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Amazon's Patent Deployment Strategies for Artificial Intelligence and Its M&A Analysis

  • Report

  • 24 Pages
  • November 2018
  • Region: Global
  • Market Intelligence & Consulting Institute (MIC)
  • ID: 4702697

Amazon Technologies started as an online bookshop and has been devoted to developing in-house technologies, making strategic investment in startups, and acquiring other companies to fulfill its promise of putting the customer first. These efforts have successfully turned Amazon Technologies into an e-commerce company and a cloud platform provider. In the wake of the widespread adoption of AI (Artificial Intelligence) in emerging applications, which has imposed a significant impact on the industry, the company has spared no effort to invest in AI so as to seize the market opportunity.

This report provides an overview of the technology and patent deployment of Amazon pertaining to AI; analyzes Amazon's patent portfolios in the areas of neural networks, genetic algorithm, knowledge engineering, fuzzy logic, machine learning, and natural language processing; examines its recent investments and M&A activities to better understand the company's strategic deployment in AI for the future.

List of Topics

  • Amazon's patent portfolios in AI and includes its patent distribution by field, technology, and intelligence application
  • Overview of Amazon's investments and includes its patent distribution in emerging fields
  • Amazon AI patents' six key technology and three intelligent application matrix
  • Analysis of implications behind Amazon's investments and M&A activities for the period 2013-2017

Table of Contents


1. Company History
2. Patent Deployment
2.1 Patent Mining
2.2 Patent Analysis
2.2.1 Analysis by Field
2.2.2 Analysis by Core Technology
2.2.3 Intelligent Applications
2.3.4 Matrix Analysis of AI Technology with Intelligent Applications
3. Analysis of Amazon's Investment Projects4. Analysis of Amazon's M&A Activity5. Author's Perspectives6. Appendix7. Glossary of Terms8. List of Companies
List of Tables
Table 1 Amazon's Patent Counts by Technology, 2006 - 2017
Table 2 Patent Count by Application, 2006 - 2017
Table 3 Matrix Analysis of Amazon's AI Core Technologies with Intelligent Applications
Table 4 Amazon's Investments in Emerging Application Areas, 2013 - 2017
List of Figures
Figure 1 Amazon's Business Model Built around Customer Experience
Figure 2 Amazon's Revenue Breakdowns by Business Unit, 2012 - 2016
Figure 3 Amazon's Patent Count by Field

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • 2lemetry
  • Amazon
  • Amiato
  • Angel.ai
  • Annapurna Labs
  • AppThwack
  • Biba
  • Body Labs
  • Cloud9 IDE
  • Clusterk
  • Comixology
  • DefinedCrowd
  • Do
  • Double Helix Games
  • Elemental Technologies
  • Embodied
  • Emvantage Payments
  • Evi
  • GameSparks
  • Goodreads
  • GraphiqHarvest.ai
  • Ivona Text-To-Speech
  • KITT
  • Liquavista
  • NICE
  • OpenDNA
  • Orbeus
  • Rooftop Media
  • Safaba Translation Solutions
  • Shoefitr
  • Souq.com
  • TenMarks Education
  • Thinkbox Software
  • Twitch
  • United States Patent and Trademark Office
  • Whole Foods Market
  • World Intellectual Property Organization

Methodology

Primary research with a holistic, cross-domain approach

The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.

Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:

Method

  • Component supplier interviews
  • System supplier interviews
  • User interviews
  • Channel interviews
  • IPO interviews
  • Focus groups
  • Consumer surveys
  • Production databases
  • Financial data
  • Custom databases

Methodology

  • Technology forecasting and assessment
  • Product assessment and selection
  • Product life cycles
  • Added value analysis
  • Market trends
  • Scenario analysis
  • Competitor analysis

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