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2019 Artificial Intelligence for Transforming Business and Society (AITB 2019) : November 5th, 2019, Kathmandu, Nepal / / Institute of Electrical and Electronics Engineers
| 2019 Artificial Intelligence for Transforming Business and Society (AITB 2019) : November 5th, 2019, Kathmandu, Nepal / / Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Pistacaway, New Jersey : , : IEEE, , [2019] |
| Descrizione fisica | 1 online resource (75 pages) : illustrations |
| Disciplina | 303.4833 |
| Soggetto topico |
Artificial intelligence - Economic aspects
Business enterprises - Information technology |
| ISBN | 1-7281-4220-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | 2019 Artificial Intelligence for Transforming Business and Society |
| Record Nr. | UNISA-996574608403316 |
| Pistacaway, New Jersey : , : IEEE, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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2019 Artificial Intelligence for Transforming Business and Society (AITB 2019) : November 5th, 2019, Kathmandu, Nepal / / Institute of Electrical and Electronics Engineers
| 2019 Artificial Intelligence for Transforming Business and Society (AITB 2019) : November 5th, 2019, Kathmandu, Nepal / / Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Pistacaway, New Jersey : , : IEEE, , [2019] |
| Descrizione fisica | 1 online resource (75 pages) : illustrations |
| Disciplina | 303.4833 |
| Soggetto topico |
Artificial intelligence - Economic aspects
Business enterprises - Information technology |
| ISBN | 1-7281-4220-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | 2019 Artificial Intelligence for Transforming Business and Society |
| Record Nr. | UNINA-9910389515903321 |
| Pistacaway, New Jersey : , : IEEE, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial economics and self organization : agent-based approaches to economics and social systems / / Stephan Leitner, Friederike Wall, editors
| Artificial economics and self organization : agent-based approaches to economics and social systems / / Stephan Leitner, Friederike Wall, editors |
| Autore | Wall Friederike |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | Cham ; ; New York, : Springer, 2014 |
| Descrizione fisica | 1 online resource (258 p.) |
| Disciplina | 330.1 |
| Altri autori (Persone) | LeitnerStephan |
| Collana | Lecture notes in economics and mathematical systems |
| Soggetto topico |
Artificial intelligence - Economic aspects
Economics - Data processing Self-organizing systems |
| ISBN | 3-319-00912-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Methodological Issues -- Macroeconomics -- Market Dynamics -- Self-Organization of Decentralized Markets with Network Externality -- Financial Markets -- Organizations -- Networks. |
| Record Nr. | UNINA-9910298545903321 |
Wall Friederike
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| Cham ; ; New York, : Springer, 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial intelligence for business : a roadmap for getting started with AI / / Jeffrey L Coveyduc, Jason L Anderson
| Artificial intelligence for business : a roadmap for getting started with AI / / Jeffrey L Coveyduc, Jason L Anderson |
| Autore | Coveyduc Jeffrey L |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (xi, 224 pages) : illustrations |
| Disciplina | 658.0563 |
| Soggetto topico | Artificial intelligence - Economic aspects |
| ISBN |
1-119-65141-7
1-119-65180-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910794161203321 |
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Coveyduc Jeffrey L
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| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial intelligence for business : a roadmap for getting started with AI / / Jeffrey L Coveyduc, Jason L Anderson
| Artificial intelligence for business : a roadmap for getting started with AI / / Jeffrey L Coveyduc, Jason L Anderson |
| Autore | Coveyduc Jeffrey L |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (xi, 224 pages) : illustrations |
| Disciplina | 658.0563 |
| Soggetto topico | Artificial intelligence - Economic aspects |
| ISBN |
1-119-65141-7
1-119-65180-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910828424003321 |
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Coveyduc Jeffrey L
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| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence for Risk Mitigation in the Financial Industry
| Artificial Intelligence for Risk Mitigation in the Financial Industry |
| Autore | Mishra Ambrish Kumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (376 pages) |
| Disciplina | 332.0285/63 |
| Altri autori (Persone) |
AnandShweta
DebnathNarayan C PokhariyalPurvi PatelArchana |
| Soggetto topico |
Finance - Technological innovations
Artificial intelligence - Economic aspects |
| ISBN |
1-394-17557-4
1-394-17556-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Artificial Intelligence in Risk Management -- 1.1 Introduction -- 1.1.1 Context and the Driving Force Behind It -- 1.1.2 Aim of This Chapter -- 1.1.3 Outline of This Chapter -- 1.2 The Role of AI in Risk Management -- 1.2.1 The Significance of Risk Management -- 1.2.2 Deficiencies in Conventional Methods of Risk Management -- 1.2.3 The Requirement for Advanced Methods -- 1.3 Role of Artificial Intelligence in Risk Management -- 1.3.1 An Overview of Artificial Intelligence and Its Applications -- 1.3.2 Applications of AI-Based Methods in Risk Management -- 1.4 The Challenges of Implementing AI-Based Risk Management Systems -- 1.5 The Benefits of Using Artificial Intelligence in Risk Management -- 1.6 Conclusions and Future Considerations of AI in Risk Management -- 1.6.1 A Brief Review of the Role of AI in Risk Management -- 1.6.2 Perspectives on the Future -- 1.6.3 The Transformative Power of AI in Risk Management -- 1.7 The Implications and Factors to Take Into Account While Using AI in Risk Management -- 1.8 Overcoming Obstacles and Putting AI to Work in Risk Management -- 1.9 Conclusion -- References -- Chapter 2 Application of Artificial Intelligence in Risk Assessment and Mitigation in Banks -- 2.1 Introduction -- 2.2 Transitions in Banking Due to AI -- 2.3 Risk Assessment and Mitigation through Artificial Intelligence -- 2.3.1 Fraud Recognition -- 2.3.2 Regulatory Compliance Management -- 2.3.3 Credit Risk Modeling -- 2.3.4 Insider Threat Prevention -- 2.4 General Banking Regulations Pertaining to Artificial Intelligence -- 2.5 Methodology -- 2.5.1 Bibliometric Analysis -- 2.5.2 Co-Occurrence Analysis -- 2.6 Theoretical Implications -- 2.7 Managerial Implications -- 2.8 Future Scope -- 2.9 Conclusion -- References.
Chapter 3 Artificial Intelligence and Financial Risk Mitigation -- 3.1 Introduction -- 3.2 Artificial Intelligence, Financial Sector, and Risk Mitigation -- 3.2.1 AI and Financial Risk Detection Processes -- 3.2.2 AI and Financial Risk Recognition Techniques -- 3.2.2.1 Risk Assessment and Prediction -- 3.2.2.2 Fraud Detection and Anticipation -- 3.2.2.3 Risk Modeling and Stress Testing -- 3.2.2.4 Portfolio Optimization and Asset Allocation -- 3.2.2.5 Regulatory Compliance -- 3.2.2.6 Cybersecurity and Data Privacy -- 3.2.2.7 Chatbots and Customer Service -- 3.2.2.8 Loan Underwriting and Processing -- 3.3 Financial Risks and AI Mitigation Practices -- 3.3.1 Credit Risk and Artificial Intelligence -- 3.3.2 Market Risk and Artificial Intelligence -- 3.3.3 Liquidity Risk and Artificial Intelligence -- 3.3.4 Operation Risk and Artificial Intelligence -- 3.3.5 Compliance Risk and Artificial Intelligence -- 3.4 AI and Financial Risk Mitigation Procedures -- 3.4.1 Identification and Assessment of Risks -- 3.4.2 Risk Prioritization -- 3.4.3 Developing Risk Mitigation Policies -- 3.4.4 Implementation of Risk Control Policies -- 3.4.5 Monitor and Evaluate Risk Mitigation Procedures -- 3.4.6 Testing and Validation -- 3.4.7 Continuously Improving the Risk Mitigation Process -- 3.5 Conclusion -- References -- Chapter 4 Artificial Intelligence Adoption in the Indian Banking and Financial Industry: Current Status and Future Opportunities -- 4.1 Introduction -- 4.2 Literature Review -- 4.2.1 Introduction to AI -- 4.2.2 Applications of Artificial Intelligence -- 4.2.2.1 AI Applications in e-Commerce -- 4.2.2.2 Applications of AI in Education -- 4.2.2.3 AI Applications in Agriculture -- 4.2.2.4 Artificial Intelligence in the Banking and Financial Industry -- 4.2.2.5 Utilization of AI in the Indian Banking and Financial Industry -- 4.3 Research Methodology. 4.4 Findings of the Study -- 4.4.1 Current Status of AI-Based Application Adoption in the Indian Banking and Financial Industry -- 4.4.2 Future Opportunities in the Adoption of AI-Based Applications in the Indian Banking and Financial Industry -- 4.4.3 Challenges to the Deployment of AI in the Indian Banking and Financial Services Industry -- 4.5 Conclusion -- References -- Chapter 5 Impact of AI Adoption in Current Trends of the Financial Industry -- 5.1 Introduction -- 5.1.1 Brief Overview of AI Technology -- 5.1.2 Importance of AI Adoption in the Financial Industry -- 5.1.3 Impact of AI on Traditional Financial Services -- 5.2 AI-Based Trading and Investment Management -- 5.2.1 Role of AI in Trading and Investment Management -- 5.2.2 AI-Powered Robot-Advisory Services -- 5.2.3 AI-Based Risk Management and Portfolio Optimization -- 5.3 Fraud Detection and Prevention -- 5.3.1 Role of AI in Fraud Detection and Prevention -- 5.3.2 Real-Time Fraud Monitoring Using AI -- 5.3.3 Machine Learning-Based Fraud Prevention Techniques -- 5.4 Customer Service and Personalization -- 5.4.1 AI-Powered Chatbots for Customer Service -- 5.4.2 Personalized Recommendations and Offerings Using AI -- 5.5 Compliance and Regulatory Reporting -- 5.5.1 Streamlining Regulatory Reporting with AI -- 5.5.2 Risk Assessment and Compliance Monitoring Using AI -- 5.6 Impact of AI on Employment in the Financial Industry -- 5.6.1 Potential Job Displacement Due to AI Adoption -- 5.6.2 Opportunities for New Roles and Skills in the Industry -- 5.6.3 The Need for Reskilling and Upskilling the Workforce -- 5.7 Ethical and Social Implications of AI Adoption -- 5.7.1 Ensuring Transparency and Accountability in AI Decision-Making -- 5.7.2 Ethical Concerns Around AI Adoption in Finance -- 5.7.3 Addressing Potential Biases and Discrimination in AI-Based Financial Services. 5.8 Future of AI Adoption in the Financial Industry -- 5.8.1 Emerging Trends and Technologies in AI Adoption in Finance -- 5.8.2 Opportunities for Innovation and Growth in the Industry -- 5.8.3 Challenges and Limitations to Widespread Adoption of AI -- 5.9 Case Studies on AI Adoption in the Financial Industry -- 5.9.1 ICICI Bank -- 5.9.2 HDFC Bank -- 5.9.3 Bank of America -- 5.9.4 Real-World Examples of Successful AI Adoption in Finance -- 5.9.5 Impact of AI on Business Operations and Customer Experience -- 5.9.6 Lessons Learned From AI Implementation in the Financial Industry -- 5.10 Conclusion and Future Directions -- 5.10.1 Summary of the Key Findings and Insights from the Chapter -- 5.10.2 Recommendations for Future Research and Development in AI Adoption in Finance -- 5.10.3 The Role of Policymakers, Regulators, and Industry Leaders in Shaping the Future of AI in Finance -- 5.11 Conclusion -- References -- Chapter 6 Artificial Intelligence Applications in the Indian Financial Ecosystem -- 6.1 Introduction -- 6.2 Literature Review -- 6.3 Evolution: From Operations to Risk Management -- 6.4 Banking Services -- 6.5 Payment Systems -- 6.6 Digital Lending -- 6.7 Credit Scoring/Creditworthiness/Direct Lending -- 6.8 Stockbrokers and Wealth Management -- 6.9 Mutual Funds and Asset Management -- 6.10 Insurance Services -- 6.11 Indian Financial Regulators -- 6.12 Challenges in Adoption -- 6.13 Conclusion -- References -- Chapter 7 The Extraction of Features That Characterize Financial Fraud Behavior by Machine Learning Algorithms -- 7.1 Introduction -- 7.2 The Framework of Gibbs Sampling Algorithm -- 7.2.1 The Summary of Gibbs Sampling Algorithm -- 7.2.2 The Framework of Associative Feature Extraction Method -- 7.3 The Framework in Screening Features for Corporate Financial Fraud Behaviors. 7.3.1 The Framework of Holographic Risk Assessment Based on the CAFÉ System -- 7.3.2 The Structure of the Company's Financial Fraud Early Warning Risk System -- 7.3.3 The Method for Extracting Financial Fraud Characteristics of Listed Companies -- 7.3.3.1 Static Analysis -- 7.3.3.2 Dynamic (Trend) Analysis -- 7.3.3.3 Comparison of Peers -- 7.3.3.4 The Insight for the Relationship Between Financial Statements and Audits -- 7.3.4 Feature Extraction Based on AUC and ROC Testing for Financial Frauds -- 7.3.5 The Corporate Governance Framework of Financial Fraud Indicators -- 7.4 The Case Study for Financial Frauds from Listed Companies -- 7.4.1 The Case Study Background -- 7.4.2 The Case Study by Qualitative Analysis -- 7.4.3 The Quantitative Analysis Based on the CAFÉ Risk Evaluation System -- 7.4.4 Case Study Results and Remark -- 7.5 Conclusion -- Appendix A: The Description for Eight Types of Financial Frauds -- Appendix B: The Summary of 12 Classes of Data Types in Describing Financial Fraud Behaviors -- References -- Chapter 8 A New Surge of Interest in the Cybersecurity of VIP Clients is the First Step Toward the Return of the Previously Used Positioning Practice in Domestic Private Banking -- 8.1 Introduction -- 8.1.1 Cyber Hygiene -- 8.2 VIP Clients -- 8.3 Cyber Defense Against Simple Threats -- 8.4 Conclusion -- References -- Chapter 9 Determinants of Financial Distress in Select Indian Asset Reconstruction Companies Using Artificial Neural Networks -- Abbreviations -- 9.1 Introduction -- 9.2 Brief Review of Literature -- 9.3 Research Design -- 9.4 Data Analysis and Interpretation -- 9.4.1 Financial Ratio Analysis -- 9.4.2 Altman's Z-Score Analysis -- 9.4.3 Determinants of Financial Distress in Indian ARCs-Analysis Using MLP-ANN -- 9.4.4 Impact of IBC, 2016, on the Capital Structure of Indian ARCs -- 9.5 Conclusion -- References -- Appendices. Chapter 10 The Framework of Feature Extraction for Financial Fraud Behavior and Applications. |
| Record Nr. | UNINA-9910877463803321 |
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Mishra Ambrish Kumar
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial intelligence, automation and the future of competence at work / / Jon-Arild Johannessen
| Artificial intelligence, automation and the future of competence at work / / Jon-Arild Johannessen |
| Autore | Johannessen Jon-Arild |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | London; ; New York, NY : , : Routledge, , [2021] |
| Descrizione fisica | 1 online resource (x, 159 pages) : illustrations |
| Disciplina | 331.25 |
| Collana | Routledge studies in the economics of innovation |
| Soggetto topico |
Labor supply - Effect of automation on
Vocational qualifications Artificial intelligence - Economic aspects Automation - Economic aspects Skilled labor - Effect of automation on |
| ISBN |
1-00-312192-6
1-003-12192-6 1-000-28350-X 1-000-28356-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- List of figures -- 1 Introduction: what competences will be in demand in the Fourth Industrial Revolution? -- Key points in this book -- Introduction -- Narratives -- Description -- Analysis -- Theoretical points -- Practical utility: what can this be used for? -- Conclusion -- Notes -- References -- 2 General and specific competences -- Introduction -- Communication competence -- Narratives -- Description -- Analysis -- Theoretical points -- Practical consequences -- Sub-conclusion -- Creativity -- Narratives -- Description -- Analysis -- Theoretical points -- Practical utility -- Sub-conclusion -- Collaboration -- Narratives -- Description -- Analysis -- Theoretical points -- Practical utility -- Sub-conclusion -- Change -- Narratives -- Description -- Analysis -- Theoretical points -- Practical utility -- Sub-conclusion -- Main conclusion -- Notes -- References -- 3 Human competences -- Key points in the chapter -- Introduction -- Social and emotional competences -- Narratives -- Description -- Analysis -- Theoretical points -- Practical utility -- Sub-conclusion -- Leadership competence -- Narratives -- Description -- Analysis -- Theoretical points -- Practical utility -- Sub-conclusion -- Cultural competence -- Narratives -- Description -- Analysis -- Theoretical points -- Practical utility -- Sub-conclusion -- General conclusion -- Notes -- References -- Index. |
| Record Nr. | UNINA-9910860838303321 |
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Johannessen Jon-Arild
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| London; ; New York, NY : , : Routledge, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Blockchain and artificial intelligence : the world rewired / / edited by Tom James
| Blockchain and artificial intelligence : the world rewired / / edited by Tom James |
| Pubbl/distr/stampa | Boston, Massachusetts : , : De Gruyter, , [2021] |
| Descrizione fisica | 1 online resource (xi, 253 pages) : illustrations |
| Disciplina | 303.4834 |
| Soggetto topico |
Artificial intelligence - Social aspects
Artificial intelligence - Economic aspects |
| Soggetto genere / forma | Electronic books. |
| ISBN |
3-11-066134-9
3-11-066445-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter --; Preface --; Acknowledgments --; Contents --; Chapter 1 Marketing --; Chapter 2 Sales --; Chapter 3 IT Operations --; Chapter 4 Human Resources --; Chapter 5 Contact Centers --; Chapter 6 Building Maintenance --; Chapter 7 Manufacturing --; Chapter 8 Finance and Accounting --; Chapter 9 Customer Experience --; Chapter 10 Maritime Innovation --; Chapter 11 The Coming Revolution --; List of Figures --; About the Editor --; Contributors --; Index. |
| Record Nr. | UNINA-9910554217003321 |
| Boston, Massachusetts : , : De Gruyter, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Brain Rush : How to Invest and Compete in the Real World of Generative AI
| Brain Rush : How to Invest and Compete in the Real World of Generative AI |
| Autore | Cohan Peter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress L. P., , 2024 |
| Descrizione fisica | 1 online resource (406 pages) |
| Disciplina | 006.3 |
| Soggetto topico | Artificial intelligence - Economic aspects |
| ISBN |
9798868803185
9798868803178 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Table of Contents -- About the Author -- Acknowledgments -- Chapter 1: Introducing Brain Rush -- Who I Am and Why I Wrote This Book -- Who Should Read Brain Rush and How Will It Help Them? -- Brain Rush Roadmap -- Chapter 2: What Is Generative AI? -- Defining Generative AI -- Generative AI Examples -- Building Generative AI Applications -- The Two Sides of Generative AI -- Generative AI's Bright Side -- Generative AI's Dark Side -- How I Researched Generative AI -- The Generative AI Ecosystem Model -- Conclusion -- Part I: Mining Generative AI's End-User Value -- Chapter 3: Generative AI Customer End Uses -- Who Uses Generative AI? -- Individual Generative AI Applications -- Consumer End Uses -- Employee End Uses -- Organizational Generative AI Applications -- Which Generative AI End Uses Create the Most Value? -- Healthcare Generative AI Case Studies -- Generative AI Helps Contra Costa County Health Services Answer Patient Questions Faster -- Generative AI Simplifies Patient Consent Forms -- Generative AI Frees Doctors from Transcribing Patient Conversations -- Generative AI Helps Doctors Diagnose Disease -- Financial Services Generative AI Case Studies -- JPMorgan Developing ChatGPT-Like Investment Advisor -- Alpha Keeps State Street's Clients Happy -- Goldman Sachs Tests Generative AI -- Principles of Successful Generative AI Deployment -- What to Do -- What to Avoid -- How End Users Can Make the Most of Generative AI -- Conclusion -- Part II: Mapping the Generative AI Ecosystem -- Chapter 4: Generative AI Consulting -- Generative AI Consulting Industry Players -- Generative AI Consulting Industry Attractiveness -- Generative AI Consulting Industry Participants -- Strategists -- McKinsey -- Boston Consulting Group -- Risk and Process Managers -- EY -- KPMG -- PwC -- Coding Outsourcers -- Cognizant.
Generative AI Consulting Critical Activities -- Conclusion -- Chapter 5: Generative AI Software -- Generative AI Software Industry Players -- Generative AI Software Industry Attractiveness -- Generative AI Software Industry Participants -- Publicly Traded Proprietary LLM Providers -- Microsoft -- Google -- Privately Held Proprietary LLM Providers -- OpenAI -- Cohere -- Anthropic -- Open Source LLM Providers -- Hugging Face -- Meta Platforms' Llama -- Publicly Traded Application-Specific Generative AI Application Providers -- Adobe -- ServiceNow -- Privately Held Application-Specific Generative AI Application Provider -- Hyro -- Writer -- Generative AI Software Critical Activities -- Conclusion -- Chapter 6: Generative AI Cloud Platforms -- Generative AI Cloud Platform Industry Players -- Generative AI Cloud Platform Industry Attractiveness -- Generative AI Cloud Platform Industry Participants -- Generative AI Cloud Services Provider Subsidiaries of Public Companies -- Amazon Web Services -- Microsoft Azure -- Google Cloud -- Publicly Traded Generative AI Data Centers -- Equinix -- Publicly Traded Generative AI Networking Technology Providers -- Arista Networks -- Generative AI Database Providers -- MongoDB -- Snowflake -- Databricks -- Publicly Traded Generative AI Application Performance Monitoring Service Providers -- Datadog -- Generative AI Cloud Services Critical Activities -- Conclusion -- Chapter 7: Generative AI Hardware -- Generative AI Hardware Industry Players -- Generative AI Semiconductor Industry Attractiveness -- Generative AI Hardware Industry Participants -- Publicly Traded Generative AI Semiconductor Companies -- AMD -- Nvidia -- TSMC -- Publicly Traded Semiconductor Manufacturing Equipment Suppliers -- ASML -- Publicly Traded Computer Server Manufacturers -- Dell -- Super Micro Computer. Publicly Traded Data Center Cooling Product Manufacturers -- Vertiv -- Generative AI Hardware Critical Activities -- Conclusion -- Part III: Panning for Generative AI Gold -- Chapter 8: Generative AI's Implications for Consumers, Employees, Companies, Product Providers, and Investors -- How Consumers Can Benefit from Generative AI -- High-Payoff Generative AI Experiments -- Consumer Generative AI Dos and Don'ts -- How Consumers Can Capture Generative AI's Value -- Prompt and Response 1: Provide Four Options for a New Office Chair -- Prompt and Response 2: Compare Four Options on Customer Reviews, Ease of Assembly, Useful Life, and Price Range -- Prompt and Response 3: Assess Whether the Quality of the Highest Priced Chair Justifies Its Price -- How Employees and Business Operators Can Benefit from Generative AI -- High-Payoff Generative AI Experiments -- Employee and Business Operator Generative AI Dos and Don'ts -- How Employees and Business Operators Can Capture Generative AI's Value -- Growth Strategies for Generative AI Product Providers -- High-Payoff Generative AI Strategies -- Generative AI Product Provider Dos and Don'ts -- How Product Providers Can Capture Generative AI's Value -- How Investors Can Profit from Generative AI -- A Goldman Sachs Perspective on Generative AI-Driven Growth -- Generative AI Investment Dos and Don'ts -- How Investors Can Capture Generative AI's Value -- Conclusion -- Chapter 9: Generative AI's Benefits and Risks to Society -- Generative AI's Influence -- The Light Side: Generative AI's Societal Benefits -- Boosting Global Growth -- Increasing Worker Productivity -- Adding New Jobs in Tech-Rich Regions -- Creating Demand in Supplier Industries -- The Dark Side: Generative AI's Societal Costs and Risks -- Creating Misinformation -- Boosting Legal Liability -- Displacing Workers -- Ending Civilization. Holding Generative AI Providers Accountable -- How Government Should Regulate Generative AI -- Actions Citizens Should Take with Generative AI's Light and Dark Sides -- Conclusion -- Chapter 10: After the Brain Rush: What Is Generative AI's Future? -- Generative AI and How It Is Likely to Evolve -- Does Generative AI Matter or Is It a Temporary Fad? -- Groups Likely to Be Generative AI Winners and Losers -- The Most Beneficial Uses of Generative AI -- Consumers -- Employees -- Business Leaders -- Publicly Traded Generative AI Product and Services Providers That Make the Best Investments -- Government Policies That Limit the Harm and Maximize the Benefit of Generative AI -- Conclusion -- Index. |
| Record Nr. | UNINA-9910872190403321 |
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Cohan Peter
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| Berkeley, CA : , : Apress L. P., , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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China's pursuit of emerging and exponential technologies : hearing before the Subcommittee on Emerging Threats and Capabilities of the Committee on Armed Services, House of Representatives, One Hundred Fifteenth Congress, second session : hearing held January 9, 2018
| China's pursuit of emerging and exponential technologies : hearing before the Subcommittee on Emerging Threats and Capabilities of the Committee on Armed Services, House of Representatives, One Hundred Fifteenth Congress, second session : hearing held January 9, 2018 |
| Pubbl/distr/stampa | Washington : , : U.S. Government Publishing Office, , 2019 |
| Descrizione fisica | 1 online resource (iii, 82 pages) |
| Soggetto topico |
Technology transfer - United States
Technology transfer - Government policy - China Business intelligence - China Artificial intelligence - Economic aspects - China Artificial intelligence - Economic aspects - United States Artificial intelligence - Military applications - China Military art and science - Technological innovations - China Cyberterrorism - United States - Prevention Artificial intelligence - Economic aspects Artificial intelligence - Military applications Business intelligence Cyberterrorism - Prevention Military art and science - Technological innovations Technology transfer Technology transfer - Government policy |
| Soggetto genere / forma |
Online resources.
Legislative hearings. |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | China's pursuit of emerging and exponential technologies |
| Record Nr. | UNINA-9910711856703321 |
| Washington : , : U.S. Government Publishing Office, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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