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| artificial intelligence document management: Intelligent Document Processing (IDP): A Comprehensive Guide to Streamlining Document Management Rick Spair, The world of document management is evolving rapidly, and organizations are increasingly turning to Intelligent Document Processing (IDP) to streamline their document management processes. This comprehensive guide serves as a valuable resource for individuals and organizations embarking on their IDP journey. It offers a step-by-step approach, practical tips, and best practices to help readers successfully implement IDP and achieve significant improvements in efficiency, accuracy, and cost savings. In today's digital age, the volume and complexity of documents continue to grow exponentially, posing significant challenges for organizations across industries. Traditional manual document management processes are time-consuming, error-prone, and resource-intensive, leading to inefficiencies and missed opportunities. However, the advent of Intelligent Document Processing (IDP) presents a game-changing solution. Intelligent Document Processing combines the power of artificial intelligence, machine learning, and automation technologies to extract and process data from unstructured documents swiftly and accurately. By automating manual tasks, organizations can enhance productivity, improve data accuracy, and optimize their document management workflows. This guide serves as a roadmap for readers looking to harness the potential of IDP and transform their document management practices. The chapters of this guide take readers on a comprehensive journey through the world of IDP. It begins with an introduction to document management and the concept of Intelligent Document Processing. Readers will gain a clear understanding of the benefits and importance of implementing IDP in their organizations. The guide then delves into the key aspects of implementing IDP. It covers topics such as assessing document management needs, identifying document types and formats, analyzing document volume and complexity, and evaluating existing document management processes. These chapters provide practical insights, tips, and strategies to help readers assess their current state and identify areas for improvement. As the journey progresses, the guide dives into creating an IDP strategy, including setting clear goals and objectives, selecting the right IDP solution, and defining key performance indicators (KPIs). It emphasizes the importance of customization and adaptation to align with specific organizational needs and goals. The guide further explores preparing documents for IDP, including standardizing formats and layouts, optimizing image quality and resolution, and implementing document classification and indexing. It provides detailed guidance on leveraging intelligent capture technologies, extracting data from structured and unstructured documents, and validating and verifying extracted data. The chapters also cover crucial aspects such as integrating IDP with existing systems, monitoring and measuring IDP performance, change management, and user adoption. They address data security and compliance requirements, as well as provide real-world case studies and success stories to inspire and educate readers. Throughout the guide, readers will find tips, recommendations, and best practices from industry leaders who have successfully implemented IDP. These insights serve as valuable lessons learned and provide practical guidance for readers as they embark on their IDP journey. In conclusion, this comprehensive guide equips readers with the knowledge and tools needed to implement Intelligent Document Processing successfully. By following the chapters, tips, recommendations, and strategies outlined in this guide, organizations can streamline their document management processes, achieve significant improvements in efficiency and accuracy, and drive tangible business outcomes. The IDP journey begins here, offering endless possibilities for optimizing document management in the digital era. |
| artificial intelligence document management: Artificial Intelligence for Healthcare Applications and Management Boris Galitsky, Saveli Goldberg, 2022-01-19 Current conditions affected by COVID-19 pose new challenges for healthcare management and learning how to apply AI will be important for a broad spectrum of students and mature professionals working in medical informatics. . |
| artificial intelligence document management: Practical Artificial Intelligence and Blockchain Ganesh Prasad Kumble, 2020-07-31 Learn how to use AI and blockchain to build decentralized intelligent applications (DIApps) that overcome real-world challenges Key FeaturesUnderstand the fundamental concepts for converging artificial intelligence and blockchainApply your learnings to build apps using machine learning with Ethereum, IPFS, and MoiBitGet well-versed with the AI-blockchain ecosystem to develop your own DIAppsBook Description AI and blockchain are two emerging technologies catalyzing the pace of enterprise innovation. With this book, you’ll understand both technologies and converge them to solve real-world challenges. This AI blockchain book is divided into three sections. The first section covers the fundamentals of blockchain, AI, and affiliated technologies, where you’ll learn to differentiate between the various implementations of blockchains and AI with the help of examples. The second section takes you through domain-specific applications of AI and blockchain. You’ll understand the basics of decentralized databases and file systems and connect the dots between AI and blockchain before exploring products and solutions that use them together. You’ll then discover applications of AI techniques in crypto trading. In the third section, you’ll be introduced to the DIApp design pattern and compare it with the DApp design pattern. The book also highlights unique aspects of SDLC (software development lifecycle) when building a DIApp, shows you how to implement a sample contact tracing application, and delves into the future of AI with blockchain. By the end of this book, you’ll have developed the skills you need to converge AI and blockchain technologies to build smart solutions using the DIApp design pattern. What you will learnGet well-versed in blockchain basics and AI methodologiesUnderstand the significance of data collection and cleaning in AI modelingDiscover the application of analytics in cryptocurrency tradingGet to grips with open, permissioned, and private blockchainsExplore the DIApp design pattern and its merit in digital solutionsFind out how LSTM and ARIMA can be applied in crypto tradingUse the DIApp design pattern to build a sample contact tracing applicationGet started with building your own DIApps across various domainsWho this book is for This book is for blockchain and AI architects, developers, data scientists, data engineers, and evangelists who want to harness the power of artificial intelligence in blockchain applications. If you are looking for a blend of theoretical and practical use cases to understand how to implement smart cognitive insights into blockchain solutions, this book is what you need! Knowledge of machine learning and blockchain concepts is required. |
| artificial intelligence document management: AI-Powered Productivity Asma Asfour, 2024-08-06 AI-Powered Productivity is a guide to understanding and using AI and generative tools in professional settings. Chapter 1 introduces AI basics, its impact on various sectors, and an overview of generative AI tools. Chapter 2 delves into large language models exploring their integration with multimodal technologies and effects on productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, with tutorials on crafting effective prompts and advanced techniques, including real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 addresses data-driven decision-making, covering data analysis techniques, AI in trend identification, consumer behavior analysis, strategic planning, and product development. Chapter 6 discusses strategic and ethical considerations, including AI feasibility, tool selection, multimodal workflows, and best practices for ethical AI development and deployment. Chapter 7 highlights AI's role in transforming training and professional development, covering structured training programs, continuous learning initiatives, and fostering a culture of innovation and experimentation. Chapter 8 provides a guide to successfully implementing AI in organizations, discussing team composition, collaborative approaches, iterative development processes, and strategic alignment for AI initiatives. Finally, Chapter 9 looks ahead to the future of work, preparing readers for the AI revolution by addressing training and education, career paths, common fears, and future workforce trends. This book is designed for both beginners and professionals, offering a deep dive into AI concepts, tools, and practices that define the current AI landscape. |
| artificial intelligence document management: AI for Accountants: Artificial Intelligence for Financial Management and Control DIZZY DAVIDSON, 2024-09-02 Are you struggling to fully understand how AI can revolutionize your accounting practice? Are you looking to harness the power of artificial intelligence but don’t know where to start? “AI for Accountants: Artificial Intelligence for Financial Management and Control” is your definitive guide to navigating the complexities of AI in the accounting world. This book demystifies AI, providing clear, actionable insights into how AI can transform your financial management processes. From automating data entry to enhancing fraud detection, this comprehensive guide covers it all. Benefits of Reading This Book: Efficiency: Learn how AI can automate repetitive tasks, freeing up your time for strategic decision-making. Accuracy: Discover AI tools that reduce errors and improve the accuracy of financial data. Compliance: Stay ahead of regulatory changes with AI-driven compliance solutions. Insight: Gain deeper insights into financial trends and customer behavior through advanced analytics. Why This Book is Essential: Comprehensive Coverage: Covers all aspects of AI in accounting, from basic concepts to advanced applications. Practical Examples: Real-world case studies and examples to illustrate AI applications. Expert Insights: Written by industry experts with deep knowledge of both AI and accounting. Future-Proofing: Prepare your practice for the future by understanding the latest AI trends and technologies. Key Topics Covered: Automating Data Entry Fraud Detection Financial Forecasting Expense Management Tax Compliance Continuous Auditing Invoice Processing Customer Insights Risk Management Financial Reporting Budgeting Personalized Financial Advice Call to Action: Don’t get left behind in the AI revolution. Get your copy of “AI for Accountants: Artificial Intelligence for Financial Management and Control” today and unlock the full potential of AI in your accounting practice. Equip yourself with the knowledge and tools to stay ahead in the rapidly evolving world of finance. |
| artificial intelligence document management: Conversational Artificial Intelligence Romil Rawat, Rajesh Kumar Chakrawarti, Sanjaya Kumar Sarangi, Anand Rajavat, Mary Sowjanya Alamanda, Kotagiri Srividya, K. Sakthidasan Sankaran, 2024-01-30 This book reviews present state-of-the-art research related to the security of cloud computing including developments in conversational AI applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in advanced security solutions for conversational AI in the cloud platform domain by reviewing present and evolving security solutions, their limitations, and future research directions. Conversational AI combines natural language processing (NLP) with traditional software like chatbots, voice assistants, or an interactive voice recognition system to help customers through either a spoken or typed interface. Conversational chatbots that respond to questions promptly and accurately to help customers are a fascinating development since they make the customer service industry somewhat self-sufficient. A well-automated chatbot can decimate staffing needs, but creating one is a time-consuming process. Voice recognition technologies are becoming more critical as AI assistants like Alexa become more popular. Chatbots in the corporate world have advanced technical connections with clients thanks to improvements in artificial intelligence. However, these chatbots’ increased access to sensitive information has raised serious security concerns. Threats are one-time events such as malware and DDOS (Distributed Denial of Service) assaults. Targeted strikes on companies are familiar and frequently lock workers out. User privacy violations are becoming more common, emphasizing the dangers of employing chatbots. Vulnerabilities are systemic problems that enable thieves to break in. Vulnerabilities allow threats to enter the system, hence they are inextricably linked. Malicious chatbots are widely used to spam and advertise in chat rooms by imitating human behavior and discussions, or to trick individuals into disclosing personal information like bank account details. |
| artificial intelligence document management: Artificial Intelligence and Cognitive Sciences Jacques Demongeot, 1988 |
| artificial intelligence document management: The Dictionary of Artificial Intelligence Utku Taşova, 2023-11-03 Unveiling the Future: Your Portal to Artificial Intelligence Proficiency In the epoch of digital metamorphosis, Artificial Intelligence (AI) stands as the vanguard of a new dawn, a nexus where human ingenuity intertwines with machine precision. As we delve deeper into this uncharted realm, the boundary between the conceivable and the fantastical continually blurs, heralding a new era of endless possibilities. The Dictionary of Artificial Intelligence, embracing a compendium of 3,300 meticulously curated titles, endeavors to be the torchbearer in this journey of discovery, offering a wellspring of knowledge to both the uninitiated and the adept. Embarking on the pages of this dictionary is akin to embarking on a voyage through the vast and often turbulent seas of AI. Each entry serves as a beacon, illuminating complex terminologies, core principles, and the avant-garde advancements that characterize this dynamic domain. The dictionary is more than a mere compilation of terms; it's a labyrinth of understanding waiting to be traversed. The Dictionary of Artificial Intelligence is an endeavor to demystify the arcane, to foster a shared lexicon that enhances collaboration, innovation, and comprehension across the AI community. It's a mission to bridge the chasm between ignorance and insight, to unravel the intricacies of AI that often seem enigmatic to the outsiders. This profound reference material transcends being a passive repository of terms; it’s an engagement with the multifaceted domain of artificial intelligence. Each title encapsulated within these pages is a testament to the audacity of human curiosity and the unyielding quest for advancement that propels the AI domain forward. The Dictionary of Artificial Intelligence is an invitation to delve deeper, to grapple with the lexicon of a field that stands at the cusp of redefining the very fabric of society. It's a conduit through which the curious become enlightened, the proficient become masters, and the innovators find inspiration. As you traverse through the entries of The Dictionary of Artificial Intelligence, you are embarking on a journey of discovery. A journey that not only augments your understanding but also ignites the spark of curiosity and the drive for innovation that are quintessential in navigating the realms of AI. We beckon you to commence this educational expedition, to explore the breadth and depth of AI lexicon, and to emerge with a boundless understanding and an unyielding resolve to contribute to the ever-evolving narrative of artificial intelligence. Through The Dictionary of Artificial Intelligence, may your quest for knowledge be as boundless and exhilarating as the domain it explores. |
| artificial intelligence document management: ARTIFICIAL INTELLIGENCE PARAG KULKARNI, PRACHI JOSHI, 2015-02-26 There has been a movement over the years to make machines intelligent. With the advent of modern technology, AI has become the core part of day-to-day life. But it is accentuated to have a book that keeps abreast of all the state-of-the-art concepts (pertaining to AI) in simplified, explicit and elegant way, expounding on ample examples so that the beginners are able to comprehend the subject with ease. The book on Artificial Intelligence, dexterously divided into 21 chapters, fully satisfies all these pressing needs. It is intended to put each and every concept related to intelligent system in front of the readers in the most simplified way so that while understanding the basic concepts, they will develop thought process that can contribute to the building of advanced intelligent systems. Various cardinal landmarks pertaining to the subject such as problem solving, search techniques, intelligent agents, constraint satisfaction problems, knowledge representation, planning, machine learning, natural language processing, pattern recognition, game playing, hybrid and fuzzy systems, neural network-based learning and future work and trends in AI are now under the single umbrella of this book, thereby showing a nice blend of theoretical and practical aspects. With all the latest information incorporated and several pedagogical attributes included, this textbook is an invaluable learning tool for the undergraduate and postgraduate students of computer science and engineering, and information technology. KEY FEATURES • Highlights a clear and concise presentation through adequate study material • Follows a systematic approach to explicate fundamentals as well as recent advances in the area • Presents ample relevant problems in the form of multiple choice questions, concept review questions, critical thinking exercise and project work • Incorporates various case studies for major topics as well as numerous industrial examples |
| artificial intelligence document management: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| artificial intelligence document management: Artificial Intelligence and Law Rushil Chandra, Karun Sanjaya, 2024-02-29 ‘Artificial Intelligence and Law’ is a ground-breaking book that delves into the intersection of artificial intelligence (AI) and the legal domain, providing a comprehensive exploration of the evolving relationship between technology and the legal framework. Authored with meticulous research and expertise, the book offers a nuanced understanding of how AI technologies impact various facets of law, from legal practice to policy considerations. The authors skillfully navigate the intricate landscape of AI and its implications on legal processes, addressing challenges and opportunities presented by the integration of advanced technologies. With a focus on both theoretical and practical aspects, the book explores key themes such as the ethical considerations surrounding AI applications in law, the automation of legal tasks, and the implications for the legal profession. Readers will find insightful discussions on topics such as machine learning algorithms, natural language processing, and the use of AI in legal research. The book goes beyond a mere analysis of the present state, offering thoughtful insights into the future trajectory of AI in the legal domain and its potential impact on the justice system. ‘Artificial Intelligence and Law’ serves as an indispensable resource for legal professionals, scholars, and technologists seeking a comprehensive guide to the evolving landscape where AI and the law intersect. With its well-researched content and forward-looking perspective, the book contributes significantly to the ongoing discourse on the integration of artificial intelligence into the legal sphere. |
| artificial intelligence document management: Artificial Intelligence for Asset Management and Investment Al Naqvi, 2021-01-13 Make AI technology the backbone of your organization to compete in the Fintech era The rise of artificial intelligence is nothing short of a technological revolution. AI is poised to completely transform asset management and investment banking, yet its current application within the financial sector is limited and fragmented. Existing AI implementations tend to solve very narrow business issues, rather than serving as a powerful tech framework for next-generation finance. Artificial Intelligence for Asset Management and Investment provides a strategic viewpoint on how AI can be comprehensively integrated within investment finance, leading to evolved performance in compliance, management, customer service, and beyond. No other book on the market takes such a wide-ranging approach to using AI in asset management. With this guide, you’ll be able to build an asset management firm from the ground up—or revolutionize your existing firm—using artificial intelligence as the cornerstone and foundation. This is a must, because AI is quickly growing to be the single competitive factor for financial firms. With better AI comes better results. If you aren’t integrating AI in the strategic DNA of your firm, you’re at risk of being left behind. See how artificial intelligence can form the cornerstone of an integrated, strategic asset management framework Learn how to build AI into your organization to remain competitive in the world of Fintech Go beyond siloed AI implementations to reap even greater benefits Understand and overcome the governance and leadership challenges inherent in AI strategy Until now, it has been prohibitively difficult to map the high-tech world of AI onto complex and ever-changing financial markets. Artificial Intelligence for Asset Management and Investment makes this difficulty a thing of the past, providing you with a professional and accessible framework for setting up and running artificial intelligence in your financial operations. |
| artificial intelligence document management: Embedding Artificial Intelligence into ERP Software Siar Sarferaz, |
| artificial intelligence document management: Transformative Impacts of AI in Management Farooq, Muhammad, Ramzan, Muhammad, Yen, Yuen Yee, 2024-10-11 The transformative impacts of artificial intelligence (AI) in management are reshaping organizational dynamics and redefining traditional leadership roles. By harnessing AI technologies, companies are achieving higher levels of efficiency, insight, and strategic agility. AI-powered tools facilitate data-driven decision-making, automate routine tasks, and enhance predictive analytics, enabling managers to focus on high-value activities and strategic innovation. From optimizing supply chains and personalizing customer interactions to streamlining human resources and financial planning, AI is driving changes across all aspects of management. As businesses embrace these advancements, further research is necessary to improve operational performance and position businesses for long-term success. Transformative Impacts of AI in Management delves into the transformative impact of AI across management science, education, business, marketing, and agriculture. Through a structured synthesis of literature, the publication provides a detailed analysis of applications, challenges, and opportunities in each domain. This book covers topics such as management science, artificial intelligence, and marketing, and is a useful resource for academicians, policymakers, business owners, computer engineers, agriculturalists, educators, scientists, and researchers. |
| artificial intelligence document management: Advances In Artificial Intelligence For Privacy Protection And Security Agusti Solanas, Antoni Martinez-balleste, 2009-08-03 In this book, we aim to collect the most recent advances in artificial intelligence techniques (i.e. neural networks, fuzzy systems, multi-agent systems, genetic algorithms, image analysis, clustering, etc), which are applied to the protection of privacy and security. The symbiosis between these fields leads to a pool of invigorating ideas, which are explored in this book.On the one hand, individual privacy protection is a hot topic and must be addressed in order to guarantee the proper evolution of a modern society. On the other, security can invade individual privacy, especially after the appearance of new forms of terrorism. In this book, we analyze these problems from a new point of view. |
| artificial intelligence document management: African Artificial Intelligence Mark Nasila, 2024-05-27 Artificial intelligence (AI) is upending life, work, and play as we know it, and it's only just getting started. The rise of AI is a milestone on par with the discovery of fire, the invention of the wheel, and the creation of the internet. In short, AI is going to change everything. For some, that's an exciting prospect. For others, it's terrifying. However you feel about AI, there's no escaping it, whether you're in a global metropolis or a farmer in rural KwaZulu-Natal. Dr Mark Nasila has been watching AI's ascent for over a decade, studying its effects on everything from agriculture and aviation to healthcare, education, entertainment, crime prevention, energy management, policy creation, finance, and anything in between, and applying them to his role at one of South Africa's most successful financial institutions, First National Bank, a division of FirstRand Group. African Artificial Intelligence is a comprehensive and fascinating journey, tracing the rise of AI and its evolution into the emerging technology underpinning all others – from connected devices and smart chatbots to the metaverse. Mark combines unexpected use cases and tales of cutting-edge innovation with a unique and potent argument: harnessing AI to solve Africa's problems requires embracing it from an African perspective. African nations can't afford to simply import AI solutions from afar. Instead, Mark contends, they need to rework, remix, and refine AI so it's able to meet uniquely African challenges in uniquely African ways, and to take advantage of the once-in-a-generation opportunity AI represents for every industry, sector, and person, everywhere. |
| artificial intelligence document management: Artificial Intelligence in Law Enrico Guardelli, Artificial Intelligence (AI) is profoundly transforming the legal field, bringing new opportunities and challenges that impact everything from process automation to judicial decision-making. In Artificial Intelligence in Law: A New Era of Regulation and Justice, we explore this complex intersection between technology and law, offering a detailed analysis of the main concepts, technologies and applications of AI in the legal sector. This book covers the historical evolution of AI, the main ethical and legal challenges, and how different legal systems around the world are adapting to this technological revolution. In addition, we discuss crucial issues such as legal liability in cases involving AI, the protection of personal data, and the impact of AI on human rights. It is essential reading for legal scholars, academics, technology professionals and anyone interested in understanding how AI is shaping the future of law. With a clear and informed approach, the book offers valuable insights on how to navigate the complexities of this new digital era. |
| artificial intelligence document management: AI*IA 2009: Emergent Perspectives in Artificial Intelligence Roberto Serra, Rita Cucchiara, 2009-11-30 Intelligence for Human Behavior Analysis,” organized by Luca Iocchi, Andrea Prati and Roberto Vezzani. |
| artificial intelligence document management: Artificial Intelligence In Medicine: A Practical Guide For Clinicians Campion Quinn, 2024-02-06 'Artificial Intelligence in Medicine' is a comprehensive guide exploring the transformative impact of artificial intelligence (AI) in healthcare. The book delves into the foundational concepts and historical development of AI in medicine, highlighting data collection, preprocessing, and feature extraction crucial for medical applications. It showcases the benefits of AI, such as accurate diagnoses and personalized treatments, while addressing ethical and regulatory considerations.The book examines the practical aspects of AI implementation in clinical practice and emphasizes the human aspect of AI in healthcare and patient engagement. Readers can gain insights into the role of AI in clinical decision support, collaborative learning, and knowledge sharing. It concludes with a glimpse into the future of AI-driven healthcare, exploring the emerging technologies and trends in the rapidly evolving field of AI in medicine. |
| artificial intelligence document management: Generative Artificial Intelligence. World Intellectual Property Organization, 2024-07-03 In this WIPO Patent Landscape Report on Generative AI, discover the latest patent trends for GenAI with a comprehensive and up-to-date understanding of the GenAI patent landscape, alongside insights into its future applications and potential impact. The report explores patents relating to the different modes, models and industrial application areas of GenAI. |
| artificial intelligence document management: Readings in Distributed Artificial Intelligence Alan H. Bond, Les Gasser, 2014-06-05 Most artificial intelligence research investigates intelligent behavior for a single agent--solving problems heuristically, understanding natural language, and so on. Distributed Artificial Intelligence (DAI) is concerned with coordinated intelligent behavior: intelligent agents coordinating their knowledge, skills, and plans to act or solve problems, working toward a single goal, or toward separate, individual goals that interact. DAI provides intellectual insights about organization, interaction, and problem solving among intelligent agents. This comprehensive collection of articles shows the breadth and depth of DAI research. The selected information is relevant to emerging DAI technologies as well as to practical problems in artificial intelligence, distributed computing systems, and human-computer interaction. Readings in Distributed Artificial Intelligence proposes a framework for understanding the problems and possibilities of DAI. It divides the study into three realms: the natural systems approach (emulating strategies and representations people use to coordinate their activities), the engineering/science perspective (building automated, coordinated problem solvers for specific applications), and a third, hybrid approach that is useful in analyzing and developing mixed collections of machines and human agents working together. The editors introduce the volume with an important survey of the motivations, research, and results of work in DAI. This historical and conceptual overview combines with chapter introductions to guide the reader through this fascinating field. A unique and extensive bibliography is also provided. |
| artificial intelligence document management: AI Money Making Machine Dr. Ope Banwo, 2024-08-10 Unleashing Potential with AI Tools The advent of AI technology has revolutionized how we approach business, creativity, and problem-solving. I wrote this book to demystify AI tools and demonstrate how they can be leveraged to create profitable ventures. The potential to make money with AI is vast, and my goal is to provide a comprehensive guide that anyone can follow to tap into this opportunity. |
| artificial intelligence document management: Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough Vinit Kumar Gunjan, Jacek M. Zurada, 2021-04-26 This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains. |
| artificial intelligence document management: Recent Technological Advances in Engineering and Management Dalia Younis, Ilona Paweloszek, Mamta Chahar, Narendra Kumar, Nino Abesadze, Preeti Narooka, 2024-09-26 It is with immense pleasure that we extend a warm welcome to all of you to the recently concluded conference, international conference on Advances in Science, Technology and Management (ICOSTEM 2023) which took place from November 24 – 27, 2023, in the picturesque Maldives, Male. This significant event focused on the “Recent Technological Advances in Engineering and Management” with special sessions on Applied Sciences, Management and Engineering. |
| artificial intelligence document management: Hybrid Artificial Intelligence Systems Emilio Corchado, Xindong Wu, Erkki Oja, Bruno Baruque, 2009-06-02 This volume constitutes the refereed proceedings of the 4th International Workshop on Hybrid Artificial Intelligence Systems, HAIS 2009, held in Salamanca, Spain, in June 2009. The 85 papers presented, were carefully reviewed and selected from 206 submissions. The topics covered are agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, real world HAIS applications and data uncertainty, hybrid artificial intelligence in bioinformatics, evolutionary multiobjective machine learning, hybrid reasoning and coordination methods on multi-agent systems, methods of classifiers fusion, knowledge extraction based on evolutionary learning, hybrid systems based on bioinspired algorithms and argumentation methods, hybrid evolutionry intelligence in financial engineering. |
| artificial intelligence document management: Artificial Intelligence Kerrigan, Charles, 2022-03-17 This timely book provides an extensive overview and analysis of the law and regulation as it applies to the technology and uses of Artificial Intelligence (AI). It examines the human and ethical concerns associated with the technology, the history of AI and AI in commercial contexts. |
| artificial intelligence document management: Digital Transformation in Education and Artificial Intelligence Application Tomislav Volarić, |
| artificial intelligence document management: Artificial Intelligence in Economics and Managment Phillip Ein-Dor, 2012-12-06 In the past decades several researchers have developed statistical models for the prediction of corporate bankruptcy, e. g. Altman (1968) and Bilderbeek (1983). A model for predicting corporate bankruptcy aims to describe the relation between bankruptcy and a number of explanatory financial ratios. These ratios can be calculated from the information contained in a company's annual report. The is to obtain a method for timely prediction of bankruptcy, a so ultimate purpose called early warning system. More recently, this subject has attracted the attention of researchers in the area of machine learning, e. g. Shaw and Gentry (1990), Fletcher and Goss (1993), and Tam and Kiang (1992). This research is usually directed at the comparison of machine learning methods, such as induction of classification trees and neural networks, with the standard statistical methods of linear discriminant analysis and logistic regression. In earlier research, Feelders et al. (1994) performed a similar comparative analysis. The methods used were linear discriminant analysis, decision trees and neural networks. We used a data set which contained 139 annual reports of Dutch industrial and trading companies. The experiments showed that the estimated prediction error of both the decision tree and neural network were below the estimated error of the linear discriminant. Thus it seems that we can gain by replacing the traditionally used linear discriminant by a more flexible classification method to predict corporate bankruptcy. The data set used in these experiments was very small however. |
| artificial intelligence document management: Artificial Intelligence-Augmented Digital Twins Abdalmuttaleb M. A. Musleh Al-Sartawi, Anas Ali Al-Qudah, Fadi Shihadeh, 2024-01-19 Presently, we stand on the threshold of a technological revolution that will drastically change the way we live, work, and communicate with each other. By the current rate, scope, and complexity, this transformation will be as fundamental for society as any other technological paradigm change from the past. The industries which are more susceptible to change are technologically oriented industries including banking, finance, accounting, and auditing. One of the technological concepts of the technological revolution is the concept of the digital twin. The application of digital twins and AI as paired with Internet of Things technologies makes it possible to solve ESG problems on a completely different level (Li, 2019) for accounting firms and financial institutions. These include recycling on demand, rational energy consumption, smart surveillance cameras for crime tracking, and smart branch parking solutions, monitoring the wear and tear and conditions of financial technology infrastructures. Moreover, numerous researchers and practitioners emphasize the significance of innovating sustainable business models and operations (Geissdoerfer et al., 2018). The digital twin will allow businesses and financial institutions to minimize costs, boost customer service, and find new ways to generate revenue. DTW is accessible now more than ever, and many reputable and innovative companies such as Tesla, Ericsson, and Siemens have adopted it with varying success. Therefore, this book examines the opportunities, challenges, and risks of artificial intelligence-augmented digital twins for financial operations, innovation, and sustainable development. It focuses on AI and digital twin technologies to furnish solutions for the current industrial revolution including the Metaverse. Henceforth, this book aims to encourage authors to submit multi-disciplinary chapters indicating the current scholarly challenges about the applications and potential of artificial intelligence and digital twins in accounting, finance, and banking. |
| artificial intelligence document management: Machine Learning, Optimization, and Data Science Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos Pardalos, Giuseppe Di Fatta, Giovanni Giuffrida, Renato Umeton, 2023-03-08 This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications. |
| artificial intelligence document management: Digital Transformation and Internationalization Strategies in Organizations Yildiz, Orkun, 2021-10-15 Competitive strategies and higher education-industry collaboration policies are playing an important role in fostering the reputation and international rankings of higher education institutions. The positive impact of these policies may best be observed in economic and social outputs of many countries such as the USA, Singapore, South Korea, EU countries, and Turkey. However, the number of academic publications that specifically concentrate on the impact of these policies on higher education institutions and authorities remains relatively limited. Digital Transformation and Internationalization Strategies in Organizations covers a wide range of issues and topics, including employment systems, quality management systems, international ranking systems in higher education, education and language policies in higher education, and business models employed in techno-parks. This book helps higher education institutions manage their manpower and become cognizant of the factors that may exert a drastic impact on their success. It is ideal for managers, executives, IT consultants, researchers, practitioners, academics, professors, and undergraduate and postgraduate students. |
| artificial intelligence document management: Handbook of Research on Records and Information Management Strategies for Enhanced Knowledge Coordination Chisita, Collence Takaingenhamo, Enakrire, Rexwhite Tega, Durodolu, Oluwole Olumide, Tsabedze, Vusi Wonderboy, Ngoaketsi, Joseph M., 2021-01-15 The convergence of technologies and emergence of interdisciplinary and transdisciplinary modus of knowledge production justify the need for research that explores the disinterestedness or interconnectivity of the information science disciplines. The quantum leap in knowledge production, increasing demand for information and knowledge, changing information needs, information governance, and proliferation of digital technologies in the era of ubiquitous digital technologies justify research that employs a holistic approach in x-raying the challenges of managing information in an increasingly knowledge- and technology-driven dispensation. The changing nature of knowledge production for sustainable development, along with trends and theory for enhanced knowledge coordination, deserve focus in current times. The Handbook of Research on Records and Information Management Strategies for Enhanced Knowledge Coordination draws input from experts involved in records management, information science, library science, memory, and digital technology, creating a vanguard compendium of novel trends and praxis. While highlighting a vast array of topics under the scope of library science, information science, knowledge transfer, records management, and more, this book is ideally designed for knowledge and information managers, library and information science schools, policymakers, practitioners, stakeholders, administrators, researchers, academicians, and students interested in records and information management. |
| artificial intelligence document management: Advances in Artificial Intelligence and Machine Learning in Big Data Processing R. Geetha, |
| artificial intelligence document management: A Guided Tour of Artificial Intelligence Research Pierre Marquis, Odile Papini, Henri Prade, 2020-05-08 The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries. Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty. Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2). Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume. |
| artificial intelligence document management: Artificial Intelligence in Healthcare: Transforming the Medical Industry Michael Roberts, Artificial Intelligence (AI) is revolutionizing the healthcare industry, offering unprecedented opportunities to enhance patient care, streamline clinical operations, and accelerate medical research. Artificial Intelligence in Healthcare: Transforming the Medical Industry is your comprehensive guide to understanding and leveraging AI technologies in the medical field. This book explores the various applications of AI in healthcare, from diagnostic tools and personalized medicine to administrative efficiency and patient management. With detailed case studies, expert insights, and practical advice, this handbook is an essential resource for healthcare professionals, technology enthusiasts, and industry leaders. Embrace the future of healthcare and discover how AI can transform the way we diagnose, treat, and manage diseases. |
| artificial intelligence document management: Advances in Artificial Intelligence and Data Engineering Niranjan N. Chiplunkar, Takanori Fukao, 2020-08-13 This book presents selected peer-reviewed papers from the International Conference on Artificial Intelligence and Data Engineering (AIDE 2019). The topics covered are broadly divided into four groups: artificial intelligence, machine vision and robotics, ambient intelligence, and data engineering. The book discusses recent technological advances in the emerging fields of artificial intelligence, machine learning, robotics, virtual reality, augmented reality, bioinformatics, intelligent systems, cognitive systems, computational intelligence, neural networks, evolutionary computation, speech processing, Internet of Things, big data challenges, data mining, information retrieval, and natural language processing. Given its scope, this book can be useful for students, researchers, and professionals interested in the growing applications of artificial intelligence and data engineering. |
| artificial intelligence document management: Hyperautomation in Business and Society Darwish, Dina, 2024-07-17 The demand for efficiency and intelligent decision-making has become paramount, prompting a crucial examination of the limitations of traditional automation. Organizations find themselves at a crossroads, searching for a transformative solution that transcends conventional approaches. Enter the era of Hyperautomation an innovative paradigm that goes beyond simple automation by integrating artificial intelligence, robotic process automation, and advanced techniques such as cognitive computing and data mining. Hyperautomation in Business and Society is a comprehensive exploration of how Hyperautomation addresses the complexities of modern challenges, offering a compelling solution to propel businesses and society into a new era of efficiency and intelligent decision-making. This book sets out to achieve a dual purpose: to enlighten and to guide. Starting with a breakdown of intelligent automation, the book progresses to dissect the latest IA technologies, platforms, and the intricate ways in which it optimizes workflows. Spanning diverse applications across sectors such as logistics, marketing, finance, and customer care, it paints a vivid picture of IA's transformative influence. Notably, it addresses the challenges faced by IA implementation, offering a nuanced exploration of real-world applications and their impact on businesses. Geared towards undergraduate and postgraduate students, researchers, and practitioners, this book is a compass for those navigating the ever-changing landscape of intelligent automation. |
| artificial intelligence document management: Application of Intelligent Systems in Multi-modal Information Analytics Vijayan Sugumaran, Zheng Xu, Huiyu Zhou, 2020-07-23 This book presents the proceedings of the 2020 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Changzhou, China, on June 18–19, 2020. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. It addresses a number of broad themes, including data mining, multi-modal informatics, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field. |
| artificial intelligence document management: Les intelligences artificielles au prisme de la justice sociale. Considering Artificial Intelligence Through the Lens of Social Justice Collectif Collectif, 2023-11-15T00:00:00-05:00 Cet ouvrage vient clôturer deux années de réflexion intensive sur les enjeux à l’intersection entre la justice sociale et les technologies d’IA. Une compréhension de ces impacts sociétaux dépasse alors l’aspect technique pour se concentrer principalement sur le fait social. |
| artificial intelligence document management: Evolution of environmental economics & management in the age of artificial intelligence for sustainable development Elena G. Popkova, Bruno Sergi, Aleksei V. Bogoviz, 2023-06-06 |
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