<div class="raw-html-embed"><a href="https://libratech.ai/ch/?utm_source=partner&amp;utm_medium=website&amp;utm_campaign=wkch_libra_prsp_staempfli_07_2026
">Stämpfli Fachinhalte - jetzt im rechtssicheren Libra All-In-One AI Workspace verfügbar - Jetzt kostenlos testen!</a></div>

Über uns

À propos de nous

Nachhaltigkeit

Durabilité

Open Access

Karriere

Carrière

Aboverträge Kündigen

Résiliation d’abonnement

Vertrag widerrufen

Résiliation de contrat 

Datenschutz

Protection des données

Impressum

Mentions légales

Zahlung und Lieferung

Paiement et livraison

Libra

Was ist Libra?

C'est quoi Libra ?

Kostenlos testen

Tester gratuitement

LEXIA

LEXIA Arbeitsrecht

Was ist LEXIA?

C'est quoi LEXIA ?

LEXIA Familienrecht

Zeitschriften

Revues

recht

Pflegerecht

ZBJV

forumpoenale

ZStrR

Anwaltsrevue

Revue de l'avocat

RSAS

FamPra.ch

ASYL

Life Science Recht

BlAR

Sachbuch

Livres spécialisés

LOKI

Semaphor

Fokusthemen

Focus

Thema

Recht studieren

Arbeitsrecht

Droit du travail

Studium

Études

Familienrecht

Droit de la famille

Sozialversicherungsrecht

Droit des assurances sociales

Strafrecht

Droit pénal

Aktienrecht

Droit des sociétés anonymes

Publikationen

Publications

Literatur

Digitales Angebot

Bücher

Livres

Buchreihen

Collections

Onlinemodule LEXIA

Modules en ligne LEXIA

recht.ch

Studienliteratur

Littérature pour les études

Dienstleistungen

Services

Dienstleistungen für

Corporate Books

Publishing Lösungen

Aktuelles

Geschäftskunden

Professionnels

Corporate Publishing

Content solutions

Buchhandlungen

Librairies

Veranstaltungen

Événements

Presse

Dozierende

Enseignants

Studierende

Étudiants

Inserierende

Annonceurs

Newsletter

Blog

Autorinnen/Autoren

Auteurs

Unsere Schreibenden

Hilfe

Unsere Autorinnen und Autoren

Liste

Autorenlounge

Espace des auteurs

Bei uns publizieren

Publier chez nous

Autorenstimmen

Témoignages

Verlag

Éditions

Themen

Mehr wissen

Mitarbeitende

Collaborateurs

Geschichte

Histoire

Vision und Mission

Vision et mission

Unser Magazin

Notre magazine

Unternehmenskultur

Culture d'entreprise

Partner

Partenaires

Kontakt

Contact

Shop

Schweizer Recht

Ausländisches Recht

Über unseren Shop

Neuerscheinungen

Nouveautés

Unsere Funktionen

Nos fonctions

Vorankündigungen

À paraître

Nach Rechtsgebiet

Par domaine juridique

Kommentare

Commentaires

Gesamtkatalog

Catalogue complet

Scott L: Business Machine Learning

Business Machine Learning

'One of our finest thinkers on technology' - Jamie Bartlett, author of How to Talk to AI Discover the key to clear thinking in the age of AI In a world of alt facts, imperfect algorithms and information overload, thinking clearly has never been more crucial. But it's not easy. It asks us to slow down and reflect; to question assumptions; to be aware of blind spots. It takes practice - and the will to resist a whole host of distractions. How to Think Clearly is a practical primer that will help you: - develop the core habits that underpin critical thinking - master techniques like powerful pauses and killer questions - be data smart and tech savvy - turn these skills into daily practice, making you think twice - and think better

Cut through noise, see the big picture and make better decisions

How to Think Clearly

Energy, Agriculture and Healthcare are key areas which address the development of the nation. Technology plays a vital role in the development of Energy, Agriculture and Healthcare. Development in sustainable Energy technologies will fulfill energy requirements for the long run. Technologies in agriculture will enable farmers to increase yield. Technology in healthcare will improve medical facilities. In today's world technology related to automation, computing, data analysis, sensor, AI/ML, and IoT drives growth in the Energy, Agriculture and Healthcare sector. There is enormous potential to explore, utilize and upgrade technologies in energy, agriculture and healthcare sector. This motivates to organize this conference which provides platform for researchers to exchange/showcase their research findings in the field of energy, agriculture and healthcare. We intend to attract high quality submission by following rigorous review process.There are conferences organized in recent times on advanced technologies independently focusing on energy, agriculture and healthcare. However our conference provides a single and integrated platform for researchers working in the area of energy, agriculture and healthcare with focus on use of IT tools in these area. Our conference is specifically focused on research in the area of Energy, agriculture and healthcare. The conference provides a platform for young researchers and Ph.D. scholars to showcase/share their research findings and get peer reviews and inputs to go further meticulously in their research area. Our conference will be organized in the hybrid mode, which will encourage researchers all over the world to participate and interact with peer researchers. Researchers will get exposure to best practices in their research area. We will be following the peer review process with a plagiarism check to maintain the originality and quality of the research paper. Under each track, researchers will be encouraged by awarding best paper.

Technologies for Energy, Agriculture, and Healthcare

A New York Times and Sunday Times Bestseller Winner of the National Book Critics Circle Award 2025 Longlisted for the 2025 Financial Times &amp; Schroders Business Book of the Year Shortlisted for Foyles Non Fiction Book of the Year 2025 An eye-opening account of the tech arms race shaping out planet, from an award-winning journalist and AI insider to the world of Sam Altman and OpenAI When longtime AI expert and journalist Karen Hao first began covering OpenAI in 2019, she thought they were the good guys. Founded as a nonprofit with safety enshrined as its core mission, it was meant, its leader Sam Altman told us, to act as a check against more purely market forces. But the core truth of this massively disruptive sector is that it requires an unprecedented amount of proprietary resources: the 'compute' power of scarce high-end chips, the sheer volume of data that needs to be amassed at scale, the humans on the ground 'cleaning it up' for sweatshop wages throughout the Global South, and a truly alarming spike in the need for energy and water underlying everything. We have entered a new, ominous age of empire with OpenAI setting a breakneck pace, as a small group of the most valuable companies in human history try to chase it down. In exhilarating prose and with unparalleled access to those closest to Sam Altman, Hao recounts the meteoric rise of OpenAI and shows us the sinister impact that this industry is having on society.

Inside the reckless race for total domination

Empire of AI

This book introduces the subject of artificial intelligence (AI), its structures, uses, application to the artificial neural network, technology applications, and the advantages and disadvantages of its use, including its potential weaknesses and drawbacks. AI, in its broadest sense, is intelligence exhibited by machines, particularly computer systems. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. Such machines may be called AIs. AI technology is widely used throughout industry, government, and science.Some high-profile applications include advanced web search engines (e.g., Google Search); recommendation systems (used by platforms such as YouTube, Amazon, and Netflix); interacting via human speech (e.g., Google Assistant, Siri, and Alexa); autonomous vehicles (e.g., Waymo); generative and creative tools (e.g., ChatGPT, Apple Intelligence, and AI art); and superhuman play and analysis in strategy games (e.g., chess and Go). However, many AI applications are not perceived as AI. It would appear that much of specific AI has filtered into general applications, often without being called AI because once something becomes useful and common enough, it is no longer labelled as AI.The growing use of AI in the 21st century is influencing a societal and economic shift towards increased automation, data-driven decision-making, and the integration of AI systems into various economic and commercial sectors and areas of everyday life. Its impact is felt across job markets, healthcare, government, industry, education, propaganda, and disinformation and deception, whether deliberate or otherwise. This raises questions about the long-term effects, ethical implications, and risks of AI, prompting discussions about regulatory policies to ensure the safety and benefits of the technology.

Advantages, Disadvantages, Benefits, and Threats

Artificial Intelligence

A Comprehensive Introduction

Financial Technology

Machine learning has become an essential component of modern business analytics -- driving insights, optimizing operations, and supporting strategic, data-informed decisions. This textbook offers a hands-on and accessible introduction to applying machine learning in business settings using R, with a strong emphasis on the tidy ecosystem. Key packages such as tidyverse, tidymodels, and tidytext provide a cohesive and efficient framework for data analysis, modeling, and communication.Balancing theoretical foundations with applied practice, the book introduces mathematical ideas in a clear, intuitive manner, always anchored in realistic business scenarios. Suitable for the classroom and independent research, readers will gain the confidence and tools to apply the tidy ecosystem effectively, from data preparation to modeling to interpretation, enabling reproducible, interpretable, and impactful analytics in dynamic business environments.Bowei Chen
 is a Professor of Business Analytics and Artificial Intelligence at the Adam Smith Business School, University of Glasgow, UK, and the Founding Programme Director of the MSc in Business Analytics programme. He received his PhD in Computer Science from the University College London. His research interests include business analytics, artificial intelligence, machine learning, and data science applications in management, finance, and the social sciences. He has published in leading academic conferences, journals, and books in these fields, and has undertaken international research collaborations and academic appointments across different institutions.
 Tianyuan Huang
 is a Lecturer of Data Science and Big Data Technologies at the School of Data Science, Zhejiang University of Finance &amp; Economics, China. He earned his PhD from Fudan University and has authored three R programming books in China. His current research mainly focuses on quantitative science studies, and he is also dedicated to leveraging data science to rapidly build domain expertise and advance scientific knowledge discovery. In addition to his publications, he supports the R community by maintaining several CRAN packages, such as akc for automated knowledge classification and tidyfst for efficient tidy data manipulation.

Machine learning has become an essential component of modern business analytics -- driving insights, optimizing operations, and supporting strategic, data-informed decisions. This textbook offers a hands-on and accessible introduction to applying machine learning in business settings using R, with a strong emphasis on the tidy ecosystem. Key packages such as tidyverse, tidymodels, and tidytext provide a cohesive and efficient framework for data analysis, modeling, and communication.Balancing theoretical foundations with applied practice, the book introduces mathematical ideas in a clear, intuitive manner, always anchored in realistic business scenarios. Suitable for the classroom and independent research, readers will gain the confidence and tools to apply the tidy ecosystem effectively, from data preparation to modeling to interpretation, enabling reproducible, interpretable, and impactful analytics in dynamic business environments.

A Tidy Approach

Business Analytics with R

Toward a deeper understanding of minds, whether natural or artificial, and of how they are studied and built across AI, AGI, and cognitive science. Minds are functional entities that enable intelligent behavior. In On Minds, Paul Rosenbloom offers reflections and perspectives on the study of minds arising from a multi-decade career focused largely on cognitive architectures—hypotheses concerning the fixed structures and processes that yield a mind, whether natural or artificial. Cognitive architectures must be integrative in accommodating the full range of capabilities required of a mind. They must also be general, in applying across many, if not all, problems and domains. This breadth of investigation, across a sequence of three such architectures—XAPS, Soar, and Sigma—and over many years, has inspired a set of reflections on both cognitive architectures and three core disciplines within which such work occurs—artificial intelligence (AI), artificial general intelligence (AGI), and cognitive science. The book’s reflections are of three types. The first explores four concepts critical to understanding minds—architectures, symbols, intelligence, and theories—to provide new perspectives and insights on them. The second rethinks the structure of the space of technologies that underlies work on minds, yielding multidimensional maps that clarify their similarities and differences plus detailed insights into the tradeoffs that exist across both individual technologies and integrated systems—whether symbolic, neural, or hybrid—built from them. The third traces the author’s decades of work on architectures—including cognitive architectures, the Common Model of Cognition, and the nature and structure of computing as a great scientific domain—interwoven with personal reflections and anecdotes.

Toward a deeper understanding of minds, whether natural or artificial, and of how they are studied and built across AI, AGI, and cognitive science. Minds are functional entities that enable intelligent behavior. In On Minds, Paul Rosenbloom offers reflections and perspectives on the study of minds arising from a multi-decade career focused largely on cognitive architectures—hypotheses concerning the fixed structures and processes that yield a mind, whether natural or artificial. Cognitive architectures must be integrative in accommodating the full range of capabilities required of a mind. They must also be general, in applying across many, if not all, problems and domains. This breadth of investigation, across a sequence of three such architectures—XAPS, Soar, and Sigma—and over many years, has inspired a set of reflections on both cognitive architectures and three core disciplines within which such work occurs—artificial intelligence (AI), artificial general intelligence (AGI), and cognitive science. The book’s reflections are of three types. The first explores four concepts critical to understanding minds—architectures, symbols, intelligence, and theories—to provide new perspectives and insights on them. The second rethinks the structure of the space of technologies that underlies work on minds, yielding multidimensional maps that clarify their similarities and differences plus detailed insights into the tradeoffs that exist across both individual technologies and integrated systems—whether symbolic, neural, or hybrid—built from them. The third traces the author’s decades of work on architectures—including cognitive architectures, the Common Model of Cognition, and the nature and structure of computing as a great scientific domain—interwoven with personal reflections and anecdotes.

Reflections of a Cognitive Architect

On Minds

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

Routledge Advances in Organizational Learning and Knowledge Management

This edited volume explores the transformative intersections of education, innovation, and sustainability, with a particular focus on Asian economies. Through rigorous research and real-world case studies, it examines how digital technologies including Artificial Intelligence (AI), Machine Learning (ML), and collaborative learning can drive sustainable growth and organizational transformation. The book provides actionable insights into leveraging digitalization to enhance institutional performance, graduate employability, and environmental sustainability, offering a multidisciplinary framework for advancing the UN Sustainable Development Goals (SDGs). Readers will benefit from case studies on topics such as decarbonization policies, eco-handloom innovations, and corporate governance practices, alongside theoretical discussions on organisational learning, digital knowledge sharing, and innovative pedagogical approaches like collaborative virtual reality platforms. The book also highlights cutting-edge applications of environmental text data mining and sustainable value stream mapping, providing tools for educators, policymakers, and business leaders to foster agile, competitive, and socially responsible organizations. Designed for academics, advanced students, educators, policymakers, and professionals, this volume equips readers with strategies to leverage technology and collaboration for institutional improvement and alignment with global sustainability goals and is an essential resource for those seeking to understand the dynamics of sustainability and digital transformation.

Productivity, Information Technology, and Strategies for the Digital and Green Economy

Organisational Learning Innovations in Asia

Platform Supply Chains in the AI Era

This open access book provides a systematic and in-depth analysis of the critical risks inherent in modern platform-based supply chains. Employing rigorous analytical methods, including game theory and advanced, computationally efficient simulation techniques, it delves into three core areas: operational risks, information and data risks, and quality and compliance risks. The book moves beyond traditional supply chain paradigms to address challenges unique to the platform economy. This includes the strategic threat of platforms using seller data to launch competing products, the complex trade-offs in managing third-party product quality, the impact of reactive capacity on quality decisions, and the challenge of optimizing inventory across networks of unprecedented scale.
 
 It is an essential resource for graduate students, academic researchers, and advanced practitioners in the fields of operations management, supply chain management, and information systems. The content is suitable for readers with a graduate-level understanding of these disciplines.

Risk Management

Platform Supply Chains 5

This book responds to the need to distinguish human creations from those produced by AI. It does so by tracing human attributes of authorship and inventorship in statutory requirements for protection and ownership in European copyright and patent laws. Its main contribution lies in exposing shortcomings in how the laws are applied in the UK, Germany, and France. It shows that the human origin of creations is traditionally inferred from their expressive form or technical character. Given the advancements in AI, such inferences are no longer legitimate. What is more, these shortcomings may eventually lead to granting copyright or patent protection where none is lawfully permitted or sufficiently justified. To remedy the situation, this book offers doctrinal and conceptual amendments and proposes law reforms to implement them. This book guides authorities, practitioners, and students through the main arguments of the debate concerning copyright and patents for objects entirely or partly generated by AI. It also makes original contributions to advance the ongoing academic and policy debates on AI and intellectual property law.

Authorship and Inventorship Revisited

Copyright and Patent Laws for the Age of Artificial Intelligence

Equips legal professionals and stakeholders with a clear, authoritative, and practical guide to the UK legal treatment of digital payments and tokenised assets. The Law of Digital Payments explores the evolving landscape of UK financial law as it adapts to innovations in digital finance. With fintech disrupting traditional models of value exchange, legal professionals must navigate complex regulatory challenges concerning digital wallets, open banking APIs, smart contracts, decentralised finance (DeFi), and the treatment of tokenised assets under common law. This work delves into how UK courts and regulators are addressing these innovations. It provides clarity on the current legal treatment of payment tokens, security tokens, cryptoassets and non-fungible tokens (NFTs). It also investigates the impact of the Financial Services and Markets Act 2023, the Bank of England's stance on central bank digital currencies (CBDCs), and how the Payment Services Regulations and E-Money Regulations are applied to innovative business models. Drawing upon regulatory guidance, case law, and international developments, the book is designed to help practitioners, regulators, academics, and financial institutions understand and navigate the complex intersection of law and digital finance. This title is included in Bloomsbury Professional's Banking and Finance Law online service.

The Law of Digital Payments

Business Machine Learning

Weitere Titel zum Thema