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Author: Arup Das
Publisher: TinyTechMedia LLC
ISBN:
Category : Computers
Languages : en
Pages : 103
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Book Description
Generative AI is revolutionizing the way organizations leverage technology to gain a competitive edge. However, as more companies experiment with and adopt AI systems, it becomes challenging for data and analytics professionals, AI practitioners, executives, technologists, and business leaders to look beyond the buzz and focus on the essential questions: Where should we begin? How do we initiate the process? What potential pitfalls should we be aware of? This TinyTechGuide offers valuable insights and practical recommendations on constructing a business case, calculating ROI, exploring real-life applications, and considering ethical implications. Crucially, it introduces five LLM patterns—author, retriever, extractor, agent, and experimental—to effectively implement GenAI systems within an organization. The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications bridges critical knowledge gaps for business leaders and practitioners, equipping them with a comprehensive toolkit to define a business case and successfully deploy GenAI. In today’s rapidly evolving world, staying ahead of the competition requires a deep understanding of these five implementation patterns and the potential benefits and risks associated with GenAI. Designed for business leaders, tech experts, and IT teams, this book provides real-life examples and actionable insights into GenAI’s transformative impact on various industries. Empower your organization with a competitive edge in today’s marketplace using The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications. Remember, it’s not the tech that’s tiny, just the book!™
Author: Arup Das
Publisher: TinyTechMedia LLC
ISBN:
Category : Computers
Languages : en
Pages : 103
Get Book Here
Book Description
Generative AI is revolutionizing the way organizations leverage technology to gain a competitive edge. However, as more companies experiment with and adopt AI systems, it becomes challenging for data and analytics professionals, AI practitioners, executives, technologists, and business leaders to look beyond the buzz and focus on the essential questions: Where should we begin? How do we initiate the process? What potential pitfalls should we be aware of? This TinyTechGuide offers valuable insights and practical recommendations on constructing a business case, calculating ROI, exploring real-life applications, and considering ethical implications. Crucially, it introduces five LLM patterns—author, retriever, extractor, agent, and experimental—to effectively implement GenAI systems within an organization. The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications bridges critical knowledge gaps for business leaders and practitioners, equipping them with a comprehensive toolkit to define a business case and successfully deploy GenAI. In today’s rapidly evolving world, staying ahead of the competition requires a deep understanding of these five implementation patterns and the potential benefits and risks associated with GenAI. Designed for business leaders, tech experts, and IT teams, this book provides real-life examples and actionable insights into GenAI’s transformative impact on various industries. Empower your organization with a competitive edge in today’s marketplace using The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications. Remember, it’s not the tech that’s tiny, just the book!™
Author: Andrew Burgess
Publisher: Springer
ISBN: 3319638203
Category : Business & Economics
Languages : en
Pages : 187
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Book Description
This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.
Author: Omer Shapira
Publisher:
ISBN: 9781641059114
Category : Arbitration and award
Languages : en
Pages : 394
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Book Description
"This book is aimed at lawyer-mediators who care about their clients, professions, and the general public and want to conduct mediations ethically"--
Author: Miao, Fengchun
Publisher: UNESCO Publishing
ISBN: 9231004476
Category : Political Science
Languages : en
Pages : 50
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Book Description
Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]
Author: JERRY. KAPLAN
Publisher: Oxford University Press
ISBN: 0197773540
Category :
Languages : en
Pages : 241
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Book Description
Generative Artificial Intelligence: What Everyone Needs to Know Â(R) equips readers with the knowledge to answer pressing questions about the impact of generative artificial intelligence on every facet of society.
Author: Gaur, Loveleen
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 350
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Book Description
The rapid advancement of generative artificial intelligence (AI) has brought about significant ethical challenges. As machines become more adept at creating human-like content, concerns about misuse, bias, privacy, and accountability have emerged. Without clear guidelines and regulations, there is a risk of unethical use, such as creating deepfake videos or disseminating misinformation, which could have severe societal consequences. Additionally, questions about intellectual property rights and the ownership of AI-generated creations still need to be solved, further complicating the ethical landscape. The book, Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices, comprehensively solves these ethical challenges. By providing insights into the historical development and key milestones of Generative AI, the book lays a foundation for understanding its complex ethical implications. It examines existing ethical frameworks and proposes new ones tailored to AI's unique characteristics, helping readers apply traditional ethics to AI development and deployment.
Author: Dr. Scott Dell
Publisher: Packt Publishing Ltd
ISBN: 1835462251
Category : Computers
Languages : en
Pages : 278
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Book Description
Elevate your accounting skills by applying ChatGPT across audit, tax, consulting, and beyond Key Features Leverage the impact of AI on modern accounting, from audits to corporate governance Use ChatGPT to streamline your accounting tasks with practical hands-on techniques Understand the impact of AI in accounting through in-depth chapters covering various domains, including ethical considerations and data analytics Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the fast-paced AI world, accounting professionals are increasingly challenged by the complexities of AI. Many struggle to integrate these advanced tools into their workflows, leading to a sense of overwhelm. ChatGPT for Accounting bridges this gap by not only simplifying AI concepts but also offering practical insights for its application in various accounting domains. This book takes you from the foundational principles of Generative Artificial Intelligence (GAI) to its practical applications in audits, tax planning, practice management, fraud examination, financial analysis, and beyond. Each chapter equips you with essential skills, showing you how AI can revolutionize internal control systems, enhance recruitment processes, streamline marketing plans, optimize tax strategies, and boost efficiency in audits. You’ll then advance to exploring the role of AI in forensic accounting, financial analysis, managerial accounting, and corporate governance, while also addressing ethical and security implications. Concluding with a reflective outlook on the promises and challenges of AI, you’ll gain a holistic view of the future of accounting. By the end of this book, you’ll be equipped with the knowledge to harness the power of AI effectively and ethically, transforming your accounting practice and staying ahead in the ever-evolving landscape.What you will learn Understand the fundamentals of AI and its impact on the accounting sector Grasp how AI streamlines and enhances the auditing process for high accuracy Uncover the potential of AI in simplifying tax processes and ensuring compliance Get to grips with using AI to identify discrepancies and prevent financial fraud Master the art of AI-powered data analytics for informed decision-making Gain insights into seamlessly integrating AI tools within existing accounting systems Stay ahead in the evolving landscape of AI-led accounting tools and practices Who this book is for Whether you're a seasoned accounting professional, a C-suite executive, a business owner, an accounting educator, a student of accounting, or a technology enthusiast, this book provides the knowledge and insights you need to navigate the changing landscape in applying GAI technology to make a difference in all you do. An appreciation and understanding of the accounting process and concepts will be beneficial.
Author: Christiansen, Bryan
Publisher: IGI Global
ISBN:
Category : Education
Languages : en
Pages : 451
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Book Description
The global skills gap and labor market disruptions pose a significant challenge for organizations worldwide. Higher education struggles to bridge the mismatch between skills taught in academia and those demanded by employers, hindering organizations in an era of heightened competition. Advancing Student Employability Through Higher Education offers a comprehensive solution to address this issue. Edited by Bryan Christiansen and Angela Even, this publication brings together innovative research and insights from employers and employees, serving as a valuable resource for academic scholars seeking the latest research on employer requirements in an era of increasing global hyper-competition. Covering topics like industry-academia collaboration, educational innovation, learning analytics, and educational artificial intelligence (AI), the book provides practical strategies and innovative approaches to bridge the gap between academic instruction and real-world organizational needs. It equips students with the skills and qualifications necessary to thrive in today's global economy through case studies, online learning effectiveness, and training evaluation. By leveraging the expertise of renowned scholars and industry practitioners, the book enhances understanding of the intricate dynamics of the workforce. It empowers scholars, graduate students, and higher education professionals to navigate the evolving needs of organizations, fostering success for individuals and organizational growth in an increasingly competitive landscape.
Author: John Long
Publisher: Springer Nature
ISBN: 303168981X
Category :
Languages : en
Pages : 183
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Book Description
Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
