Artificial Intelligence for Industries of the Future: Beyond Facebook, Amazon, Microsoft and Google
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer International Publishing AG
2022
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | Future of Business and Finance Series
|
| Schlagworte: | |
| Online-Zugang: | DE-2070s |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (165 Seiten) |
| ISBN: | 9783031190391 |
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| 505 | 8 | |a Intro -- Preface -- Acknowledgments -- Contents -- Acronyms -- 1 Artificial Intelligence: An Introduction -- 1.1 Introduction -- 1.2 Artificial Intelligence (AI) -- 1.3 AI, Machine Learning, and Deep Learning -- 1.3.1 Types of Machine Learning -- 1.4 Industry 4.0 Versus Industries of the Future -- 1.5 Other (Non-AI) Drivers of Industries of the Future -- 1.5.1 Quantum Information Science (QIS) -- 1.5.2 5G and Advanced Communication -- 1.5.3 Advanced Manufacturing -- 1.5.4 Biotechnology -- 1.6 Where Will Industries of the Future Come From? -- 1.7 The Role of Research -- 1.8 Future Developments -- References -- 2 AI in Practice and Implementation: Issues and Costs -- 2.1 Introduction -- 2.2 Challenges in Implementing AI -- 2.2.1 Data Acquisition -- 2.2.2 Data Quality -- 2.2.3 Privacy and Compliance -- 2.2.4 AI Quality Metrics -- 2.3 Guidelines and Practices for Measuring Return on Investment (ROI) of AI Projects -- 2.3.1 Traditional Valuation Approaches and Their Pitfalls for Valuing AI Projects -- 2.3.2 Soft Versus Hard Returns and Investments -- 2.4 Digital Technology and the Productivity Puzzle -- 2.5 Conclusion -- References -- 3 AI in Industry Today -- 3.1 Introduction -- 3.2 AI in Big Tech -- 3.2.1 Alphabet -- 3.2.2 Amazon -- 3.2.3 Meta -- 3.2.4 Other Big Tech: Microsoft and Apple -- 3.2.5 Other Large Tech Firms in the United States -- 3.2.6 The Chinese ''Big Tech'' -- 3.3 Large Firms Outside Big Tech -- 3.4 Startups and Small/Medium-Sized Enterprises (SBEs) -- 3.5 Case Study: Neural Language Models -- 3.5.1 Can Transformers Automate Software Engineers? -- 3.5.2 Applications Beyond NLP -- 3.5.3 Potential Ethical Concerns -- 3.5.4 Summary -- 3.6 Conclusion -- References -- 4 Augmented Artificial Intelligence -- 4.1 Introduction -- 4.2 Augmented AI Versus Complete Automation -- 4.3 Key Features and Example Applications | |
| 505 | 8 | |a 4.4 A Case Study in Augmented AI: Radiology -- 4.5 Changes in the Workforce -- 4.5.1 How Will Organizations Change? -- 4.5.2 Demand for Technological Skills -- 4.5.3 Cognitive Skills and the Future of Work: Is There a Mismatch? -- 4.5.4 New-Collar Versus White-Collar Jobs -- 4.5.5 Adaptation in the C-Suite -- 4.6 Automation and the Future of Work: Examples from Three Industrial Sectors -- 4.6.1 Banking and Insurance -- 4.6.2 Manufacturing -- 4.6.3 Retail -- 4.7 Conclusion -- References -- 5 AI Ethics and Policy -- 5.1 Introduction -- 5.2 AI Versus Digital Ethics -- 5.3 The Philosophy of Ethics: A Brief Review -- 5.4 AI Ethics in Policy -- 5.4.1 Case Study 1: The European Union General Data Protection Regulation (GDPR) -- 5.4.1.1 Enforcement of GDPR -- 5.4.2 Case Study 2: The United States National Defense Authorization Act (NDAA) -- 5.5 AI Ethics in Research and Higher Education -- 5.6 Conclusion -- References -- 6 What Is on the Horizon? -- 6.1 Introduction -- 6.2 Can AI Copyright Its Own Art? -- 6.3 Legal Issues Around Deepfakes -- 6.4 AI's Explainability Crisis -- 6.5 More Vigorous Algorithmic Regulation -- 6.6 Increasing Convergence of Emerging Technologies -- 6.7 Concluding Notes -- References -- Glossary -- References -- Index | |
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Datensatz im Suchindex
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| contents | Intro -- Preface -- Acknowledgments -- Contents -- Acronyms -- 1 Artificial Intelligence: An Introduction -- 1.1 Introduction -- 1.2 Artificial Intelligence (AI) -- 1.3 AI, Machine Learning, and Deep Learning -- 1.3.1 Types of Machine Learning -- 1.4 Industry 4.0 Versus Industries of the Future -- 1.5 Other (Non-AI) Drivers of Industries of the Future -- 1.5.1 Quantum Information Science (QIS) -- 1.5.2 5G and Advanced Communication -- 1.5.3 Advanced Manufacturing -- 1.5.4 Biotechnology -- 1.6 Where Will Industries of the Future Come From? -- 1.7 The Role of Research -- 1.8 Future Developments -- References -- 2 AI in Practice and Implementation: Issues and Costs -- 2.1 Introduction -- 2.2 Challenges in Implementing AI -- 2.2.1 Data Acquisition -- 2.2.2 Data Quality -- 2.2.3 Privacy and Compliance -- 2.2.4 AI Quality Metrics -- 2.3 Guidelines and Practices for Measuring Return on Investment (ROI) of AI Projects -- 2.3.1 Traditional Valuation Approaches and Their Pitfalls for Valuing AI Projects -- 2.3.2 Soft Versus Hard Returns and Investments -- 2.4 Digital Technology and the Productivity Puzzle -- 2.5 Conclusion -- References -- 3 AI in Industry Today -- 3.1 Introduction -- 3.2 AI in Big Tech -- 3.2.1 Alphabet -- 3.2.2 Amazon -- 3.2.3 Meta -- 3.2.4 Other Big Tech: Microsoft and Apple -- 3.2.5 Other Large Tech Firms in the United States -- 3.2.6 The Chinese ''Big Tech'' -- 3.3 Large Firms Outside Big Tech -- 3.4 Startups and Small/Medium-Sized Enterprises (SBEs) -- 3.5 Case Study: Neural Language Models -- 3.5.1 Can Transformers Automate Software Engineers? -- 3.5.2 Applications Beyond NLP -- 3.5.3 Potential Ethical Concerns -- 3.5.4 Summary -- 3.6 Conclusion -- References -- 4 Augmented Artificial Intelligence -- 4.1 Introduction -- 4.2 Augmented AI Versus Complete Automation -- 4.3 Key Features and Example Applications 4.4 A Case Study in Augmented AI: Radiology -- 4.5 Changes in the Workforce -- 4.5.1 How Will Organizations Change? -- 4.5.2 Demand for Technological Skills -- 4.5.3 Cognitive Skills and the Future of Work: Is There a Mismatch? -- 4.5.4 New-Collar Versus White-Collar Jobs -- 4.5.5 Adaptation in the C-Suite -- 4.6 Automation and the Future of Work: Examples from Three Industrial Sectors -- 4.6.1 Banking and Insurance -- 4.6.2 Manufacturing -- 4.6.3 Retail -- 4.7 Conclusion -- References -- 5 AI Ethics and Policy -- 5.1 Introduction -- 5.2 AI Versus Digital Ethics -- 5.3 The Philosophy of Ethics: A Brief Review -- 5.4 AI Ethics in Policy -- 5.4.1 Case Study 1: The European Union General Data Protection Regulation (GDPR) -- 5.4.1.1 Enforcement of GDPR -- 5.4.2 Case Study 2: The United States National Defense Authorization Act (NDAA) -- 5.5 AI Ethics in Research and Higher Education -- 5.6 Conclusion -- References -- 6 What Is on the Horizon? -- 6.1 Introduction -- 6.2 Can AI Copyright Its Own Art? -- 6.3 Legal Issues Around Deepfakes -- 6.4 AI's Explainability Crisis -- 6.5 More Vigorous Algorithmic Regulation -- 6.6 Increasing Convergence of Emerging Technologies -- 6.7 Concluding Notes -- References -- Glossary -- References -- Index |
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| dewey-ones | 006 - Special computer methods |
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| discipline | Informatik |
| edition | 1st ed |
| format | Electronic eBook |
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| indexdate | 2024-09-19T05:21:46Z |
| institution | BVB |
| isbn | 9783031190391 |
| language | English |
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| spelling | Kejriwal, Mayank Verfasser aut Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google 1st ed Cham Springer International Publishing AG 2022 ©2023 1 Online-Ressource (165 Seiten) txt rdacontent c rdamedia cr rdacarrier Future of Business and Finance Series Description based on publisher supplied metadata and other sources Intro -- Preface -- Acknowledgments -- Contents -- Acronyms -- 1 Artificial Intelligence: An Introduction -- 1.1 Introduction -- 1.2 Artificial Intelligence (AI) -- 1.3 AI, Machine Learning, and Deep Learning -- 1.3.1 Types of Machine Learning -- 1.4 Industry 4.0 Versus Industries of the Future -- 1.5 Other (Non-AI) Drivers of Industries of the Future -- 1.5.1 Quantum Information Science (QIS) -- 1.5.2 5G and Advanced Communication -- 1.5.3 Advanced Manufacturing -- 1.5.4 Biotechnology -- 1.6 Where Will Industries of the Future Come From? -- 1.7 The Role of Research -- 1.8 Future Developments -- References -- 2 AI in Practice and Implementation: Issues and Costs -- 2.1 Introduction -- 2.2 Challenges in Implementing AI -- 2.2.1 Data Acquisition -- 2.2.2 Data Quality -- 2.2.3 Privacy and Compliance -- 2.2.4 AI Quality Metrics -- 2.3 Guidelines and Practices for Measuring Return on Investment (ROI) of AI Projects -- 2.3.1 Traditional Valuation Approaches and Their Pitfalls for Valuing AI Projects -- 2.3.2 Soft Versus Hard Returns and Investments -- 2.4 Digital Technology and the Productivity Puzzle -- 2.5 Conclusion -- References -- 3 AI in Industry Today -- 3.1 Introduction -- 3.2 AI in Big Tech -- 3.2.1 Alphabet -- 3.2.2 Amazon -- 3.2.3 Meta -- 3.2.4 Other Big Tech: Microsoft and Apple -- 3.2.5 Other Large Tech Firms in the United States -- 3.2.6 The Chinese ''Big Tech'' -- 3.3 Large Firms Outside Big Tech -- 3.4 Startups and Small/Medium-Sized Enterprises (SBEs) -- 3.5 Case Study: Neural Language Models -- 3.5.1 Can Transformers Automate Software Engineers? -- 3.5.2 Applications Beyond NLP -- 3.5.3 Potential Ethical Concerns -- 3.5.4 Summary -- 3.6 Conclusion -- References -- 4 Augmented Artificial Intelligence -- 4.1 Introduction -- 4.2 Augmented AI Versus Complete Automation -- 4.3 Key Features and Example Applications 4.4 A Case Study in Augmented AI: Radiology -- 4.5 Changes in the Workforce -- 4.5.1 How Will Organizations Change? -- 4.5.2 Demand for Technological Skills -- 4.5.3 Cognitive Skills and the Future of Work: Is There a Mismatch? -- 4.5.4 New-Collar Versus White-Collar Jobs -- 4.5.5 Adaptation in the C-Suite -- 4.6 Automation and the Future of Work: Examples from Three Industrial Sectors -- 4.6.1 Banking and Insurance -- 4.6.2 Manufacturing -- 4.6.3 Retail -- 4.7 Conclusion -- References -- 5 AI Ethics and Policy -- 5.1 Introduction -- 5.2 AI Versus Digital Ethics -- 5.3 The Philosophy of Ethics: A Brief Review -- 5.4 AI Ethics in Policy -- 5.4.1 Case Study 1: The European Union General Data Protection Regulation (GDPR) -- 5.4.1.1 Enforcement of GDPR -- 5.4.2 Case Study 2: The United States National Defense Authorization Act (NDAA) -- 5.5 AI Ethics in Research and Higher Education -- 5.6 Conclusion -- References -- 6 What Is on the Horizon? -- 6.1 Introduction -- 6.2 Can AI Copyright Its Own Art? -- 6.3 Legal Issues Around Deepfakes -- 6.4 AI's Explainability Crisis -- 6.5 More Vigorous Algorithmic Regulation -- 6.6 Increasing Convergence of Emerging Technologies -- 6.7 Concluding Notes -- References -- Glossary -- References -- Index Artificial intelligence Erscheint auch als Druck-Ausgabe Kejriwal, Mayank Artificial Intelligence for Industries of the Future Cham : Springer International Publishing AG,c2022 9783031190384 |
| spellingShingle | Kejriwal, Mayank Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google Intro -- Preface -- Acknowledgments -- Contents -- Acronyms -- 1 Artificial Intelligence: An Introduction -- 1.1 Introduction -- 1.2 Artificial Intelligence (AI) -- 1.3 AI, Machine Learning, and Deep Learning -- 1.3.1 Types of Machine Learning -- 1.4 Industry 4.0 Versus Industries of the Future -- 1.5 Other (Non-AI) Drivers of Industries of the Future -- 1.5.1 Quantum Information Science (QIS) -- 1.5.2 5G and Advanced Communication -- 1.5.3 Advanced Manufacturing -- 1.5.4 Biotechnology -- 1.6 Where Will Industries of the Future Come From? -- 1.7 The Role of Research -- 1.8 Future Developments -- References -- 2 AI in Practice and Implementation: Issues and Costs -- 2.1 Introduction -- 2.2 Challenges in Implementing AI -- 2.2.1 Data Acquisition -- 2.2.2 Data Quality -- 2.2.3 Privacy and Compliance -- 2.2.4 AI Quality Metrics -- 2.3 Guidelines and Practices for Measuring Return on Investment (ROI) of AI Projects -- 2.3.1 Traditional Valuation Approaches and Their Pitfalls for Valuing AI Projects -- 2.3.2 Soft Versus Hard Returns and Investments -- 2.4 Digital Technology and the Productivity Puzzle -- 2.5 Conclusion -- References -- 3 AI in Industry Today -- 3.1 Introduction -- 3.2 AI in Big Tech -- 3.2.1 Alphabet -- 3.2.2 Amazon -- 3.2.3 Meta -- 3.2.4 Other Big Tech: Microsoft and Apple -- 3.2.5 Other Large Tech Firms in the United States -- 3.2.6 The Chinese ''Big Tech'' -- 3.3 Large Firms Outside Big Tech -- 3.4 Startups and Small/Medium-Sized Enterprises (SBEs) -- 3.5 Case Study: Neural Language Models -- 3.5.1 Can Transformers Automate Software Engineers? -- 3.5.2 Applications Beyond NLP -- 3.5.3 Potential Ethical Concerns -- 3.5.4 Summary -- 3.6 Conclusion -- References -- 4 Augmented Artificial Intelligence -- 4.1 Introduction -- 4.2 Augmented AI Versus Complete Automation -- 4.3 Key Features and Example Applications 4.4 A Case Study in Augmented AI: Radiology -- 4.5 Changes in the Workforce -- 4.5.1 How Will Organizations Change? -- 4.5.2 Demand for Technological Skills -- 4.5.3 Cognitive Skills and the Future of Work: Is There a Mismatch? -- 4.5.4 New-Collar Versus White-Collar Jobs -- 4.5.5 Adaptation in the C-Suite -- 4.6 Automation and the Future of Work: Examples from Three Industrial Sectors -- 4.6.1 Banking and Insurance -- 4.6.2 Manufacturing -- 4.6.3 Retail -- 4.7 Conclusion -- References -- 5 AI Ethics and Policy -- 5.1 Introduction -- 5.2 AI Versus Digital Ethics -- 5.3 The Philosophy of Ethics: A Brief Review -- 5.4 AI Ethics in Policy -- 5.4.1 Case Study 1: The European Union General Data Protection Regulation (GDPR) -- 5.4.1.1 Enforcement of GDPR -- 5.4.2 Case Study 2: The United States National Defense Authorization Act (NDAA) -- 5.5 AI Ethics in Research and Higher Education -- 5.6 Conclusion -- References -- 6 What Is on the Horizon? -- 6.1 Introduction -- 6.2 Can AI Copyright Its Own Art? -- 6.3 Legal Issues Around Deepfakes -- 6.4 AI's Explainability Crisis -- 6.5 More Vigorous Algorithmic Regulation -- 6.6 Increasing Convergence of Emerging Technologies -- 6.7 Concluding Notes -- References -- Glossary -- References -- Index Artificial intelligence |
| title | Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google |
| title_auth | Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google |
| title_exact_search | Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google |
| title_full | Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google |
| title_fullStr | Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google |
| title_full_unstemmed | Artificial Intelligence for Industries of the Future Beyond Facebook, Amazon, Microsoft and Google |
| title_short | Artificial Intelligence for Industries of the Future |
| title_sort | artificial intelligence for industries of the future beyond facebook amazon microsoft and google |
| title_sub | Beyond Facebook, Amazon, Microsoft and Google |
| topic | Artificial intelligence |
| topic_facet | Artificial intelligence |
| work_keys_str_mv | AT kejriwalmayank artificialintelligenceforindustriesofthefuturebeyondfacebookamazonmicrosoftandgoogle |