary Field ◽  
Potential Applications ◽  
Number Of Publications ◽  
Surgical Setting

AI (Artificial intelligence) is an interdisciplinary field aimed at the development of algorithms to endow machines with the capability of executing cognitive tasks. The number of publications regarding AI and surgery has increased dramatically over the last two decades. This phenomenon can partly be explained by the exponential growth in computing power available to the largest AI training runs. AI can be classified into different sub-domains with extensive potential clinical applications in the surgical setting. AI will increasingly become a major component of clinical practice in surgery. The aim of the present Narrative Review is to give a general introduction and summarized overview of AI, as well as to present additional remarks on potential surgical applications and future perspectives in surgery.

Rethinking Software Protection

2021 ◽  
pp. 341-362
Author(s):  
Peter R Slowinski
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Evolutionary Algorithms ◽  
Future Development ◽  
Computer Programs ◽  
Software Protection ◽  
Computing Power ◽  
The Core ◽  
Quantum Leap ◽  
Core Part

The core of artificial intelligence (AI) applications is software of one sort or another. But while available data and computing power are important for the recent quantum leap in AI, there would not be any AI without computer programs or software. Therefore, the rise in importance of AI forces us to take—once again—a closer look at software protection through intellectual property (IP) rights, but it also offers us a chance to rethink this protection, and while perhaps not undoing the mistakes of the past, at least to adapt the protection so as not to increase the dysfunctionality that we have come to see in this area of law in recent decades. To be able to establish the best possible way to protect—or not to protect—the software in AI applications, this chapter starts with a short technical description of what AI is, with readers referred to other chapters in this book for a deeper analysis. It continues by identifying those parts of AI applications that constitute software to which legal software protection regimes may be applicable, before outlining those protection regimes, namely copyright and patents. The core part of the chapter analyses potential issues regarding software protection with respect to AI using specific examples from the fields of evolutionary algorithms and of machine learning. Finally, the chapter draws some conclusions regarding the future development of IP regimes with respect to AI.

scholarly journals Artificial Intelligence and Health in Nepal

2020 ◽  
Vol 10 (3) ◽  
pp. 915-918
Author(s):  
Alexander Van Teijlingen ◽  
Tell Tuttle ◽  
Hamid Bouchachia ◽  
Brijesh Sathian ◽  
Edwin Van Teijlingen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
South Asian ◽  
Low Income ◽  
Short Communication ◽  
Data Sets ◽  
Low Income Country ◽  
Local Resources ◽  
Self Driving Cars ◽  
Key Terms

The growth in information technology and computer capacity has opened up opportunities to deal with much and much larger data sets than even a decade ago.  There has been a technological revolution of big data and Artificial Intelligence (AI).  Perhaps many readers would immediately think about robotic surgery or self-driving cars, but there is much more to AI.  This Short Communication starts with an overview of the key terms, including AI, machine learning, deep learning and Big Data.  This Short Communication highlights so developments of AI in health that could benefit a low-income country like Nepal and stresses the need for Nepal’s health and education systems to track such developments and apply them locally.  Moreover, Nepal needs to start growing its own AI expertise to help develop national or South Asian solutions.  This would require investing in local resources such as access to computer power/capacity as well as training young Nepali to work in AI. 

Artificial Intelligence (AI) Ethics

2020 ◽  
Vol 31 (2) ◽  
pp. 74-87 ◽  
Author(s):  
Keng Siau ◽  
Weiyu Wang
Keyword(s):  
Artificial Intelligence ◽  
Data Privacy ◽  
Ethical Issues ◽  
Well Being ◽  
Critical Issue ◽  
Ethical Principles ◽  
Machine Ethics ◽  
Moral Issues ◽  
Ai Ethics ◽  
Self Driving Cars

Artificial intelligence (AI)-based technology has achieved many great things, such as facial recognition, medical diagnosis, and self-driving cars. AI promises enormous benefits for economic growth, social development, as well as human well-being and safety improvement. However, the low-level of explainability, data biases, data security, data privacy, and ethical problems of AI-based technology pose significant risks for users, developers, humanity, and societies. As AI advances, one critical issue is how to address the ethical and moral challenges associated with AI. Even though the concept of “machine ethics” was proposed around 2006, AI ethics is still in the infancy stage. AI ethics is the field related to the study of ethical issues in AI. To address AI ethics, one needs to consider the ethics of AI and how to build ethical AI. Ethics of AI studies the ethical principles, rules, guidelines, policies, and regulations that are related to AI. Ethical AI is an AI that performs and behaves ethically. One must recognize and understand the potential ethical and moral issues that may be caused by AI to formulate the necessary ethical principles, rules, guidelines, policies, and regulations for AI (i.e., Ethics of AI). With the appropriate ethics of AI, one can then build AI that exhibits ethical behavior (i.e., Ethical AI). This paper will discuss AI ethics by looking at the ethics of AI and ethical AI. What are the perceived ethical and moral issues with AI? What are the general and common ethical principles, rules, guidelines, policies, and regulations that can resolve or at least attenuate these ethical and moral issues with AI? What are some of the necessary features and characteristics of an ethical AI? How to adhere to the ethics of AI to build ethical AI?

Augmenting Healthcare with Human-Centered Technologies

2020 ◽  
Vol 25 (4) ◽  
Author(s):  
Christopher Moehle ◽  
Jessica Gibson
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
Precision Medicine ◽  
Economic Factors ◽  
Central Theme ◽  
Business Cases ◽  
Self Driving Cars ◽  
High Level ◽  
Near Future

“Robotics”, “Artificial Intelligence”, and “Machine Learning” have become an almost impossibly broad amalgam of terminologies that span across industries to include everything from the cotton gin to self-driving cars, and touch a broad range of biotechnology and med tech applications.  We address the spread of these transformative technologies across every interpretation of the analogy, including the spectrum ranging from practical, highly economic products to inventive science fiction with speculative business cases.  In this two-part article, we first briefly overview the high-level commonalities between historically successful products and the economic factors driving adoption of these intelligent technologies in our current economy.  In doing so, we focus heavily on “Augmentation” as a central theme of the best products historically, now, and in the near future.  In the second part of the article, we further illustrate how “Augmented Intelligence” can be applied to biotech. This is done through a mini-case study, or a detailed practicum, on Ariel Precision Medicine, to illustrate how “Augmented Intelligence” can be applied to precision medicine currently.

scholarly journals Transparency and Fairness in Machine Learning Applications

2018 ◽  
Vol 4 (5) ◽  
pp. 443-463
Author(s):  
Jim Shook ◽  
Robyn Smith ◽  
Alex Antonio
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Reading Comprehension ◽  
New Technology ◽  
Human Intervention ◽  
Daily Work ◽  
Comprehension Test ◽  
The Future ◽  
Machine Learning Applications ◽  
Self Driving Cars

Businesses and consumers increasingly use artificial intelligence (“AI”)— and specifically machine learning (“ML”) applications—in their daily work. ML is often used as a tool to help people perform their jobs more efficiently, but increasingly it is becoming a technology that may eventually replace humans in performing certain functions. An AI recently beat humans in a reading comprehension test, and there is an ongoing race to replace human drivers with self-driving cars and trucks. Tomorrow there is the potential for much more—as AI is even learning to build its own AI. As the use of AI technologies continues to expand, and especially as machines begin to act more autonomously with less human intervention, important questions arise about how we can best integrate this new technology into our society, particularly within our legal and compliance frameworks. The questions raised are different from those that we have already addressed with other technologies because AI is different. Most previous technologies functioned as a tool, operated by a person, and for legal purposes we could usually hold that person responsible for actions that resulted from using that tool. For example, an employee who used a computer to send a discriminatory or defamatory email could not have done so without the computer, but the employee would still be held responsible for creating the email. While AI can function as merely a tool, it can also be designed to act after making its own decisions, and in the future, will act even more autonomously. As AI becomes more autonomous, it will be more difficult to determine who—or what—is making decisions and taking actions, and determining the basis and responsibility for those actions. These are the challenges that must be overcome to ensure AI’s integration for legal and compliance purposes.

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