Название: Cognitive Computing for Machine Thinking
Автор: Makarand R. Velankar, Parikshit N. Mahalle, Gitanjali R. Shinde
Издательство: Springer
Год: 2024
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 10.1 MB

This book presents cognitive modeling along with the new paradigm machine thinking to enhance existing AI power and address its current limitations. This book provides overview of natural and Artificial Intelligence (AI) along with the computing models used currently. The need of advancing the current models is presented with suitable examples. The business case studies presented in different domains provide possible use of augmented intelligence with the proposed machine thinking paradigm.

Cognitive computing has grabbed the attention of researchers recently. It deals with the human mind and thinking to make appropriate decisions considering human psychology. The current AI models are mainly based on data-driven models and require huge data to train the models. The issues that need to be tackled by AI models include fairness, deviation from intended objectives, ethical principles, sensitive information and security, performance disparity, privacy, and copyrights. Challenge is to align the AI models to perform in the right manner especially to the critical decision-making systems such as legal or medical applications. An augmented intelligent model with embedded cognitive computing and machine thinking paradigm can be a possible approach to tackle the current limitations of AI and advance the research in computing domain. Machine thinking is the new paradigm shift proposed in this book. The challenges in machine thinking are understanding and modeling the cognitive thinking process of humans that are discussed. The proposed paradigm will be useful in improving AI application performance which involves human cognition.

This book is targeted at academicians, researchers, students, and professionals who belong to disciplines which involve intelligent computing and modeling human thinking. It provides possible multidisciplinary research directions including social psychology, Artificial Intelligence, human–computer interaction (HCI), and cognition for applications in various domains.

There is a growing interest in the field of Artificial Intelligence (AI) and Machine Learning, and with that interest comes a need for a better understanding of how machines think. A book on machine thinking could be an important resource for individuals who want to learn more about this field, including researchers, engineers, and anyone who is interested in the potential applications of AI and machine learning. This book helps individuals understand the capabilities and limitations of machines, including how they process information and make decisions. This knowledge could be crucial for individuals who are working on developing new AI systems or who are incorporating AI into their businesses or organizations. This book also explores the future of this rapidly evolving field. As new technologies emerge and new applications for AI are developed, it is important for individuals to stay up to date on the latest developments and to be prepared for the changes that lie ahead. A book on machine thinking could be an important resource for individuals who want to stay informed and engaged with this dynamic field.

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