Artificial Intelligence Theory For Management
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Artificial Intelligence Theory For Management
This is an introductory book about Artificial Intelligence Theory based on Service Science. It is not for AI specialists. It is too simple for them. As unusual as it sounds, there is a very good reason for its existence. There are existing books on the subject that are very good but are very difficult to read. Its that simple. The concepts are complicated and some require complex math. A typical example is the subject of neural networks. A person should know what theory governs the new field of artificial intelligence, because we will be involved if only at the listening level or going into a meeting. Artificial Intelligence is here to stay this time. It’s a third try to bring the subject to the forefront. It is here for the future, and it is here to stay because the world needs it. We are in the midst of war, preparation for defense, a dismal economic outlook, crime, killing, and so forth. We need it because if we continue the way we are going, we won’t be going anywhere for very long. Practically everything is disarray. Just name them: violence, shady politics, global warming, discrimination, abortion, women’s birth problems, men’s cancer. What is the solution? It is twofold. Equitably use the information we have and permit the human race to communicate and act in a reasonable manner. Through Artificial Intelligence, often referred to as AI, we have the key to managing our lives on a daily basis – worldwide. There is a lot going on in the area of AI, as it’s called. Young people all over the place are into it. New software is being developed. There is a generative AI system named ChatGPT developed by a company named OpenAI that has done a good job with new developments. What is a manager to do. A company named IBM is in the field with a system called IBM Watson, that operates out of the cloud is also in the game. In fact, this book can give you some insight into what is going on. It contains three snippets on ChatGPT, IBM Watson, and Data Science that are included at the end of the book. Instead of business and government leaders having to tell us what they are going to do, we can and will be addressing that subject through AI. AI is a systems concept, not a single piece of software you can buy at a local store. Can you imagine a kid telling you they have computers and AI, meaning software apps. You will be able to obtain AI capability but it needs to be blended into the infrastructure to its host organization. A good example is the Watson System developed by IBM. It can, will, and has done wonders with design and analytics, but you probably will need some help in employing the computational infrastructure. There are already competition systems but Watson is mentioned because it beat some Jeopardy! champions at their own game. So, here is what we are providing to you with in this book. A straightforward description of the subject of AI that is easy to read. No more and no less. You can jump into this book at any point and get something out of it. In addition, you will get a quick survey of Service Science. After all, Artificial Intelligence is a service In the best sense of the word. The book is not expensive and something you would enjoy giving to a relative or friend. The book adheres to the author’s principle of no sex, no violence, and no bad language. It is accessible to all readers. This need not be said for a book of this type, but I like saying it.
Project Management – an Artificial Intelligent (Ai) Approach
Author: Kim Hin David HO
language: en
Publisher: Partridge Publishing Singapore
Release Date: 2020-08-04
This book is a novel treatment of modern project management from artificial intelligence (AI), entailing data analytics, neural networks, fuzzy logic, genetic algorithms; and data visualisation deploying agent based modelling for the knowledge based urban development (KBUD). The book can be adopted by design engineers, urban planners, project managers, quantity and real estate surveyors, public and private real estate developers, architects and scholars. Chapter 1 discusses that the traditional statistical method, which needs a priori parametric knowledge of linear or non-linear functions between the input and output variables. Nneural networks do not need such information to predict future possible outcomes. Chapter 2 reiterates that new private office and residential supply like in Hong Kong depend on current market prices, relative to the replacement or building costs. The market should equate prices with replacement costs that include the cost of land. Prices and costs may diverge because of lags and delays in the building process. Chapter 3 discusses the specific tasks to be planned to develop life cycle models and metrics to analyse technology and innovation. Such models can look into life cycle cost analysis (LCA). Chapter 4 draws attention to the trend that in a highly volatile world, the best point estimate of classical DCF model is not a reliable indication of investment worth. The fuzzy discounted cash flow (DCF) model offers a natural and intuitive way, based on a set of fuzzy inputs. The fuzzy net present value (NPV) for an office-cum-retail development is so estimated to provide the approximated evaluation of investment worth. Chapter 5 discusses the fuzzy tactical asset allocation (FTAA) model, incorporating intuitive decision making into the direct real estate project (asset) allocation process, from the expert investor prospective. The FTAA model improves the efficiency of asset allocation, adopting fuzzy set theory and fuzzy optimization theory. Chapter 6 reiterates that today’s city planners see the KBUD strategy as a new form of urban renewal for industrial cities. Planners believe KBUDs bring economic, technological progress and sustainable socio-spatial order to the contemporary city. Chapter 6 addresses the need for an urban design criterion that aids in efficient land use planning for KBUDs.
Management, Organisations and Artificial Intelligence
This book combines academic research with practical guidelines in methods and techniques to supplement existing knowledge relating to organizational management in the era of digital acceleration. It offers a simple layout with concise but rich content presented in an engaging, accessible style and the authors’ holistic approach is unique in the field. From a universalist perspective, the book examines and analyzes the development of, among others, Industry 4.0, artificial intelligence (AI), AI 2.0, AI systems and platforms, algorithmics, new paradigms of organization management, business ecosystems, data processing models in AI-based organizations and AI strategies in the global perspective. An additional strength of the book is its relevance and contemporary nature, featuring information, data, forecasts or scenarios reaching up to 2030. How does one build, step by step, an organization that will be based on artificial intelligence technology and gain measurable benefits from it, for instance, as a result of its involvement in the creation of the so-called mesh ecosystem? The answer to this and many other pertinent questions are provided in this book. This timely and important book will appeal to scholars and students across the fields of organizational management and innovation and technology management, as well as managers, educators, scientists, entrepreneurs, innovators and more.