人工知能(AI)の世界市場:技術、インフラ、構成要素、機器、ソリューション

Mind Commerceが発行した調査報告書(DATA905002)
◆英語タイトル:Artificial Intelligence Market by Technology, Infrastructure, Components, Devices, Solutions, and Industry Verticals 2019 – 2024
◆商品コード:DATA905002
◆発行会社(リサーチ会社):Mind Commerce
◆発行日:2019年4月
◆ページ数:413
◆レポート形式:英語 / PDF
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◆調査対象地域:グローバル
◆産業分野:情報技術・通信
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【レポートの概要】

Artificial Intelligence (AI) represents a combination of various technologies including Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Speech Recognition, Context Aware Processing, Neural Network, and Predictive APIs. AI will be found in virtually everything, ranging from individual products and applications to wide spread systems and networks. Network infrastructure and computing equipment will rely upon AI algorithms for decision making while at the device level AI will be built into electronics at the chipset level.
This report provides a multi-dimensional view into the AI market including analysis of embedded devices and components, embedded software, and AI platforms. This research also assesses the combined Artificial Intelligence (AI) marketplace including embedded IoT and non-IoT devices, embedded components (including AI chipsets), embedded software and AI platforms, and related services.

The report evaluates leading solution providers including hardware, software, integrated platforms, and services. The report includes quantitative analysis with forecasts covering AI technology and systems by type, use case, application, and industry vertical. Forecast also cover each major market sector including consumer, enterprise, industrial, and government. The report also includes specific industry recommendations with respect to Artificial Intelligence hardware, software and services including:

• AI Chipsets: The AI chipset marketplace is poised to transform the entire embedded system ecosystem with a multitude of AI capabilities such as deep machine learning, image detection, and many others. This will also be transformational for existing critical business functions such as Identity management, authentication, and cybersecurity. Multi-processor AI chipsets learn from the environment, users, and machines to uncover hidden pattern among data, predict actionable insight, and perform actions based on specific situations. AI chipsets will become an integral part of both AI software/systems as well as critical support of any data-intensive operation as they drastically improve processing for various functions as well as enhance overall computing performance.

• AI in Edge Networks: Computing at the edge of IT and communications networks will require a different kind of intelligence. AI will be required for both security (data and infrastructure) as well as to optimize the flow of information in the form of streaming data and the ability to optimize decision-making via real-time data analytics. Edge networks will be the “point of the spear” so to speak when it comes to data handling, meaning that streaming data will be available for processing and decision-making. While advanced data analytics software solutions can be very effective for this purpose, there will be opportunities to enhance real-time data analytics by way of leveraging AI to automate decision making and to engage machine learning for ongoing efficiency and effectiveness improvements.

• AI and 5G: The role and importance of AI in 5G ranges from optimizing resource allocation to data security and protection of network and enterprise assets. However, the concept of using AI in networking is relatively new area that will ultimately require a more unified approach to fully realize its great potential. In addition, AI will assist 5G network slicing, which represents the ability to dynamically allocate bandwidth, and enforce associated service level agreements, and a per-customer and per-application basis. AI will automate the process of assigning network slices, including informing enterprise customers when the slices they are requesting are not in their best interest based on anticipated network conditions.

• AI and Real-time Data Processing: The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic. In addition, AI will support data management across all of these areas. The growing amount of human-oriented and machine generated from communications, applications, content, and commerce data will drive substantial opportunities for AI support of unstructured data analytics solutions.

The outlook for AI in support of the ICT industry is strong, especially when one considers that the purpose of telecom and IT services is to support virtually every other industry in terms of communications, applications, content, and commerce.

Select Report Findings:

• The global context-aware processing market will reach $5.3B by 2024
• AI in IoT Devices will reach $9.5B in North America by 2024 with 28.% CAGR
• The AI in manufacturing market will reach $15.5B globally by 2024 with 35.3% CAGR
• Asia Pac and North America AI markets will reach $44.4B and $42.3B respectively by 2024
• Starting with consumer appliances and electronics AIoT will be a significant driver of AI adoption

【レポートの目次】

1.0 Introduction
1.1 Executive Summary
1.2 Research Objectives
1.3 Select Findings
1.4 Target Audience
1.5 Companies in the Report
2.0 Overview
2.1 Defining Artificial Intelligence
2.2 Artificial General Intelligence
2.3 Artificial Super Intelligence
2.4 Artificial Intelligence Types
2.5 Artificial Intelligence Language
2.6 Artificial Intelligence Systems
2.7 AI Outcomes and Enterprise Benefits
2.8 Conversational User Interfaces
2.9 Cognitive Computing and Swarm Intelligence
2.10 AI Market Drivers and Impact
2.11 AI Market Constraints
2.12 AI Market Opportunities
2.13 AI Market Outlook and Predictions
3.0 Technology Impact Analysis
3.1 AI Technology Matrix
3.1.1 Machine Learning
3.1.1.1 Deep Learning
3.1.1.2 Supervised vs. Unsupervised Learning
3.1.1.3 Reinforcement Learning
3.1.2 Natural Language Processing
3.1.3 Computer Vision
3.1.4 Speech Recognition
3.1.5 Context Aware Processing
3.1.6 Artificial Neural Network
3.1.7 Predictive APIs
3.1.8 Autonomous Robotics
3.2 AI Technology Readiness
3.3 Machine Learning APIs
3.3.1 IBM Watson API
3.3.2 Microsoft Azure Machine Learning API
3.3.3 Google Prediction API
3.3.4 Amazon Machine Learning API
3.3.5 BigML
3.3.6 AT&T Speech API
3.3.7 Wit.ai
3.3.8 AlchemyAPI
3.3.9 Diffbot
3.3.10 PredictionIO
3.3.11 General Application Environment
3.4 AI Technology Goal
3.5 AI Tools and Approaches
3.6 Emotion AI
3.6.1 Facial Detection APIs
3.6.2 Text Recognition APIs
3.6.3 Speech Recognition APIs
3.7 IoT Application and Big Data Analytics
3.8 Data Science and Predictive Analytics
3.9 Edge Computing and 5G Network
3.10 Cloud Computing and Machine Learning
3.11 Smart Machine and Virtual Twinning
3.12 Factory Automation and Industry 4.0
3.13 Building Automation and Smart Workplace
3.14 Cloud Robotics and Public Security
3.15 Self-Driven Network and Domain Specific Network
3.16 Predictive 3D Design
4.0 Market Solutions and Applications Analysis
4.1 AI Market Landscape
4.1.1 Embedded Device and Things
4.1.2 AI Software and Platform
4.1.3 AI Component and Chipsets
4.1.4 AI Service and Deployment
4.2 AI Application Delivery Platform
4.3 AIaaS and MLaaS
4.4 Enterprise Adoption and External Investment
4.5 Enterprise AI Drive Productivity Gains
4.6 AI Patent and Regulatory Framework
4.7 Value Chain Analysis
4.7.1 Artificial Intelligence Companies
4.7.2 IoT Companies and Suppliers
4.7.3 Data Analytics Providers
4.7.4 Connectivity Infrastructure Providers
4.7.5 Components and Chipsets Manufacturers
4.7.6 Software Developers and Data Scientists
4.7.7 End Users
4.7.8 End User Industry and Application
4.8 AI Use Case Analysis
4.9 Competitive Landscape Analysis
5.0 Company Analysis
5.1 NVIDIA Corporation
5.2 IBM Corporation
5.3 Intel Corporation
5.4 Samsung Electronics Co Ltd.
5.5 Microsoft Corporation
5.6 Google Inc.
5.7 Baidu Inc.
5.8 Qualcomm Incorporated
5.9 Huawei Technologies Co. Ltd.
5.10 Fujitsu Ltd.
5.11 H2O.ai
5.12 Juniper Networks, Inc.
5.13 Nokia Corporation
5.14 ARM Limited
5.15 Hewlett Packard Enterprise (HPE)
5.16 Oracle Corporation
5.17 SAP
5.18 Siemens AG
5.19 Apple Inc.
5.20 General Electric (GE)
5.21 ABB Ltd.
5.22 LG Electronics
5.23 Koninklijke Philips N.V
5.24 Whirlpool Corporation
5.25 AB Electrolux
5.26 Wind River Systems Inc.
5.27 Cumulocity GmBH
5.28 Digital Reasoning Systems Inc.
5.29 SparkCognition Inc.
5.30 KUKA AG
5.31 Rethink Robotics
5.32 Motion Controls Robotics Inc.
5.33 Panasonic Corporation
5.34 Haier Group Corporation
5.35 Miele
5.36 Next IT Corporation
5.37 Nuance Communications Inc.
5.38 InteliWISE
5.39 Facebook Inc.
5.40 Salesforce
5.41 Amazon Inc.
5.42 SK Telecom
5.43 motion.ai
5.44 Buddy
5.45 AOL Inc.
5.46 Tesla Inc.
5.47 Inbenta Technologies Inc.
5.48 Cisco Systems
5.49 MAANA
5.50 Veros Systems Inc.
5.51 PointGrab Ltd.
5.52 Tellmeplus
5.53 Xiaomi Technology Co. Ltd.
5.54 Leap Motion Inc.
5.55 Atmel Corporation
5.56 Texas Instruments Inc.
5.57 Advanced Micro Devices (AMD) Inc.
5.58 XILINX Inc.
5.59 Omron Adept Technology
5.60 Gemalto N.V.
5.61 Micron Technology
5.62 SAS Institute Inc.
5.63 AIBrian Inc.
5.64 QlikTech International AB
5.65 MicroStrategy Incorporated
5.66 Brighterion Inc.
5.67 IPsoft Inc.
5.68 24/7.ai Inc.
5.69 General Vision Inc.
5.70 Sentient Technologies Holdings Limited
5.71 Graphcore
5.72 CloudMinds
5.73 Rockwell Automation Inc.
5.74 Tend.ai
5.75 SoftBank Robotics Holding Corp.
5.76 iRobot Corp.
5.77 Lockheed Martin
5.78 Spacex
5.79 Fraight AI
5.80 Infor Global Solutions
5.81 Presenso
5.82 Teknowlogi
6.0 AI Market Analysis and Forecasts 2019 – 2024
6.1 AI Market
6.2 AI Market by Segment
6.2.1 Hardware
6.2.1.1 Embedded Device
6.2.1.1.1 Non-IoT Device
6.2.1.1.2 IoT Device
6.2.1.1.2.1 Wearable Devices
6.2.1.1.2.2 Medical and Healthcare Devices
6.2.1.1.2.3 Smart Appliances
6.2.1.1.2.4 Industrial Machines
6.2.1.1.2.5 Robots and Drone
6.2.1.1.2.6 Service Robots
6.2.1.1.2.7 Entertainment Devices
6.2.1.1.2.8 Security Devices
6.2.1.1.2.9 Networking Device
6.2.1.1.2.10 In-Vehicle IoT Device
6.2.1.1.2.11 Smart Grid Device
6.2.1.1.2.12 Military Device
6.2.1.1.2.13 Energy Management Device
6.2.1.1.2.14 Agriculture Specific Device
6.2.1.2 Embedded IoT System
6.2.1.3 Semiconductor Components
6.2.1.3.1 Wearable and Embedded Components
6.2.1.3.1.1 Real Time Location System (RTLS)
6.2.1.3.1.2 Barcode
6.2.1.3.1.3 Barcode Scanner
6.2.1.3.1.4 Barcode Scanner Technology Levels
6.2.1.3.1.5 Barcode Stickers
6.2.1.3.1.6 RFID
6.2.1.3.1.7 RFID Tags
6.2.1.3.1.8 Sensor
6.2.1.3.2 Processors
6.2.2 Software
6.2.2.1 Software Category
6.2.2.1.1 AI Platform
6.2.3 Services
6.2.3.1 Professional Services
6.3 AI Market by Management Functions
6.4 AI Market by Technology
6.4.1 Machine Learning
6.5 AI Market by Industry Vertical
6.5.1 Medical and Healthcare
6.5.2 Manufacturing
6.5.3 Consumer Electronics
6.5.4 Automotive and Transportation
6.5.5 Retail and Apparel
6.5.6 Marketing and Advertising
6.5.7 FinTech
6.5.8 Building and Construction
6.5.9 Agriculture
6.5.10 Security and Surveillance
6.5.11 Government, Military, and Aerospace
6.5.12 Human Resource
6.5.13 Legal and Law
6.5.14 Telecommunication and IT
6.5.15 Oil, Gas, and Mining
6.5.16 Logistics
6.5.17 Education and Learning
6.6 AI Market by Solution
6.7 AI Market by Deployment
6.7.1 Cloud Deployment
6.8 AI Market by AI System
6.9 AI Market by AI Type
6.10 AI Market by Connectivity
6.10.1 Non-Telecom Connectivity
6.10.2 Telecom Connectivity
6.10.3 Connectivity Standard
6.10.4 Enterprise
6.11 AI Market by IoT Network
6.12 AI Market by IoT Edge Network
6.13 AI Analytics Market
6.14 AI Market by Intent Based Networking
6.15 AI Market by Virtualization
6.16 AI Market by 5G Network
6.17 AI Market by Blockchain Network
6.18 AI Market by Region
6.18.1 North America
6.18.2 Asia Pacific
6.18.2.1 China
6.18.2.2 South Korea
6.18.2.3 Taiwan
6.18.2.4 Rest of Asia
6.18.3 Europe
6.18.4 Middle East and Africa
6.18.5 Latin America
6.19 AI Embedded Unit Deployment Forecast
6.19.1 Unit Deployment by Solution
6.19.1.1 Non-IoT Device
6.19.1.2 IoT Device
6.19.1.3 IoT Things and Objects
6.19.1.4 IoT Semiconductor
6.19.1.5 Software
6.19.2 Unit Deployment by Region
6.19.2.1 North America
6.19.2.2 Asia Pacific
6.19.2.3 Europe
6.19.2.4 Middle East and Africa
6.19.2.5 Latin America
7.0 Conclusions and Recommendations
7.1 Advertisers and Media Companies
7.2 Artificial Intelligence Providers
7.3 Automotive Companies
7.4 Broadband Infrastructure Providers
7.5 Communication Service Providers
7.6 Computing Companies
7.7 Data Analytics Providers
7.8 Immersive Technology (AR, VR, and MR) Providers
7.9 Networking Equipment Providers
7.10 Networking Security Providers
7.11 Semiconductor Companies
7.12 IoT Suppliers and Service Providers
7.13 Software Providers
7.14 Smart City System Integrators
7.15 Automation System Providers
7.16 Social Media Companies
7.17 Workplace Solution Providers
7.18 Large Businesses and SMBs



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