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 Anonymous

Nutzung von Business Intelligence zur Identifikation und Entwicklung digitaler Geschäftsmodelle

Management on the Cutting Edge

In his bestselling first book, Eric Siegel explained how machine learning works. Now, in The AI Playbook, he shows how to capitalize on it. “Eric Siegel delivers a robust primer on machine learning, the key mechanism in AI. A forward-looking, practical book and a must-read for anyone in the information economy.” —Scott Galloway, NYU Stern Professor of Marketing; bestselling author of The Four “An antidote to today’s relentless AI hype—why some AI initiatives thrive while others fail and what it takes for companies and people to succeed.” —Charles Duhigg, author of bestsellers The Power of Habit and Smarter Faster Better The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects, aka predictive AI projects, from conception to deployment. He illustrates the practice with stories of success and of failure, including revealing case studies from UPS, FICO, and prominent dot-coms. This disciplined approach serves both sides: It empowers business professionals, and it establishes a sorely needed strategic framework for data professionals. Beyond detailing the practice, this book also upskills business professionals—painlessly. It delivers a vital yet friendly dose of semi-technical background knowledge that all stakeholders need to lead or participate in machine learning projects, end to end. This puts business and data professionals on the same page so that they can collaborate deeply, jointly establishing precisely what machine learning is called upon to predict, how well it predicts, and how its predictions are acted upon to improve operations. These essentials make or break each initiative—getting them right paves the way for machine learning's value-driven deployment. A note from the author: The buzzword AI can mean many things, but this book is about the most vital use cases of machine learning,&nbsp;those designed to improve large-scale business operations—aka predictive AI or predictive analytics.

Mastering the Rare Art of Machine Learning Deployment

The AI Playbook, with a new preface by the author

This book offers a multidisciplinary analysis of the technologies that are transforming financial services, markets, and regulation. It examines the rise of digital payments, peer-to-peer lending, challenger banks, blockchain, big data, cybersecurity, and artificial intelligence. It aims to bridge the gap between theoretical knowledge and practical application while also offering guidance on how individuals, businesses, and financial institutions can leverage fintech innovations to their advantage. Not only does it discuss the current fintech trends but also explores future developments and potential disruptions in the financial sector. In an era where fintech is transforming traditional finance, this book addresses the growing need for accessible, up-to-date, and reliable information on the subject. It will be an essential resource for academics, researchers, students, and practitioners seeking to navigate the ever-evolving financial landscape.Brian Lucey&nbsp;
 is a Professor of International Finance at Trinity Business School, Ireland. Professor Lucey has worked as a statistician in the Department of Health and as an economist in the Central Bank.&nbsp;He has studied at graduate level in Canada, Ireland, and Scotland, and holds a PhD from the University of Stirling.
 Vincenzo Verdoliva
 is Professor of Finance at Pegaso Digital University, Italy. His main research interests include market liquidity, credit risk and financial distress, initial public offerings and venture capital, FinTech and digital transformation, lending, and relationship banking. He also serves as an Associate Editor of 
 The European Journal of Finance
 .

The Innovations Reshaping the Financial Landscape

The FinTech Frontier

In Digitizing the Supply Chain, Nick Seiersen explores the transformative potential of information technologies in modern supply chain management. This book examines the foundational technologies, tools, and challenges of the digital transformation of supply chains, offering insights into future trends and opportunities.

The author reviews key technologies such as AI, IoT, blockchain, and Big Data, illustrating their application through real-world case studies. Readers will gain a practical understanding of how to leverage these technologies to optimize logistics, enhance cybersecurity, and manage risk.

This book serves as an essential resource for executives and professionals seeking to navigate the complexities of deploying new technologies to build resilient, future-proof supply chains.

How AI and 8 Technology Building Blocks Can Supercharge Your Supply Chain

Digitizing the Supply Chain

An Advanced Guide to Data-Driven Decision Making

Business Analytics and Artificial Intelligence

Technik im Fokus

Marketing-Text
Künstliche Intelligenz ist längst Teil unseres Alltags. Dieses Buch erklärt verständlich, wie sich KI von frühen symbolischen Ansätzen bis zu neuronalen Netzen entwickelt hat. KI ist aber nicht nur statistische Datenoptimierung, sondern beginnt, zu erklären und zu entscheiden, die Energieeffizienz des menschlichen Gehirns zu simulieren und sich mit Quantencomputing zu verbinden.
Anschaulich beleuchtet das Buch die Herausforderungen einer Technologie, die zur globalen Schlüsselressource geworden ist.
Ein fundierter Leitfaden für alle, die verstehen wollen, wie KI unsere Welt verändert – und wie wir sie so gestalten können, dass sie dem Menschen dient.
Zielgruppe
Alle an KI interessierten Leserinnen und Leser, die ihre Grundlagen, Möglichkeiten und Grenzen verstehen wollen.
Der Autor
Nach Studium der Mathematik, Physik und Philosophie, Promotion, Habilitation und Heisenbergstipendium an der Universität Münster war Klaus Mainzer Professor und Prorektor an der Universität Konstanz, Gründungsdirektor des Instituts für interdisziplinäre Informatik an der Universität Augsburg, Direktor der Carl von Linde Akademie und Gründungsdirektor des Munich Center for Technology in Society (MCTS) an der Technischen Universität München (TUM). Er ist TUM-Emeritus of Excellence, Mitglied verschiedener Akademien, Präsident der Europäischen Akademie der Wissenschaften und Künste, Ehrendoktor und Honorarprofessor. Seine Forschungsthemen betreffen komplexe Systeme, KI und die Zukunft der technisch-wissenschaftlichen Welt.

Künstliche Intelligenz – Wann übernehmen die Maschinen?

'This view from the other side of the search box is both charming and insightful, tapping into a deep well of curiosity.' Tim Harford, author of How to Make the World Add UpEver wondered what goes through other people's minds - our silly questions, inner anxieties, hopes and dreams?In this hopeful and insightful book, Google Data Editor Simon Rogers explores insights from the world's biggest dataset: an epic snapshot, two decades long and counting, of our collective brain. What it reveals about us might surprise you.<ul><li>In June the UK sees a spike in searches for 'how to help a bee'</li><li>London is the top place on earth searching for 'tell the time drunk'</li><li>Around the world, it's 2am when parents want to know how to get their baby to sleep</li><li>Searches for 'how to help' are at an all-time high</li></ul> Brimming with insights that vary from the playful to the profound, What We Ask Google delves into the momentous and the mundane secrets of what we ask when we get the chance to ask anything, offering a surprisingly hopeful picture of humankind.'In a time when the news is so relentlessly gloomy, this book provides a ray of hope.' Daily Mail'Deserves a place on any bathroom bookshelf' Guardian

A surprisingly hopeful picture of humankind

What We Ask Google

A critical introduction to the psychiatric technologies of the future Artificial intelligence (AI) promises to transform nearly every area of modern life, and psychiatry is no exception. The field faces the mounting crisises in diagnostic inaccuracy, treatment stagnation, and persistent failures in suicide prevention, while traditional approaches struggle to keep pace with patient needs. AI and neuroscience offer a new path forward, pointing toward a future where mental health care is grounded in objective data, individualized predictions, and biologically informed treatments. Decoding Despair provides a cutting-edge look at these emerging scientific possibilities and the long-standing norms they may replace. Beginning with an examination of psychiatry's current challenges, it moves toward a present where AI-powered tools are beginning to reshape diagnostics, treatment selection, and drug development. The book offers readers a deeper understanding of mental health as both a scientific field and a lived human experience, while igniting an essential conversation about the transformative potential of precision psychiatry and technology. Decoding Despair readers will also find: <ul> <li>Exploration of the patient's journey from first symptoms to being prescribed medication</li> <li>Deep dive into the healthcare system and an understanding of the connections between stakeholders</li> <li>Clear explanations of how AI models work and how they can be practically applied to solving issues in mental health</li> <li>Deep introduction into the world of data and the different models of data acquisition necessary for building AI solutions</li> <li>Analysis of the potential innovations that could come first and the conditions necessary for them to occur</li> </ul> &nbsp; Decoding Despair is ideal for professionals and innovators building the future of psychiatry-as well as anyone seeking to understand their own mental health and the technological breakthroughs poised to reshape this critical field of care.

How AI is Reshaping Psychiatry

Decoding Despair

Masterarbeit aus dem Jahr 2021 im Fachbereich BWL - Sonstiges, Note: 1.0, Fachhochschule Koblenz - Standort RheinAhrCampus Remagen, Sprache: Deutsch, Abstract: Die Bekämpfung der Geldwäsche stellt die Kreditinstitute vor große Herausforderungen. Kreditinstitute können derzeit neben den "klassischen" Verfahren wie der Implementierung von "unflexiblen" IT-basierten AML-Lösungen (Anti-Money-Laundering) nur mit immer größeren Personalressourcen auf die Herausforderungen reagieren. Das Forschungsziel der vorliegenden Arbeit ist es, zu untersuchen, ob der Einsatz der künstlichen Intelligenz (Artificial Intelligence) bei der Bekämpfung der Geldwäsche wirkungsvoll unterstützen kann. Dazu wird die folgende Forschungsfrage gestellt: "Inwieweit können Kreditinstitute durch den Einsatz von KI-Technologien auffällige Muster und Hinweise auf Geldwäsche effizienter als mit bestehenden IT-Systemen entdecken?" Um die Forschungsfrage zu beantworten, wird eine qualitative Forschungsmethode gewählt. Dabei wird die vorhandene akademische Literatur zum Einsatz künstlicher Intelligenz bei der Bekämpfung der Geldwäsche untersucht und werden qualitative Interviews mit Branchenexperten als Instrument zur Datenerhebung mit Branchenexperten durchgeführt. Als Resultat zeigt sich, dass die Lücke zwischen den aktuellen AML-Methoden und der hochmodernen künstlichen Intelligenz (KI) geschlossen werden kann. Durch die neuen Trends und Richtungen in der KI-Technologie ist es möglich, skalierbare AML-Lösungen zu entwickeln.

Qualitative Analyse und Betrachtung

Einsatz von Artificial Intelligence zur Bekämpfung der Geldwäsche in Kreditinstituten

Advanced technologies like Artificial Intelligence, the Internet of Things, Big Data and Cyber Physical Systems are not only reshaping business operations but also redefining competition across industries. 
Integrating 4IR and 5IR Technologies for Digital Business Innovation provides an understanding of the characteristics and implications associated with Industry 4.0 and 5.0 technologies. It also offers frameworks for integrating these technologies into business operations to foster innovation, enhance efficiency, and gain a competitive edge. Furthermore, the book offers insights and frameworks for integrating these technologies into business operations to foster innovation, enhance efficiency, and gain a competitive edge and investigates the paths of these technologies and their potential impact on various industries. 
Perspectives from a range of experts in divergent fields makes this an invaluable resource suitable for various audiences: from business executives and entrepreneurs to scholars and students alike this publication serves as a reference material that equips them with knowledge and tools necessary for thriving in the era of intelligent technology.

Integrating 4ir and 5ir Technologies for Digital Business Innovation

In Networked Business, Paul Grefen returns with the third edition of his tried and tested BOAT framework for advanced e-business, covering the spectrum from business models via organization structures and digital system architectures to information technology.Today's successful organizations are complex; they are part of dynamic business networks built on digital channels, going far beyond traditional e-commerce. This book provides invaluable insights of modern digitally enabled networked business, going much further than the usual analysis of traditional e-business texts. It is heavily expanded and updated with the latest developments of digitally connected business, including new topics like value-oriented business, business optimization loops, (generative) artificial intelligence, and technology hype cycles.This essential text provides a compact roadmap to networked business for engineering, information systems or business students as well as professionals in the field.

Charting Digitally Enabled Business Collaboration

Networked Business

An acclaimed New York Times Magazine writer brings us into the world of the controversial technology firm Palantir and its very colorful and outspoken CEO, Alex Karp, tracing the ascent of Big Data, the rise of surveillance technology, and the shifting global balance of power in the 21st century. Palantir builds data integration software: its technology ingests vast quantities of information and quickly identifies patterns, trends, and connections that might elude the human eye. Founded in 2003 to help the US government in the war on terrorism—an early investor was the CIA—Palantir is now a $400 billion global colossus whose software is used by major intelligence services (including the Mossad), the US military, dozens of federal agencies, and corporate giants like Airbus and BP. From AI to counterterrorism to climate change to immigration to financial fraud to the future of warfare, the company is at the nexus of the most critical issues of the 21st century. Its CEO, Alex Karp, is a distinctive figure on the global business scene. A biracial Jew who is also severely dyslexic, Karp has built Palantir into a tech giant despite having no background in either business or computer science. Instead, he’s a trained philosopher who has become known for his strongly held views on a range of issues and for his willingness to grapple with the moral and ethical implications of Palantir’s work. Those questions have taken on added urgency during the Trump era, which has also brought attention to the political activism of Karp’s close friend and Palantir cofounder Peter Thiel. In The Philosopher in the Valley, journalist Michael Steinberger explores the world of Alex Karp, Palantir, and the future that they are leading us toward. It is an urgent and illuminating work about one of Silicon Valley’s most secretive and powerful companies, whose technology is at the leading edge of the surveillance state.

Alex Karp, Palantir, and the Rise of the Surveillance State

The Philosopher in the Valley

Grundzüge der Wirtschaftsinformatik

Nutzung von Business Intelligence zur Identifikation und Entwicklung digitaler Geschäftsmodelle

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