Emerging trends in artificial intelligence :integrating theories and practice /

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Emerging trends in artificial intelligence :integrating theories and practice /

Chiroma, Haruna, - Personal Name; Institute of Physics (Great Britain), - Personal Name;

"Version: 20250501"--Title page verso.Includes bibliographical references.1. Artificial intelligence history from the abacus through science fiction movies and artificial intelligence winter to future expectations -- 1.1. Introduction -- 1.2. Previously published history of artificial intelligence -- 1.3. Era of mechanical operations leading to computers -- 1.4. Innovations and discoveries from the perspective of artificial intelligence -- 1.5. Artificial intelligence in science fiction movies that turned into reality -- 1.6. The cycle of artificial intelligence winter, innovations and renewed interest -- 1.7. Artificial intelligence future expectations -- 1.8. Industrial applications and case study -- 1.9. Summary -- 1.10. Organization of the book2. Generative artificial intelligence : gateway and recent progress -- 2.1. Introduction -- 2.2. Generative tasks -- 2.3. Generative models -- 2.4. The taxonomy of generative models -- 2.5. Comparative analysis of the generative models : weaknesses and strengths -- 2.6. Integrating generative models to enhance performance -- 2.7. The pipeline for developing a generative tool -- 2.8. Deepfakes -- 2.9. Generative models in pharmaceuticals -- 2.10. Prompt engineering -- 2.11. Industry applications and case studies -- 2.12. Summary3. Artificial general intelligence and beyond : large language models tutorial, debates, hypothesis and future outlook -- 3.1. Introduction -- 3.2. Human-level general intelligence -- 3.3. Attempt to AGI development via symbolic AI -- 3.4. The LLMs tutorial : fundamentals of LLMs -- 3.5. Developing large language models from the scratch -- 3.6. Comparing large language models to machine learning and deep learning -- 3.7. Artificial general intelligence versus human-level intelligence -- 3.8. Artificial superintelligence -- 3.9. Intellectual debates -- 3.10. Timelines expected to achieve artificial general intelligence -- 3.11. Industrial applications and case studies -- 3.12. Current status, challenges and future outlook -- 3.13. Risk -- 3.14. Summary4. AI-DevOps : proposed artificial intelligence enhanced development and operations lifecycle -- 4.1. Introduction -- 4.2. The traditional software development approach -- 4.3. The traditional development and operations -- 4.4. Motivation for artificial intelligence-assisted development and operations -- 4.5. Artificial intelligence accelerating development and operations lifecycle -- 4.6. Accelerating security in development and operations via large language models -- 4.7. Industrial applications and case studies -- 4.8. Summary5. Centralized huge graph neural networks advances -- 5.1. Introduction -- 5.2. Fundamentals of graph and artificial neural networks -- 5.3. Categories of graph neural network -- 5.4. Graph neural network hyper-parameter settings and parameters tuning -- 5.5. Published surveys and tutorials on graph neural networks -- 5.6. Datasets suitable for graph neural networks -- 5.7. Software platform for running graph neural networks -- 5.8. Industrial applications -- 5.9. Case studies -- 5.10. Discussion -- 5.11. Limitations and future direction -- 5.12. Summary6. Brain-machine interface for autonomous robots control with feedback from augmented reality and its relevance to industry 4.0 and 5.0 -- 6.1. Introduction -- 6.2. Autonomous robots -- 6.3. Robotics components -- 6.4. Robotic brain -- 6.5. Robotics programming, modelling and simulation -- 6.6. Deliberation function -- 6.7. Types of autonomous robots -- 6.8. Brain-machine interface -- 6.9. Brain-controlled autonomous robot -- 6.10. Augmented reality -- 6.11. Autonomous robots, augmented reality and BMI in industry 4.0 and 5.0 -- 6.12. Case study -- 6.13. Summary7. Recent developments in artificial intelligence and high-performance computing -- 7.1. Introduction -- 7.2. Autonomous robotics surgery -- 7.3. Readiness status levels of robotic autonomy surgery in clinical practice -- 7.4. High-performance computing -- 7.5. Quantum theory -- 7.6. Quantum computing -- 7.7. Decentralized blockchain technology -- 7.8. Carbon-aware computing -- 7.9. Case study -- 7.10. Summary8. Explainable artificial intelligence tailored to emerging concepts linking human acceptability -- 8.1. Introduction -- 8.2. Why explainable artificial intelligence? -- 8.3. Integrating interpretation and explainability into machine learning models -- 8.4. Stakeholders -- 8.5. Explainable artificial intelligence methods -- 8.6. Emerging concept linking to human acceptability -- 8.7. Industry applications and case studies -- 8.8. Summary9. Proposed bibliometric methods for artificial intelligence domain and bibliometric analysis on artificial intelligence for over six decades -- 9.1. Introduction -- 9.2. Bibliometric analysis theoretical background -- 9.3. Theories of scientific change -- 9.4. Performance analysis -- 9.5. Science mapping -- 9.6. Bradford law -- 9.7. Previously published bibliometric analysis -- 9.8. Methodology -- 9.9. Bibliometric software tools -- 9.10. Results and discussion -- 9.11. Industrial applications and case studies -- 9.12. Summary.Full-text restricted to subscribers or individual document purchasers.Emerging Artificial Intelligence: Integrating theories and practice is specifically tailored for researchers in AI who are eager to delve into the latest developments and explore the integration of theoretical concepts with practical applications. This book is an essential guide for researchers in AI seeking to bridge the gap between theory and practice, embark on a transformative journey through the latest advancements in AI and gain a comprehensive understanding of their real-world applications. After reading the book, the reader will be able to clearly understand the industrial applications of each emerging AI domain and appreciate the operations of AI in industry as well as society in general. Part of IOP Series in Next Generation Computing.Students and researchers in academia and industry.Also available in print.Mode of access: World Wide Web.System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.Haruna Chiroma received a PhD in artificial intelligence from University of Malaya. He received BTech and MSc in computer science from Abubakar Tafawa Balewa University and Bayero University, respectively. He is ranked in the Top 2% most influential scientists by Stanford University. He is an academic editor of Computational and Mathematical Methods in Medicine, associate editor for IEEE Access 2018-2021, an editorial board member of IAES International Journal of Artificial Intelligence, (Scopus Indexed), Associate Editor of TELKOMNIKA, Indonesia, (Scopus Indexed), Editorial board member of Recent advances in Computer Science and Communications, (Scopus Indexed). He was a guest editor of three special issues in ISI/Scopus indexed journals, and Editor of three edited Books by Springer, Berlin Heidelberg, and one co-authored book to be published by IOP Publishing. His research interests include: artificial neural networks, machine learning, deep learning, nature inspired algorithms, robotics, NLP and IoT. He has published over 140 academic articles relevant to his research interests in ISI WoS/Scopus indexed journals including but not limited to Neural Network World, Artificial Intelligence Review (Springer), Applied Soft Computing (Elsevier), Neural Computing and Applications (Springer), Expert systems with applications (Elsevier), Intelligent Automation and Soft Computing (Taylor & Francis), Supercomputing (Springer). He is an invited reviewer for over 60 ISI WoS/Scopus indexed journals such as IEEE Transactions on Neural Networks and Learning Systems, Artificial Intelligence Review (Springer), Applied Soft Computing (Elsevier), Expert Systems with Applications (Elsevier), Knowledge-Based System (Elsevier), Soft Computing (Springer), International Journal of Bioinspired Computation (Interscience), Neural Computing and Applications (Springer), etc. He has been a technical programme committee member for more than 30 international conferences.Title from PDF title page (viewed on June 2, 2025).

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Series Title: -
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Publisher: : .,
Collation: 1 online resource (various pagings) :illustrations (some color).
Language: English
ISBN/ISSN: 9780750363204
Classification: 006.3
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Edition: -
Subject(s): Machine learning.
Artificial intelligence
Artificial Intelligence.
COMPUTERS / Data Science / Machine Learning.
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Statement of Responsibility: Haruna Chiroma.

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