ビッグデータとIoTにおける人工知能(AI)および機械学習:データ収集、分析、意思決定市場

◆英語タイトル:Artificial Intelligence and Machine Learning in Big Data and IoT: The Market for Data Capture, Analytics, and Decision Making 2016 - 2021
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【レポートの概要】

More than 50% of enterprise IT organizations are experimenting with Artificial Intelligence (AI) in various forms such as Machine Learning, Deep Learning, Computer Vision, Image Recognition, Voice Recognition, Artificial Neural Networks, and more. AI is not a single technology but a convergence of various technologies, statistical models, algorithms, and approaches. Machine Learning is a sub-field of computer science that evolved from the study of pattern recognition and computational learning theory in AI.
Every large corporation collects and maintains a huge amount of human-oriented data associated with its customers including their preferences, purchases, habits, and other personal information. As the Internet of Things (IoT) progresses, there will an increasingly large amount of unstructured machine data. The growing amount of human-oriented and machine generated data will drive substantial opportunities for AI and Machine Learning support for unstructured data analytics solutions.

This research evaluates various AI technologies and their use relative to analytics solutions within the rapidly growing enterprise data arena. The report assesses emerging business models, leading companies, and solutions. The report also provides forecasting for unit growth and revenue from 2016 – 2021 associated with AI supported predictive analytics solutions. All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you’re addressing. This needs to be used within three months of purchasing the report.

【レポートの目次】

1 Introduction
1.1 Executive Summary
1.2 Research Objectives
1.3 Key Findings
1.4 Target Audience
1.5 Companies in Report
2 Artificial Intelligence Technology and Market
2.1 Artificial Intelligence and Machine Learning
2.2 AI Types
2.3 Use of AI and ML in Enterprise
2.4 Artificial Intelligence Technology
2.4.1 Machine Learning
2.4.2 Natural Language Processing
2.4.3 Image Processing
2.4.4 Voice Recognition
2.4.5 Artificial Neural Network
2.4.6 Deep Learning
2.4.7 Others
2.5 AI and ML Technology Goals
2.5.1 Reasoning
2.5.2 Knowledge Representation
2.5.3 Planning
2.5.4 Learning
2.5.5 Communication
2.5.6 Machine Perception
2.5.7 Motion Manipulation
2.5.8 Social Intelligence
2.5.9 Creativity
2.5.10 Artificial General Intelligence
2.5.11 Computer Vision
2.5.12 Robotics
2.6 AI Approaches
2.6.1 Cybernetics and Brian Simulation
2.6.2 Symbolic
2.6.3 Sub-Symbolic
2.6.4 Statistical
2.6.5 Integration
2.7 AI Tools
2.7.1 Search and Optimization
2.7.2 Logic
2.7.3 Probability
2.7.4 Classifier and Statistics
2.7.5 Neural Network
2.7.6 Deep Feedforward Neural Network
2.7.7 Deep Recurrent Neural Network
2.7.8 Control Theory
2.7.9 Language
2.8 AI Outcomes
2.9 Neural Networks and Artificial Intelligence
2.10 Deep Learning and Artificial Intelligence
2.11 Predictive Analytics and Artificial Intelligence
2.12 Internet of Things and Big Data Analytics
2.13 IoT and Artificial Intelligence
2.14 Consumer IoT, Big Data Analytics, and Artificial Intelligence
2.15 Industrial IoT, Big Data Analytics, and Machine Learning
2.16 Artificial Intelligence and Cognitive Computing
2.17 Transhumanism and Artificial Intelligence
3 Artificial Intelligence and Machine Learning in Big Data and IoT
3.1 Machine Learning Everywhere
3.1.1 Machine Learning as Open Source Technology
3.1.2 Machine Learning and Intelligent Discovery in IoT
3.1.3 Supervised and Unsupervised Machine Learning
3.1.4 Machine Learning as Big Data Analysis Technique
3.1.5 Machine Learning AI Robots
3.1.6 Machine Learning and Data Democratization
3.2 Machine Learning APIs and Big Data Development
3.2.1 Phases of Machine Learning APIs
3.2.2 Machine Learning API Challenges
3.2.3 Top Machine Learning APIs
3.2.3.1 IBM Watson API
3.2.3.2 Microsoft Azure Machine Learning API
3.2.3.3 Google Prediction API
3.2.3.4 Amazon Machine Learning API
3.2.3.5 BigML
3.2.3.6 AT&T Speech API
3.2.3.7 Wit.ai
3.2.3.8 AlchemyAPI
3.2.3.9 Diffbot
3.2.3.10 PredictionIO
3.2.4 Machine Learning API in General Application Environment
3.3 Ultra-Scale Analytics and Artificial Intelligence
3.4 Rise of Algorithmic Business
3.5 Cloud Hosted Machine Intelligence
3.6 Contradiction of Machine Learning
3.7 Value Chain Analysis
3.7.1 AI and Machine Learning Companies
3.7.2 IoT Companies
3.7.3 Big Data Analytics Providers
3.7.4 Connectivity Solution and Infrastructure Providers
3.7.5 Hardware and Equipment Manufacturers
3.7.6 Developers and Data Scientists
3.7.7 End Users
4 Artificial Intelligence and Machine Leaning Applications and Services
4.1 Intelligence Performance Monitoring
4.2 Infrastructure Monitoring
4.3 Generating Accurate Models
4.4 Recommendation Engine
4.5 Block Chain and Crypto Technologies
4.6 Enterprise Applications
4.7 Contextual Awareness
4.8 Customer Feedback
4.9 Self-Driving Cars
4.10 Fraud Detection Systems
4.11 Personalized Medicine and Healthcare Service
4.12 Predictive Data Modelling
4.13 Smart Machines
4.14 Cybersecurity Solutions
4.15 Autonomous Agents
4.16 Intelligent Assistant
4.17 Intelligent Decision Support Systems
4.18 Risk Management
4.19 Data Mining and Management
4.20 Intelligent Robotics
4.21 Financial Technology
4.22 Machine Intelligence
5 AI Powered Predictive Analytics Market Outlook and Forecasts
5.1 Global Market Forecast
5.1.1 Global Market Revenue 2016 – 2021
5.1.1.1 Market by Type 2016 – 2021
5.1.1.2 Market by Business Application 2016 – 2021
5.1.1.3 Market by Core Technology 2016 – 2021
5.1.1.4 Market by Technology Application 2016 – 2021
5.1.1.5 Market by Segment 2016 – 2021
5.1.1.6 Market by Industry Vertical 2016 – 2021
5.1.2 Productivity in Industry Vertical 2016 – 2021
5.1.3 System and Hardware Market 2016 – 2021
5.1.4 Cognitive Computing Market 2016 – 2021
5.1.5 Business Content Creation
5.1.6 Economic Transactions
5.1.7 Robo-Boss and Worker Supervision
5.1.8 Building Security System
5.1.9 Business Analytics Software
5.1.10 Smart Machine and Employment
5.1.11 Self-Service Visual Discovery and Data Penetration Tools
5.2 Regional Market Forecasts
5.2.1 Revenue by Region 2016 – 2021
5.2.2 North America Market Forecasts 2016 – 2021
5.2.2.1 Market by Types
5.2.2.2 Market by Business Application
5.2.2.3 Market by Core Technology
5.2.2.4 Market by Technology Application
5.2.2.5 Market by Segment
5.2.2.6 Market by Industry Verticals
5.2.3 Europe Market Forecasts 2016 – 2021
5.2.3.1 Market by Types
5.2.3.2 Market by Business Application
5.2.3.3 Market by Core Technology
5.2.3.4 Market by Technology Application
5.2.3.5 Market by Segments
5.2.3.6 Market by Industry Verticals
5.2.4 APAC Market Forecasts 2016 – 2021
5.2.4.1 Market by Type
5.2.4.2 Market by Business Application
5.2.4.3 Market by Core Technology
5.2.4.4 Market by Technology Application
5.2.4.5 Market by Segments
5.2.4.6 Market by Industry Vertical
5.2.5 ME&A Market Forecasts 2016 – 2021
5.2.5.1 Market by Type
5.2.5.2 Market by Business Application
5.2.5.3 Market by Core Technology
5.2.5.4 Market by Technology Application
5.2.5.5 Market by Segment
5.2.5.6 Market by Industry Vertical
5.2.6 Latin America Market Forecasts 2016 – 2021
5.2.6.1 Market by Type
5.2.6.2 Market by Business Application
5.2.6.3 Market by Core Technology
5.2.6.4 Market by Technology Application
5.2.6.5 Market by Segment
5.2.6.6 Market by Industry Vertical
6 AI Supported Connected Device Deployment Forecasts
6.1 Global Deployment Forecast 2016 – 2021
6.1.1 Deployment by Device and Platform
6.1.2 Deployment by Application Sector
6.1.3 Deployment by Core Technology
6.1.4 Deployment by Technology Applications
6.1.5 Deployment by Segments
6.1.6 Deployment by Industry Verticals
6.2 Regional Deployment Forecasts 2016 – 2021
6.2.1 Deployment by Region
6.2.2 North America Deployment Forecasts 2016 – 2021
6.2.2.1 Deployment by Device and Platform
6.2.2.2 Deployment by Application Sector
6.2.2.3 Deployment by Core Technology
6.2.2.4 Deployment by Technology Application
6.2.2.5 Deployment by Segment
6.2.2.6 Deployment by Industry Verticals
6.2.3 Europe Deployment Forecasts 2016 – 2021
6.2.3.1 Deployment by Device and Platform
6.2.3.2 Deployment by Application Sector
6.2.3.3 Deployment by Core Technology
6.2.3.4 Deployment by Technology Applications
6.2.3.5 Deployment by Segment
6.2.3.6 Deployment by Industry Vertical
6.2.4 APAC Deployment Forecasts 2016 – 2021
6.2.4.1 Deployment by Device and Platform
6.2.4.2 Deployment by Application Sector
6.2.4.3 Deployment by Core Technology
6.2.4.4 Deployment by Technology Application
6.2.4.5 Deployment by Segment
6.2.4.6 Deployment by Industry Vertical
6.2.5 ME&A Deployment Forecasts 2016 – 2021
6.2.5.1 Deployment by Device and Platform
6.2.5.2 Deployment by Application Sector
6.2.5.3 Deployment by Core Technology
6.2.5.4 Deployment by Technology Application
6.2.5.5 Deployment by Segment
6.2.5.6 Deployment by Industry Vertical
6.2.6 Latin America Deployment Forecasts 2016 – 2021
6.2.6.1 Deployment by Device and Platform
6.2.6.2 Deployment by Application Sector
6.2.6.3 Deployment by Core Technology
6.2.6.4 Deployment by Technology Application
6.2.6.5 Deployment by Segment
6.2.6.6 Deployment by Industry Vertical
7 Company Analysis
7.1 AI Initiatives and Acquisition Strategies
7.1.1 Google
7.1.2 Twitter
7.1.3 Microsoft
7.1.4 IBM
7.1.5 Apple
7.1.6 Facebook
7.1.7 Amazon
7.1.8 Skype
7.1.9 Salesforce
7.1.10 Intel
7.1.11 Yahoo
7.1.12 AOL
7.1.13 NVIDIA
7.1.14 x.ai
7.1.15 Tesla
7.1.16 Baidu
7.1.17 H2O.ai
7.1.18 SparkCognition
7.1.19 OpenAI
7.1.20 Inbenta
7.2 Big Data, Analytics, and IoT Companies and Solutions
7.2.1 Tachyus
7.2.2 Sentrian
7.2.3 Maana
7.2.4 Veros Systems
7.2.5 Neura
7.2.6 Augury Systems
7.2.7 Glassbeam
7.2.8 Comfy
7.2.9 mnubo
7.2.10 C-B4
7.2.11 PointGrab
7.2.12 Tellmeplus
7.2.13 Moov
7.2.14 Sentenai
7.2.15 Imagimob
7.2.16 FocusMotion
7.2.17 MoBagel
8 Conclusions and Recommendations
8.1 Recommendations for Data Analytics Providers
8.2 Recommendations for AI and Machine Learning Companies
8.3 Recommendations for IoT Companies and Equipment Manufacturers
8.4 Recommendations for Service Providers
8.5 Recommendations for Enterprise

Figures

Figure 1: Artificial Intelligence Technology
Figure 2: Sentiment Analysis with Deep Machine Learning
Figure 3: Artificial Intelligence (AI) and Predictive Layer System
Figure 4: Industrial IoT Landscape and Machine Learning as a Service (MLaaS)
Figure 5: Machine Learning Use Case Scenario
Figure 6: Artificial Intelligence and Machine Learning Landscape and Impact
Figure 7: Global AI Powered Predictive Analytics Market 2016 – 2021
Figure 8: AI Powered Analytics Driven Productivity Gains in Industry Verticals 2016 – 2021
Figure 9: AI Driven System and Hardware Market 2016 – 2021
Figure 10: AI Driven Cognitive Computing Market 2016 – 2021
Figure 11: Business Content Created by AI Powered Smart Machines 2018 – 2021
Figure 12: Worker Supervision by AI Powered Robo-Boss 2018 – 2021
Figure 13: Building Security System by AI Capabilities 2018 – 2021
Figure 14: Business Analytics Software by AI Powered Predictive Analytics 2018 – 2021
Figure 15: AI powered Smart Machines vs. Humans 2018 – 2021
Figure 16: Global AI Connected Devices Deployment 2016 – 2021

Tables

Table 1: Global AI Powered Predictive Analytics Market by Type 2016 – 2021
Table 2: Global AI Powered Predictive Analytics Market by Business Application 2016 – 2021
Table 3: Global AI Powered Predictive Analytics Market by Core Technology 2016 – 2021
Table 4: Global AI Powered Predictive Analytics Market by Technology Applications 2016 – 2021
Table 5: Global AI Powered Predictive Analytics Market by Segment 2016 – 2021
Table 6: Global AI Powered Predictive Analytics Market by Industry Verticals 2016 – 2021
Table 7: Global Economic Transaction by AI Powered Autonomous Software Agents 2018 – 2021
Table 8: AI Self Service Visual Discovery and Data Penetration Tools 2018 – 2021
Table 9: AI Powered Predictive Analytics Market by Region 2016 – 2021
Table 10: North America AI Powered Predictive Analytics Market by Type 2016 – 2021
Table 11: North America AI Powered Predictive Analytics Market by Business Application 2016 – 2021
Table 12: North America AI Powered Predictive Analytics Market by Core Technology 2016 – 2021
Table 13: North America AI Powered Predictive Analytics Market by Technology App 2016 – 2021
Table 14: North America AI Powered Smart & Predictive Analytics Market by Segment 2016 – 2021
Table 15: North America AI Powered Predictive Analytics Market by Industry Vertical 2016 – 2021
Table 16: Europe AI Powered Predictive Analytics Market by Type 2016 – 2021
Table 17: Europe AI Powered Predictive Analytics Market by Business Application 2016 – 2021
Table 18: Europe AI Powered Predictive Analytics Market by Core Technology 2016 – 2021
Table 19: Europe AI Powered Predictive Analytics Market by Technology Application 2016 – 2021
Table 20: Europe AI Powered Predictive Analytics Market by Segment 2016 – 2021
Table 21: Europe AI Powered Predictive Analytics Market by Industry Vertical 2016 – 2021
Table 22: APAC AI Powered Predictive Analytics Market by Type 2016 – 2021
Table 23: APAC AI Powered Predictive Analytics Market by Business Application 2016 – 2021
Table 24: APAC AI Powered Predictive Analytics Market by Core Technology 2016 – 2021
Table 25: APAC AI Powered Predictive Analytics Market by Technology Applications 2016 – 2021
Table 26: APAC AI Powered Predictive Analytics Market by Segment 2016 – 2021
Table 27: APAC AI Powered Predictive Analytics Market by Industry Vertical 2016 – 2021
Table 28: ME&A AI Powered Predictive Analytics Market by Type 2016 – 2021
Table 29: ME&A AI Powered Predictive Analytics Market by Business Application 2016 – 2021
Table 30: ME&A AI Powered Predictive Analytics Market by Core Technology 2016 – 2021
Table 31: ME&A AI Powered Predictive Analytics Market by Technology Application 2016 – 2021
Table 32: ME&A AI Powered Predictive Analytics Market by Segment 2016 – 2021
Table 33: ME&A AI Powered Predictive Analytics Market by Industry Vertical 2016 – 2021
Table 34: Latin America AI Powered Predictive Analytics Market by Type 2016 – 2021
Table 35: Latin America AI Powered Predictive Analytics Market by Business Application 2016 – 2021
Table 36: Latin America AI Powered Predictive Analytics Market by Core Technology 2016 – 2021
Table 37: Latin America AI Powered Predictive Analytics Market by Technology App 2016 – 2021
Table 38: Latin America AI Powered Predictive Analytics Market by Segment 2016 – 2021
Table 39: Latin America AI Powered Predictive Analytics Market by Industry Vertical 2016 – 2021
Table 40: Global Device Deployment by Device Type and Platform 2016 – 2021
Table 41: Global Device Deployment by Application Sector 2016 – 2021
Table 42: Global Device Deployment by Core Technology 2016 – 2021
Table 43: Global Device Deployment by Technology Application 2016 – 2021
Table 44: Global Device Deployment by Segment 2016 – 2021
Table 45: Global Device Deployment by Industry Vertical 2016 – 2021
Table 46: AI Connected Device Deployment by Region 2016 – 2021
Table 47: North America Device Deployment by Device Type and Platform 2016 – 2021
Table 48: North America Device Deployment by Application Sector 2016 – 2021
Table 49: North America Device Deployment by Core Technology 2016 – 2021
Table 50: North America Device Deployment by Technology Application 2016 – 2021
Table 51: North America Device Deployment by Segment 2016 – 2021
Table 52: North America Device Deployment by Industry Vertical 2016 - 2021
Table 53: Europe Device Deployment by Device Type and Platform 2016 – 2021
Table 54: Europe AI Device Deployment by Application Sector 2016 – 2021
Table 55: Europe Device Deployment by Core Technology 2016 – 2021
Table 56: Europe Device Deployment by Technology Application 2016 – 2021
Table 57: Europe Device Deployment by Segment 2016 – 2021
Table 58: Europe Device Deployment by Industry Vertical 2016 – 2021
Table 59: APAC AI Device Deployment by Device Type and Platform 2016 – 2021
Table 60: APAC Device Deployment by Application Sector 2016 – 2021
Table 61: APAC Device Deployment by Core Technology 2016 – 2021
Table 62: APAC Device Deployment by Technology Application 2016 – 2021
Table 63: APAC Device Deployment by Segment 2016 – 2021
Table 64: APAC Device Deployment by Industry Vertical 2016 – 2021
Table 65: ME&A Device Deployment by Device Type and Platform 2016 – 2021
Table 66: ME&A Device Deployment by Application Sector 2016 – 2021
Table 67: ME&A Device Deployment by Core Technology 2016 – 2021
Table 68: ME&A Device Deployment by Technology Application 2016 – 2021
Table 69: ME&A Device Deployment by Segment 2016 – 2021
Table 70: ME&A Device Deployment by Industry Vertical 2016 – 2021
Table 71: Latin America Device Deployment by Device Type and Platform 2016 – 2021
Table 72: Latin America Devices Deployment by Application Sector 2016 – 2021
Table 73: Latin America Device Deployment by Application Sector 2016 – 2021
Table 74: Latin America Device Deployment by Technology Application 2016 – 2021
Table 75: Latin America Device Deployment by Segment 2016 – 2021
Table 76: Latin America Device Deployment by Industry Vertical 2016 – 2021

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