This book is a comprehensive guide to understanding the potential of artificial intelligence (AI) in improving business functions, as well as the limitations and challenges that come with its implementation. In this book, readers will learn about the various opportunities that AI presents in business, including how it can automate routine tasks, reduce errors, and increase efficiency. The book covers a range of topics, including how AI can be used in financial reporting, auditing, fraud detection, and tax preparation. However, the book also explores the limitations of AI in business, such as the need for skilled professionals, data quality, and the potential for bias. It examines the challenges that companies face when implementing AI in business functions, including the need for ethical considerations, transparency, and accountability. The book is written for business professionals, business leaders, and anyone interested in the potential of AI in business functions. It offers practical advice on how to implement AI effectively and provides insights into the latest developments in AI technology. Through case studies and real-world examples, readers will gain a deeper understanding of how AI can be used to enhance business functions, as well as the potential pitfalls and limitations to be aware of. Overall, this book is an essential guide for anyone looking to harness the power of AI to improve their business functions and to stay ahead in an increasingly competitive business environment.

The book, “Intelligent Computing - Proceedings of the 2022 Computing Conference”, is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world.
Each chapter is a paper presented at the Computing Conference 2022 held on July 14–15, 2022. Computing 2022 attracted a total of 498 submissions which underwent a double-blind peer-review process. Of those 498 submissions, 179 submissions have been selected to be included in this book.

This book addresses the history of artificial intelligence through the author’s experiences from the 1960s, when AI was a dream to give computers far more power than the progress for industrial technological advancement. The book starts from the AI pioneering days including what the author witnessed and impressed, then the episodes during AI boom of the 80s and 90s when the author was involved in ANSI X3J13 committee work as a principal member, translating Common Lisp books into Japanese, leading committee works in Japan for global standardization, and visiting MIT AI Lab for totally three years. The book points out that neural network research started in the 1980s, highlighting the DARPA report dated in 1988. The last episodes and thoughts include the experiences with business school students after the author moved from engineering school. The former half is from a view of an engineering mind and then the latter is based on how the author struggled with business-minded people to explain the core of AI.

"Mastering Large Language Models with Python" is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects.

This book researches the intricate world of generative Artificial Intelligence, offering readers an extensive understanding of various components and applications in this field.

In the world of industrial manufacturing and supply chain, the lack of real-time visibility and insights into processes poses a significant challenge. However, IoT is set to bring about a profound transformation. This technological revolution promises efficiency gains, operational optimization, and unprecedented business insights.

Explore the vast possibilities of integrating the ChatGPT API across various domains, from creating simple wrappers to developing knowledge-based assistants, multi-model applications, and conversational interfaces

Use active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fields

Join the data-centric revolution and master the concepts, techniques, and algorithms shaping the future of AI and ML development, using Python

Artificial Intelligence (AI) is defined as the simulation of human intelligence through the mimicking of the human brain for analysis, modeling, and decision‑making. Science and engineering problem solving requires modeling of physical phenomena, and humans approach the solution of scientific and engineering problems differently from other problems. Artificial Intelligence for Science and Engineering Applications addresses the unique differences in how AI should be developed and used in science and engineering. Through the inclusion of definitions and detailed examples, this book describes the actual and realistic requirements as well as what characteristics must be avoided for correct and successful science and engineering applications of AI.

The role of artificial intelligence in war is widely recognized, but is there also a role for AI in fostering peace and preventing conflict? AI for Peace provides a new perspective on AI as a potential force for good in conflict-affected countries through its uses for early warning, combating hate speech, human rights investigations, and analyzing the effects of climate change on conflict.

This book constitutes the refereed proceedings of the First International Conference on Recent Trends in AI Enabled Technologies, ThinkAI 2023, which took place in Hyderabad, India, in December 2023. The 7 full papers presented in these proceedings were carefully reviewed and selected from 51 submissions. The conference focuses on on up to date topics and recent trends in artificial intelligence and related technologies.

This two-volume set constitutes the proceedings of the Third International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022, which took place in Paris, France, in June 2022.
The 98 full papers presented were carefully reviewed and selected from 192 submissions. The papers present new advances in the field of pattern recognition and artificial intelligence. They are organized in topical sections as follows: pattern recognition; computer vision; artificial intelligence; big data.