Artificial intelligence is a word that carries with it heavy connotations. Although artificial intelligence is nothing more than the capacity for logic and understanding that machines can exhibit, in the minds of most people artificial intelligence is almost a Pandora's box that, when opened, will eventually signal the human race's doom..
The idea that machines pose an existential threat to human beings has been around for at least 60 years. It goes something like this: intelligent machines eventually realize the uselessness of human beings and turn against their creators. Or this: intelligent machines reduce human to cattle or even food after a dramatic war that human beings lose.
Human beings have created countless languages and writing systems that have allowed us to expand collective human knowledge over a period of thousands of years. Much of the knowledge that we utilized today, knowledge about the math, science, and the stars, originates from observations made thousands of years ago but which were recorded by writing systems, allowing this knowledge to be preserved and passed down.
Artificial intelligence has been used for many business, financial, medical, and other applications, and scientists and researchers are actively studying how these applications can be expanded to make human life simpler.
The applications of AI will be explored in this book, both the real applications to business, finance, medicine, and health and the theoretical applications. Even the sensational, perhaps exaggerated applications of AI will be explored in the context of taking a look at how AI may potentially be applied in the future. The purpose of this discussion is for the reader to understand what AI is by understanding how it is used.
Artificial intelligence is certainly a blessing at this point, but the reality that it may become a curse is not lost on some people. Understanding the full implications of AI requires a deep knowledge of what it is and where it came from.
For companies and businesses to take advantage of AI-powered and improved interactions, the conversation has to begin inside the organization. Leaders are supposed to start with the available channels and improve their smartness. From that point, they are supposed to ask key questions about engagements with customers and employees.
Here is a preview of what you will learn...
Brief history of artificial intelligence
The state of art of machine learning
Artificial neural networks applied to machine learning
How can we build an AI ready culture
Our daily lives with AI
And More.....
Автор: Das, S.K., Das, S.P., Dey, N., Hassanien, A.-E. Название: Machine Learning Algorithms for Industrial Applications ISBN: 3030506401 ISBN-13(EAN): 9783030506407 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics.
Описание: This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies.
Описание: This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.
Описание: This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. The book is useful as a reference book for machine learning researchers and professionals as well as machine intelligence enthusiasts.
Описание: This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics.
Описание: Assesses the challenges, limitations, and potential solutions for creating more sustainable and agile industrial systems. This publication presents recent intelligent systems for a wide range of industrial applications and smart safety measures toward industrial systems.
Автор: Reinhard Dummer; Mark R. Pittelkow; Keiji Iwatsuki Название: Skin Cancer - A World-Wide Perspective ISBN: 3662518554 ISBN-13(EAN): 9783662518557 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Over the last decades the incidence of skin cancers is dramatically increasing world-wide. This is not only confined to the incidence of melanoma but includes also other skin cancers such as basal cell carcinomas. Based on the recent WHO classification of skin cancers, this lavishly illustrated reference book covers comprehensively the epidemiology, histology and pathology, as well as diagnostic signs and treatment options of skin cancers. Homogenously and reader-friendly structured, it links the diagnostic and genetic features of each disease in order to guide the reader to the most appropriate therapeutic strategies for the best possible treatment outcome. In order to demonstrate the world wide activities in the field, all chapters cover the variations of the individual experiences and expertise in different nations.
The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.
Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.
Автор: Zhang Yinyan, Li Shuai Название: Machine Behavior Design and Analysis: A Consensus Perspective ISBN: 9811532303 ISBN-13(EAN): 9789811532306 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
1 Introduction to Collective Machine Behavior
1.1 Collective Machine Behavior
1.2 Consensus
1.3 Theoretical Tools
1.4 Chapter Summary
References
2 Second-Order Min-Consensus
2.1 Introduction
2.2 Preliminary and Problem Formulation
2.3 Min-Consensus Under Switching Topology
2.4 Simulation Example
2.5 Chapter Summary
References
3 Consensus of High-Order Discrete-TimeMulti-Agent Systems
3.1 Introduction
3.2 Problem Description
3.3 Protocol Design
3.4 Theoretical Results
3.5 Illustrative Examples
3.6 Chapter Summary
References
4 Continuous-Time Biased Min-Consensus
4.1 Introduction
4.2 Background
4.3 Biased Min-Consensus
4.4 Equivalence to Shortest Path Planning
4.5 Simulations and Applications
4.6 Conclusions
References
5 Discrete-Time Biased Min-Consensus
5.1 Introduction
5.2 Preliminary
5.3 Discrete-Time Biased Min-Consensus
5.4 Algorithms
5.5 Numerical Investigations
5.6 Applications
5.7 Chapter Summary
References
6 Biased Consensus Based Distributed Neural Network
6.1 Introduction
6.2 Problem Formulation
6.3 Unified Scheme
6.4 Theoretical Results
6.5 Illustrative Examples
6.6 Extension to Path Planning of Mobile Robots
6.7 Chapter Summary
References
7 Predictive Suboptimal Consensus
7.1 Introduction
7.2 Preliminary
7.3 Control Law Design
7.4 Theoretical Results
7.5 Simulation Investigation
7.6 Chapter Summary
References
8 Adaptive Near-Optimal Consensus
8.1 Introduction
8.2 Problem Formulation
8.3 Nominal Near-Optimal Design
8.4 Adaptive Near-Optimal Design
8.5 Illustrative Example
8.6 Chapter Summary
References
Автор: Das Santosh Kumar, Das Shom Prasad, Dey Nilanjan Название: Machine Learning Algorithms for Industrial Applications ISBN: 3030506436 ISBN-13(EAN): 9783030506438 Издательство: Springer Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics.
Описание: In Facing Cancer and the Fear of Death: A Psychoanalytic Perspective on Treatment, Dr. Norman Straker proposes that "death anxiety" is responsible for the American society`s failure to address costly futile care at the end of life.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
