Literaturnachweis - Detailanzeige
Autor/inn/en | Chui, Michael; Manyika, James; Miremadi, Mehdi; Henke, Nicolaus; Chung, Rita; Nel, Pieter; Malhotra, Sankalp |
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Institution | McKinsey & Company (Washington, DC) |
Titel | Notes from the AI frontier. Insights from hundreds of use cases. |
Quelle | Washington, DC (2018), 31 S.
PDF als Volltext (1); PDF als Volltext (2) |
Reihe | McKinsey Global Institute. Discussion paper |
Sprache | englisch |
Dokumenttyp | online; gedruckt; Monografie |
Schlagwörter | Leistungsfähigkeit; Künstliche Intelligenz; Lernen; Neuronales Netz; Technologische Entwicklung; Anwendung; Entwicklungspotenzial; Innovation; Innovationspotenzial; Netzwerk; Datenverarbeitung; USA |
Abstract | "This discussion paper seeks to contribute to the body of knowledge about AI by mapping AI techniques to the types of problems they can help solve and then mapping these problem types to more than 400 practical use cases and applications in businesses across 19 industries, from aerospace and defense to travel and the public sector, and nine business functions ranging from marketing and sales and supply-chain management to product development and human resources. Drawing on a wide variety of public and proprietary data sources, including the experiences of our McKinsey & Company colleagues, we also assess the potential economic value of the latest generations of AI technologies. The AI techniques we focus on are deep learning techniques based on artificial neural networks, which we see as generating as much as 40 percent of the total potential value that all analytics techniques could provide." (Text excerpt, IAB-Doku). |
Erfasst von | Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg |
Update | 2018/4 |