Analysis of Qualcomm's AI Technologies, Patents, and Strategies
2. Patent Distribution Analysis
2.1 Patent Mining
2.2 Patent Analysis
2.2.1 Analysis by Field
2.2.2 Analysis by Core Technologies
2.2.3 Analysis by Smart Applications
2.2.4 Matrix Analysis of Core AI Technologies and Smart Applications
3. Investment Projects Analysis
4. Acquisition Projects Analaysis
5. Conclusions
5.1 Qualcomm Facing Revenue Dilemmas Due to Excessive Focus on Mobile Phone Market
5.2 Investment Focuses on Machine Learning Solutions for Car Electronics, Healthcare, Medical Technology, and Robot Applications
5.3 Core AI Patents Focus on Neural Networks and Natural Language Processing While Machine Learning Patents on the Rise
5.4 Communications Patents Account for Largest Share in AI Applications, Followed by Neuromorphic Computing Hardware, Transport, Healthcare, and Medical Technology
Appendix
Glossary of Terms
List of Companies
List of Tables
Table 1 Development of Qualcomm’s Core AI Technologies
Table 2 Smart Application Areas of Qualcomm’s AI Technologies
Table 3 Matrix Analysis of Qualcomm’s Core AI Technologies and Smart Applications
Table 4 Qualcomm Ventures’ Investment between 2013 and 2017
Table 5 Qualcomm’s M&A between 2013 and 2017
List of Figures
Figure 1 Qualcomm’s Business Model
Figure 2 Qualcomm’s Revenue Structure, 2012 - 2016
Figure 3 Qualcomm’s AI Patent Distribution Share by Field
List Of Tables
Background of Qualcomm, touching on its business model and revenue structure for the period 2012-2016Qualcomms major technology fields, core technologies, and smart applications identified using the data mining technique; also included is the matrix analysis of core AI technologies and smart applications of Qualcomm for the period 2006-2017 (January to May)
Analysis of Qualcomms investment and acquisition projects
Analysis of the worldwide sensor sales value and share in 2011 vs. 2016, by application, by region market
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