The Impact of Big Data on the Pay-TV Industry, 2018: Data Trends & Opportunities

DUBLIN, Sept. 28, 2018 /PRNewswire/ —

The “TV Services: Pay TV in a Data-Driven World” report has been added to’s offering.

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Pay-TV providers are increasingly facing online challengers that have extensive expertise in using data to define and drive their businesses as well as user experiences.

Big data is the new field for competition, and developing more strategic methods to leverage collected data to improve services and revenues is critical for the pay-TV industry.

This report focuses on the impact of big data on the pay-TV industry, both today and in the future, including profiles of major players.

Key Topics Covered

1. Report Summary
1.1 Purpose of Report
1.2 Key Burning Questions Addressed by This Research
1.3 Research Approach/Sources

2. The State of Pay TV

3. Pay TV and Data Use
3.1 Comparing Traditional and New Generation Use of Data
3.2 Regulation

4. The Value of Data in Pay TV
4.1 Types of Data
4.2 Quantifying Data’s Value
4.2.1 Utility
4.2.2 Cost
4.2.3 Impact

5. Consumer Attitudes about Data Use

6. Data Trends and Opportunities in Pay TV
6.1 Advertising
6.2 Content-Related Decisions
6.3 User Experience and Feature Design
6.4 Use of Artificial Intelligence/Machine Learning

7. Global Forecast of Pay-TV Subscriptions

8. Implications
8.1 Pay-TV Providers
8.2 Cable Networks/Content Producers
8.3 Technology Vendors

Companies Featured

  • 605
  • Accedo
  • Accenture
  • Amino
  • AT&T
  • Brightcove
  • Cisco
  • Cogeco
  • Comcast
  • Dativa
  • Equifax
  • Ericsson
  • Gracenote
  • IBM
  • Irdeto
  • JumpTV
  • LiveRamp
  • Kaltura
  • MobiTV
  • NFL
  • NTCA
  • Ooyala
  • Plex
  • Roku
  • Samsung
  • Sling TV
  • Tegna
  • TiVo
  • Verimatrix
  • Verizon
  • Vewd
  • Viacom
  • Warner Bros
  • Wicket Labs
  • and more…

For more information about this report visit

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BootstrapLabs Announces Fourth Annual Artificial Intelligence Conference

SAN FRANCISCO, Sept. 27, 2018 /PRNewswire/ — BootstrapLabs, a leading venture capital firm focusing on Applied AI and based in Silicon Valley, announced today the 4th annual Applied Artificial Intelligence Conference will be held in San Francisco on April 18, 2019. 

The BootstrapLabs Applied Artificial Intelligence Conference (#AAI19) has grown to become one of the top AI events in the U.S. Mentioned in publications such as Forbes, TechCrunch and Fortune, and selected by Business Insider as one of the top 20 AI conferences to attend, the exclusive conference has brought together over 2,000 professionals and is considered by many AI leaders to be the best forum to learn, network and discover the latest Applied AI technologies.

The one-day conference will focus on the latest and future impacts of AI applications across a breadth of sectors including Transportation, Logistics, Healthcare, Energy, FinTech, the Future of Work, IoT and Cybersecurity.

The conference will take place in downtown San Francisco and will feature keynotes from Artificial Intelligence leaders who will share practical wisdom and methodologies on how to take advantage of AI’s powerful potential. Past speakers include world-class technology leaders such as:

  • Paul Daugherty, Chief Technology & Innovation Officer, Accenture
  • Steve Carlin, Chief Strategy Officer, SoftBank Robotics America, 
  • Richard Socher, Chief Scientist, Salesforce
  • Kay Firth-Butterfield, Head of AI and Machine Learning, World Economic Forum
  • Karen Kerr, Executive Managing Director, GE Ventures
  • Sangeeta Chakraborty, Chief Customer Officer, Ayasdi

Many CTOs, CIOs and AI/ML experts from top tech companies like Facebook, Amazon, Uber, MasterCard, Unity, Airbnb, Linkedin, Intel, Samsung, Tesla, JP Morgan, Comcast, Microsoft, IBM, Walmart and many others, including top AI founders and government officials, have been participating during past conference editions.

“As Paul Daugherty, CTO at Accenture, stated this year during the conference ‘AI is the alpha trend.’ I think that he is right on the money and that AI might be the most disruptive technology humanity has created. At BootstrapLabs, we are fully focused on investing in the most talented entrepreneurs solving some of the world’s biggest problems by applying AI,” said Nicolai Wadstrom, founder and CEO, BootstrapLabs.

“AI is rapidly approaching human performance in basic comprehension and composition, which will greatly impact people, corporations and governments. Leaders around the world need to get involved now and join the conversation on Applied AI,” said Ben Levy, co-founder at BootstrapLabs. 

Contact for Media: 
BootstrapLabs Press

More about the event can be found at the BootstrapLabs event webpage. 

Related Links:

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BootstrapLabs Twitter

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Global Artificial Intelligence in IoT Markets 2018-2023: Convergence of AI, 5G, Blockchain, and Edge Computing with IoT Facilitates a Multi-Billion Dollar Market

DUBLIN, Sept. 28, 2018 /PRNewswire/ —

The “Artificial Intelligence in IoT: AIoT Technology, Platforms, Applications and Services by Industry Vertical 2018 – 2023” report has been added to’s offering.

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Artificial Intelligence (AI) is rapidly making its way into many advanced solutions including autonomous vehicles, smart bots, advanced predictive analytics, and more. Many industry verticals will be transformed through AI integration with enterprise, industrial, and consumer product and service ecosystems. It is destined to become an integral component of business operations including supply chains, sales and marketing processes, product and service delivery and support models. AIoT (AI support of IoT) is just beginning to become part of the ICT lexicon as the possibilities for the former adding value to the latter are only limited by the imagination.

AI enhances the ability for Big Data Analytics and IoT platforms to provide value to each of these market segments. The use of AI for decision making in IoT and data analytics will be crucial for efficient and effective decision making, especially in the area of streaming data and real-time analytics associated with edge computing networks. Real-time data will be a key value proposition for all use cases, segments, and solutions. 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 many cases, the data itself, and actionable information will be the service.

This research provides a multi-dimensional view into the AI market including analysis of embedded devices and components, embedded software, and AI platforms. This includes an assessment of the combined AI marketplace with analysis of embedded IoT and non-IoT devices, embedded components (including AI chipsets), embedded software and AI platforms, and related services. It also evaluates leading solution providers including hardware, software, integrated platforms, and services. It also evaluates the market for AI in IoT networks and systems.

This research also assesses the impact of AI in various networking products and solutions including embedded equipment, components, and software platforms (network automation, optimization, and transformation). The report also evaluates the role of SDN, Edge Computing, NFV, and Augmented Intelligence in the formation and support of AI driven networking ecosystems. In addition, the impact of 5G networks, IoT technology and systems, and network analytics functions is also evaluated.

Target Audience:

  • AI companies
  • IoT companies
  • Robotics companies
  • Semiconductor vendors
  • Data management vendors
  • Industrial automation companies
  • Governments and R&D organizations
  • Enterprises across all industry verticals

Select Research Findings:

  • Global AI Chipsets market will reach $6.6B USD by 2023
  • The APAC region will lead the IoT technology market through 2023
  • The combined global IoT technology market will reach $869.9B USD by 2023
  • Global AI in embedded IoT devices market will approach $26.2B USD by 2023
  • Total AI driven networking solution market is expected to reach $5.8 billion by 2023
  • Over 50% of the enterprise organizations will leverage AI technology for networking by 2023
  • Over 87 billion semiconductors and embedded devices will be shipped in support of IoT by 2023
  • The convergence of AI, 5G, Blockchain, and Edge Computing with IoT facilitates a multi-billion dollar market

Research Benefits:

  • Identify AI market trends, challenges, and opportunities
  • Identify highest potential AI technology area opportunities
  • Identify leading AI hardware, software, and service providers
  • Learn the optimal use of AI for smart predictive analytics in IoT data
  • Understand the AI in Big Data, Analytics, and IoT ecosystem and value chain
  • Identify opportunities for AI in Analytics for IoT and other unstructured data
  • Understand IoT technology convergence with AI, Edge Computing, 5G, and Blockchain
  • Identify market opportunities globally, regionally, and by industry vertical for IoT technology
  • Know the full stack AI vendor landscape including AI core technology and supporting technology
  • Understand the relationship between 5G, AI, Big Data, Edge Computing, IoT, Smart Machines, Robotics

Key Topics Covered:

Artificial Intelligence Market by Platforms, Components, Deployment Mode, Applications, and Industry Verticals

1 Introduction
1.1 Executive Summary
1.2 Research Objectives
1.3 Select Findings
1.4 Target Audience
1.5 Companies in the Report

2 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 Technology and Impact Analysis
3.1 AI Technology Matrix
3.2 AI Technology Readiness
3.3 Machine Learning APIs
3.4 AI Technology Goal
3.5 AI Tools and Approaches
3.6 Emotion AI
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 Market and Application Analysis
4.1 AI Market Landscape
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
4.8 End User Industry and Application
4.9 AI Use Case Analysis
4.10 Competitive Landscape Analysis

5 Artificial Intelligence Market Analysis and Forecasts 2018 – 2023
5.1 Global AI Market Forecasts 2018 – 2023
5.2 Regional AI Market Forecasts 2018 – 2023

6 AI Embedded IoT Device and Things Deployment Forecasts 2018 – 2023
6.1 AI Embedded Connected IoT Device Deployment 2018 – 2023
6.2 AI Embedded Connected IoT Things and Objects Deployment 2018 – 2023

7 Company Analysis
7.1 NVIDIA Corporation
7.2 IBM Corporation
7.3 Intel Corporation
7.4 Samsung Electronics Co Ltd.
7.5 Microsoft Corporation
7.6 Google Inc.
7.7 Baidu Inc.
7.8 Qualcomm Incorporated
7.9 Huawei Technologies Co. Ltd.
7.10 Fujitsu Ltd.
7.12 Juniper Networks, Inc.
7.13 Nokia Corporation
7.14 ARM Limited
7.15 Hewlett Packard Enterprise (HPE)
7.16 Oracle Corporation
7.17 SAP
7.18 Siemens AG
7.19 Apple Inc.
7.20 General Electric (GE)
7.21 ABB Ltd.
7.22 LG Electronics
7.23 Koninklijke Philips N.V
7.24 Whirlpool Corporation
7.25 AB Electrolux
7.26 Wind River Systems Inc.
7.27 Cumulocity GmBH
7.28 Digital Reasoning Systems Inc.
7.29 SparkCognition Inc.
7.30 KUKA AG
7.31 Rethink Robotics
7.32 Motion Controls Robotics Inc.
7.33 Panasonic Corporation
7.34 Haier Group Corporation
7.35 Miele
7.36 Next IT Corporation
7.37 Nuance Communications Inc.
7.38 InteliWISE
7.39 Facebook Inc.
7.40 Salesforce
7.41 Amazon Inc.
7.42 SK Telecom
7.44 Buddy
7.45 AOL Inc.
7.46 Tesla Inc.
7.47 Inbenta Technologies Inc.
7.48 Cisco Systems
7.49 MAANA
7.50 Veros Systems Inc.
7.51 PointGrab Ltd.
7.52 Tellmeplus
7.53 Xiaomi Technology Co. Ltd.
7.54 Leap Motion Inc.
7.55 Atmel Corporation
7.56 Texas Instruments Inc.
7.57 Advanced Micro Devices (AMD) Inc.
7.58 XILINX Inc.
7.59 Omron Adept Technology
7.60 Gemalto N.V.
7.61 Micron Technology
7.62 SAS Institute Inc.
7.63 AIBrian Inc.
7.64 QlikTech International AB
7.65 MicroStrategy Incorporated
7.66 Brighterion Inc.
7.67 IPsoft Inc.
7.68 24/ Inc.
7.69 General Vision Inc.
7.70 Sentient Technologies Holdings Limited
7.71 Graphcore
7.72 CloudMinds
7.73 Rockwell Automation Inc.
7.75 SoftBank Robotics Holding Corp.
7.76 iRobot Corp.
7.77 Lockheed Martin
7.78 Spacex

8 Conclusions and Recommendations
8.1 Advertisers and Media Companies
8.2 Artificial Intelligence Providers
8.3 Automotive Companies
8.4 Broadband Infrastructure Providers
8.5 Communication Service Providers
8.6 Computing Companies
8.7 Data Analytics Providers
8.8 Equipment (AR, VR, and MR) Providers
8.9 Networking Equipment Providers
8.10 Networking Security Providers
8.11 Semiconductor Companies
8.12 IoT Suppliers and Service Providers
8.13 Software Providers
8.14 Smart City System Integrators
8.15 Automation System Providers
8.16 Social Media Companies
8.17 Workplace Solution Providers
8.18 Large Businesses and SMBs

Artificial Intelligence in Big Data Analytics and IoT: Market for Data Capture, Information and Decision Support Services

1 Introduction
1.1 Executive Summary
1.2 Research Objectives
1.3 Key Findings
1.4 Target Audience
1.5 Companies in the Report

2 Overview
2.1 Artificial Intelligence and Machine Learning
2.2 AI Types
2.3 AI and ML Language
2.4 Artificial Intelligence Technology
2.5 AI and ML Technology Goal
2.6 AI Approaches
2.7 AI Tools
2.8 AI Outcome
2.9 Neural Network 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 or H+ and Artificial Intelligence
2.18 Rise of the Analysis of Things
2.19 Supervised vs. Unsupervised Learning
2.20 AI as New form of UI

3 AI Technology in Big Data and IoT
3.1 Machine Learning Everywhere
3.2 Machine Learning APIs and Big Data Development
3.3 Enterprise Benefits of Machine Learning
3.4 Machine Learning in IoT Data
3.5 Ultra Scale Analytics and Artificial Intelligence
3.6 Rise of Algorithmic Business
3.7 Cloud Hosted Machine Intelligence
3.8 Contradiction of Machine Learning
3.9 Value Chain Analysis

4 AI Technology Application and Use Case
4.1 Intelligence Performance Monitoring
4.2 Infrastructure Monitoring
4.3 Generating Accurate Models
4.4 Recommendation Engine
4.5 Blockchain and Crypto Technologies
4.6 Enterprise Application
4.7 Contextual Awareness
4.8 Customer Feedback
4.9 Self-Driving Car
4.10 Fraud Detection System
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 System
4.18 Risk Management
4.19 Data Mining and Management
4.20 Intelligent Robotics
4.21 Financial Technology
4.22 Machine Intelligence

5 AI Technology Impact on Vertical Market
5.1 Enterprise Productivity Gain
5.2 Digital Twinning and Physical Asset Security
5.3 IT Process Efficiency Increase
5.4 AI to Replace Human Form Work
5.5 Enterprise AI Adoption Trends
5.6 Inclusion of AI as IT Requirement

6 AI Predictive Analytics in Vertical Industry

7 AI Solution in Big Data and IoT Market Forecast 2018 – 2023
7.1 Aggregated AI Solution Market 2018 – 2023
7.2 AI Solution Market by Segment 2018 – 2023
7.3 AI Embedded Solution Market 2018 – 2023
7.4 AI Predictive Analytics Market 2018 – 2023
7.5 AI Professional Service Market in Big Data and IoT 2018 – 2023

8 AI Embedded Connected IoT Device and Things 2018 – 2023
8.1 AI Embedded Connected IoT Device 2018 – 2023
8.2 AI Embedded Connected IoT Things 2018 – 2023

9 Company Analysis
9.1 Google Inc.
9.2 Twitter Inc.
9.3 Microsoft Corporation
9.4 IBM Corporation
9.5 Apple Inc.
9.6 Facebook Inc.
9.7 Inc.
9.8 Skype
9.10 Intel Corporation
9.11 Yahoo Inc.
9.12 AOL Inc.
9.13 NVIDIA Corporation
9.15 Tesla Inc.
9.16 Baidu Inc.
9.18 SparkCognition Inc.
9.19 OpenAI
9.20 Inbenta
9.21 CISCO Systems Inc.
9.22 Infineon Technologies AG
9.23 McAfee
9.24 Happiest Minds Technologies
9.25 Tachyus
9.26 Sentrian
9.27 MAANA
9.28 Veros Systems Inc.
9.29 NEURA
9.30 Augury Systems Ltd.
9.31 glassbeam
9.32 Comfy
9.33 mnubo
9.34 C-B4
9.35 PointGrab Ltd.
9.36 Tellmeplus
9.37 moov
9.38 Sentenai Inc.
9.39 imagimob
9.40 FocusMotion
9.41 MoBagel

10 Conclusions and Recommendations
10.1 AI in the Next Decade
10.2 Recommendation for Data Analytics Providers
10.3 Recommendation for AI and Machine Learning Companies
10.4 Recommendation for IoT Companies and Equipment Manufacturers
10.5 Recommendation for Service Providers
10.6 Recommendations for Enterprise

11 Appendix
11.1 AI Embedded IoT Device Sales Revenue
11.2 AI Optimized IoT Component Market
11.3 AI Optimized IoT Equipment Market
11.4 AI Optimized IoT Software Market
11.5 AI Optimized IoT Platform Market

IoT Technology by Component, Infrastructure, Software, Platform, Application, Service, and Industry Verticals

1 Introduction
1.1 Executive Summary
1.2 Research Objectives
1.3 Select Findings
1.4 Target Audience
1.5 Companies in the Report

2 Overview
2.1 Defining the Internet of Things
2.2 IoT Technology
2.3 IoT Functional Structure
2.4 IoT Network Architecture
2.5 Economic Impact Analysis
2.6 Market Factors and Challenges
2.7 Artificial Intelligence and Machine Learning
2.8 Edge Computing and Fog Computing
2.9 Digital Twin Technology
2.10 5G IoT Network
2.11 Blockchain Technology
2.12 Cloud Computing
2.13 Internet of Nanoscale Things (IoNT)

3 Technology and Value Chain Analysis
3.1 IoT Semiconductor Building Blocks
3.2 IoT Chipsets
3.3 Network Technology and Protocol
3.4 Real Time Operating System (RTOS)
3.5 IoT Software and Platform
3.6 IoT Industry Application
3.7 IoT Value Chain Analysis
3.8 IoT Investments and Market Alliances
3.9 Role of Mobile Network Operators

4 IoT Technology Market Analysis and Forecasts 2018 – 2023
4.1 Global IoT Technology Market 2018 – 2023
4.2 Global AI Equipped IoT Technology Market 2018 – 2023
4.3 Global 5G Driven IoT Technology Market 2018 – 2023
4.4 Global Edge Computing Enabled IoT Technology Market 2018 – 2023
4.5 Global Blockchain Based IoT Technology Market 2018 – 2023
4.6 Regional IoT Technology Market 2018 – 2023
4.7 IoT Semiconductor Unit Shipment Forecasts 2018 – 2023
4.8 IoT Software Unit Deployment Forecasts 2018 – 2023

5 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 Qualcomm Incorporated
5.8 Huawei Technologies Co. Ltd.
5.9 Fujitsu Ltd.
5.10 Juniper Networks, Inc.
5.11 Nokia Corporation
5.12 ARM Limited
5.13 Hewlett Packard Enterprise (HPE)
5.14 Oracle Corporation
5.15 SAP
5.16 General Electric (GE)
5.17 Wind River Systems Inc.
5.18 Cumulocity GmBH
5.19 SparkCognition Inc.
5.20 Amazon Inc. (AWS)
5.21 Cisco Systems
5.22 Atmel Corporation
5.23 Texas Instruments Inc.
5.24 Advanced Micro Devices (AMD) Inc.
5.25 XILINX Inc.
5.26 Gemalto N.V.
5.27 Micron Technology
5.28 SAS Institute Inc.
5.29 General Vision Inc.
5.30 PTC Corporation
5.31 Analog Devices Inc.
5.32 Cypress Semiconductor Corp
5.33 Rohm Semiconductor
5.34 Semtech Corporation
5.35 Enea AB
5.36 Express Logic Inc.
5.37 Kaspersky Lab
5.38 Losant IoT Inc.
5.40 Robert Bosch GmbH
5.41 Echelon Corporation
5.42 Symantec Corporation
5.43 NXP Semiconductors N.V.
5.44 STMicroelectronics
5.45 MediaTek Inc.
5.46 Microchip Technology Inc.
5.47 Renesas Electronics Corporation
5.48 Ayla Networks Inc.
5.49 Pepper
5.50 Helium Systems Inc.

6 Conclusions and Recommendations
6.1 Advertisers and Media Companies
6.2 Artificial Intelligence Providers
6.3 Automotive Companies
6.4 Broadband Infrastructure Providers
6.5 Communication Service Providers
6.6 Computing Companies
6.7 Data Analytics Providers
6.8 Equipment (AR, VR, and MR) Providers
6.9 Networking Equipment Providers
6.10 Networking Security Providers
6.11 Semiconductor Companies
6.12 IoT Suppliers and Service Providers
6.13 Software Providers
6.14 Smart City System Integrators
6.15 Automation System Providers
6.16 Social Media Companies
6.17 Workplace Solution Providers
6.18 Enterprise and Government

Next Generation Networking for Artificial Intelligence (AI): Market Outlook for AI driven SDN, 5G, IoT, and Network Analytics

1 Introduction
1.1 Unified Network, IoT, and AI
1.2 AI Driven Network
1.3 Intent Based Network
1.4 Self-driven Networks
1.5 Augmented Intelligence
1.6 AI Technology
1.7 Market Drivers and Challenges

2 Technology and Market Landscape
2.1 Networking Equipment, Platforms, and Services
2.2 Enterprise Networking
2.3 IoT Networking Technology
2.4 IoT Application
2.5 Network Optimization
2.6 Network Automation
2.7 Network Transformation
2.8 Edge Computing and AI
2.9 Software Driven Networking (SDN)
2.10 Software Defined Infrastructure (SDI)
2.11 AI-Defined Infrastructure (ADI)
2.12 Network Function Virtualization (NFV)
2.13 Telecom Infrastructure and Cloud RAN (C-RAN)
2.14 New Radio Technology and 5G Network
2.15 AI Powered Network Analytics
2.16 Competitive Landscape

3 AI driven Networking Market Analysis and Forecasts
3.1 Total AI-driven Networking Solution Market
3.2 AI driven Networking Solution Market by Segment
3.3 AI Driven Networking Solution Market by AI Technology Type
3.4 AI Driven Networking Solution Market by Deployment Type
3.5 AI Driven Networking Solution Market by Industry Sector
3.6 AI Driven Networking Solution Market by Organization Type
3.7 AI Driven Networking Solution Market by Network Type
3.8 AI Driven Networking Solution Market by Network Platform
3.9 AI Driven Networking Solution Market by IoT Application Type
3.10 AI Driven Networking Solution Market by 5G Network Type
3.11 AI Driven Networking Solution Market by Industry Vertical
3.12 AI Driven Networking Solution Market by Region

4 Company Analysis
4.1 Cisco Systems
4.2 Hewlett Packard Enterprise (HPE)
4.3 IBM Corporation
4.4 Samsung Electronics Co Ltd.
4.5 Baidu Inc.
4.6 NVIDIA Corporation
4.7 Google Inc.
4.8 Microsoft Corporation
4.9 Dell EMC
4.10 Nokia Corporation
4.11 ARM Limited
4.12 Xively
4.13 PTC Corporation
4.14 Huawei Technologies Co. Ltd.
4.15 ZTE Corporation
4.16 Intel Corporation
4.17 Ericsson AB
4.18 Fujitsu Ltd.
4.19 NEC Corporation
4.21 Qualcomm Incorporated
4.22 Juniper Networks, Inc.
4.23 Accenture PLC
4.24 Brocade Communication Systems
4.25 VMware Inc.
4.26 Aricent Inc.
4.27 Arista Networks Inc.
4.28 Extreme Networks
4.30 ECI Telecom
4.31 Foxconn Electronics Inc.
4.33 Riverbed Technology

5 Conclusions and Recommendations
5.1 Artificial Intelligence Providers
5.2 Broadband Infrastructure Providers
5.3 Communication Service Providers
5.4 Computing Companies
5.5 Data Analytics Providers
5.6 Networking Equipment Providers
5.7 Networking Security Providers
5.8 Semiconductor Companies
5.9 IoT Suppliers and Service Providers
5.10 Software and Platform Providers

For more information about this report visit

Did you know that we also offer Custom Research? Visit our Custom Research page to learn more and schedule a meeting with our Custom Research Manager.

Media Contact:

Research and Markets
Laura Wood, Senior Manager

For E.S.T Office Hours Call +1-917-300-0470
For U.S./CAN Toll Free Call +1-800-526-8630
For GMT Office Hours Call +353-1-416-8900

U.S. Fax: 646-607-1907
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The Global Machine Learning Chip Market is Expected to Grow as AI use Increases

NEW YORK, September 28, 2018 /PRNewswire/ —

According to a report published by Allied Market Research, the global machine learnings chip market was valued at USD 2.4 Billion in 2017 and is expected to reach about USD 37.8 Billion by 2025 while growing at a compound annual growth rate (CAGR) of 40.8% during the forecast periods. The increasing use of artificial intelligence (AI) and machine learning in numerous applications are one of the main factors that drive the market. Based on chip type, the market is segmented into GPU, ASIC, FPGA, CPU, and others. The ASIC segment is expected to surpass the GPU segment in future, in terms of revenue. Based on industry vertical, the market can be segmented into media & advertising, BFSI, IT & telecom, retail, healthcare, automotive & transportation, and others. Squire Mining Ltd. (OTC: SQRMF), Nvidia Corporation (NASDAQ: NVDA), Qualcomm Incorporated (NASDAQ: QCOM), Advanced Micro Devices, Inc. (NASDAQ: AMD), Micron Technology, Inc. (NASDAQ: MU)

Akshay Jadhav, Lead Analyst, Semiconductor & Electronics at AMR, said: “In 2017, the GPU segment dominated the global machine learning chip market in terms of revenue, in the chip type category. However, the others segment is expected to grow at a highest CAGR during the forecast period. Based on technology, the system-on-chip segment is anticipated to dominate the market throughout the forecast period (2018‐2025). Moreover, based on industry vertical, the BFSI segment dominates the overall machine learning chip market. The machine learning chip market signifies a promising future for the technological industry. The current business scenario has witnessed an increase in the adoption of this technology, particularly in the developing regions. The companies have been adopting innovative techniques to provide customers with advanced and innovated product offerings.”

Squire Mining Ltd. (OTCQB: SQRMF) is also listed on the Canadian Securities Exchange under the ticker (CSE: SQR). Earlier this week, the Company announced, “SQUIRE ANNOUNCES SAMSUNG ELECTRONICS AS FOUNDRY PARTNER TO MANUFACTURE ASIC CHIPS, Squire is very pleased to announce Gaonchips as our design house and Samsung Electronics as our chosen foundry partner to manufacture our ASIC chips in Korea. On August 1, 2018, we announced that Squire had engaged an undisclosed arm’s length design fabrication firm to perform the back-end design, testing and initial mass production run of our next generation ASIC chip for mining Bitcoin.  We are delighted that we are now able to disclose Gaonchips as our design house and Samsung Electronics as our foundry partner.

Our front-end development team of engineers and programmers is currently working with Gaonchips to develop the Company’s initial ASIC chip to mine Bitcoin and other associated cryptocurrencies using a wafer process technology that, once confirmed and accepted as meeting certain prescribed specifications and criteria, will form the basis of an initial mass production test run of the ASIC chip by Samsung Electronics.

In addition, once a working FPGA prototype of our initial ASIC chip is developed, we will be able to aggressively accelerate the design and development of our initial mining rig for Bitcoin and associated cryptocurrencies. We anticipate completing a FPGA prototype of our initial ASIC chip by September 30, 2018.”

Nvidia Corporation (NASDAQ: NVDA), in 1999, sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. At GTC Japan, in the heart of the robotics revolution, Nvidia Corporation recently introduced the NVIDIA DRIVE AGX Xavier Developer Kit, a platform for building autonomous driving systems. This open, scalable software and hardware solution enables companies to seamlessly develop and test customized autonomous driving technology, streamlining production. The developer kit includes a DRIVE AGX Xavier car computer, along with a vehicle harness to connect the platform to the car, international power supply, camera sensor and other accessories. NVIDIA DRIVE AGX is part of the NVIDIA AGX platform for autonomous machines, powering robots, medical devices and self-driving cars. The NVIDIA DRIVE AGX Xavier Developer Kit platform is scalable, enabling manufacturers to streamline development whether on DRIVE AGX Xavier with a single Xavier system-on-a-chip or DRIVE AGX Pegasus, which integrates dual Xavier SoCs and dual next-generation GPUs. “After several years of working on an autonomous driving computer, the DRIVE AGX Xavier Developer Kit is now available to order,” said NVIDIA founder and Chief Executive Officer Jensen Huang on stage at GTC Japan. “The development of autonomous vehicles is now turbocharged.”

Qualcomm Incorporated (NASDAQ: QCOM) invents breakthrough technologies that transform how the world connects, computes and communicates. China Mobile Research Institute, China Mobile IoT (CMIoT) Company Limited, a wholly-owned subsidiary of China Mobile, and Qualcomm Technologies, Inc., a subsidiary of Qualcomm Incorporated, recently announced new roadside units (RSUs) for 3rd Generation Partnership Project (3GPP) Release 14 LTE-V2X direct communication (PC5) based on the Qualcomm® 9150 C-V2X chipset solution. Developed by CMIoT and China Mobile Research Institute, the new RSUs will be showcased at the China Mobile booth during the WIoT 2018 expo from September 15-18th.  The cooperation between China Mobile Research Institute, CMIoT and Qualcomm Technologies, Inc. marks the extension of the three companies’ long-term, strategic relationship to the automobile and transportation sector, in which the companies are working together to explore new technologies and applications for intelligent vehicles, while driving the development and maturity of the connected vehicle industry in China.

Advanced Micro Devices, Inc. (NASDAQ: AMD), for more than 45 years, has driven innovation in high-performance computing, graphics and visualization technologies ― the building blocks for gaming, immersive platforms and the datacenter. AMD recently announced a reimagined family of AMD Athlon desktop processors with Radeon Vega graphics that have been optimized for everyday PC users: the AMD Athlon 200GE, Athlon 220GE, and Athlon 240GE processor. Combining the high-performance x86 “Zen”3 core and “Vega“3 graphics architectures in a versatile System-on-Chip (SOC) design, the Athlon desktop processors offer responsive and reliable computing for a wide range of experiences, from day-to-day needs like web browsing and video streaming through more advanced workloads like high-definition PC gaming. Complementing this news, AMD announced the availability of the commercial-grade Athlon PRO 200GE desktop processor, along with three 2nd Gen Ryzen PRO desktop processor models for the commercial, enterprise, and the public sector: the Ryzen 7 PRO 2700X, Ryzen 7 PRO 2700, and Ryzen 5 PRO 2600 processors. With these new introductions, AMD now offers a top-to-bottom line-up of professional-grade computing solutions for experiences that range from premium content creation to advanced multitasking and office productivity.

Micron Technology, Inc. (NASDAQ: MU) is a world leader in innovative memory solutions. Micron recently announced volume production on its 8Gb GDDR6 memory. Built on experience and execution for several generations of GDDR memory, GDDR6 – Micron’s fastest and most powerful graphics memory designed in Micron’s Munich Development Center – is optimized for a variety of applications that require high performance memory, including artificial intelligence (AI), networking, automotive and graphics processing units (GPUs). Additionally, Micron has worked with core ecosystem partners to ramp GDDR6 documentation and interoperability, enabling faster time to market for designs. Targeting up to 64GB/s in one package, GDDR6 brings a significant improvement over the fastest available GDDR5. This unprecedented level of single-chip performance, using proven, industry-standard BGA packaging provides designers a powerful, cost-efficient and low-risk solution using the most scalable, high-speed discrete memory available to the market. “Micron is a pioneer in developing advanced high bandwidth memory solutions and continues that leadership with GDDR6. Micron demonstrated this leadership by recently achieving throughput up to 20 Gb/s on our GDDR6 solutions,” said Andreas Schlapka, Director, Compute Networking Business Unit, Micron. “In addition to performance increases, Micron has developed a deep partner ecosystem to enable rapid creation of GDDR6 designs, enabling faster time to market for customers looking to leverage this powerful new memory technology.”

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Joe Theismann to Keynote Partner Summit at Yext’s ONWARD18 Conference

NEW YORK, Sept. 28, 2018 /PRNewswire/ — Yext, Inc. (NYSE: YEXT), the leader in Digital Knowledge Management (DKM), today announced the agenda for the ONWARD18 Partner Summit, featuring speakers from the Marketing AI Institute, Google, and Duda, and headlined by Joe Theismann, former NFL star  quarterback and Super Bowl champion with the Washington Redskins. The ONWARD18 Partner Summit will take place on Oct. 25, 2018, at JW Marriott Essex House New York.

Joe Theismann will share what we can all learn from his incredible career from being a Super Bowl-winning quarterback, to a career-ending injury, to his new start as an entrepreneur,” said Jeffrey K. Rohrs, Chief Marketing Officer of Yext. “He’s an inspiring addition to the ONWARD18 Partner Summit, and joins an all-star lineup of speakers throughout the day.”

The Partner Summit will feature a wide variety of speakers including:

  • Paul Roetzer, Founder and CEO of Marketing AI Institute, who will speak on how artificial intelligence is transforming marketing for small businesses.
  • Meagan Tanner, Head of Google My Business Strategic Partnerships, Americas, Google, who will host a fireside chat on what partners need to know about Google My Business.
  • Itai Sada, CEO, Duda, who will speak and moderate a panel discussion on the evolution of the website and how agencies can deliver personalized technical solutions at scale to small business customers.

Yext leaders including Founder and CEO Howard Lerman, Chief Client Officer Wendi Sturgis, Chief Strategy Officer Marc Ferrentino, President & Chief Revenue Officer Jim Steele, and EVP Global Partners Chris Penner, will share their vision for the future of Digital Knowledge Management and host a question and answer session with Partner Summit participants.

ONWARD brings together the smartest minds in marketing and technology to explore how AI, digital assistants, and intelligent search will shape our world in the years to come.

Registration for ONWARD18 is now open. Visit to learn more.

About Yext
Yext (NYSE: YEXT) is the leading Digital Knowledge Management (DKM) platform. Yext’s mission is to give companies control over their brand experiences across the digital universe of maps, apps, search engines, voice assistants, and other intelligent services that drive consumer discovery, decision, and action. Today, thousands of businesses including brands like Taco Bell, Rite Aid, and Steward Health Care use the Yext Knowledge Engine™ to manage their digital knowledge in order to boost brand engagement, drive foot traffic, and increase sales.

Yext has been named a Best Place to Work by Fortune and Great Place to Work® as well as a Best Workplace for Women. Yext is headquartered in New York City with offices in Berlin, Chicago, Dallas, Geneva, London, Paris, Tyson’s Corner, San Francisco, Shanghai, and Tokyo.  For more information, visit

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CHI Franciscan Partners with GE Healthcare to Bring First AI-Powered Hospital Mission Control Center to Washington State

TACOMA, Wash., Sept. 27, 2018 /PRNewswire/ — CHI Franciscan Health and GE Healthcare have joined forces to implement a NASA-style “Mission Control” command center to effectively and efficiently synchronize all elements of a patient’s hospital experience. The artificial intelligence (AI)-powered system will support caregivers to enhance patient safety, orchestrate seamless care delivery and, ultimately, get patients back home sooner.

CHI Franciscan will be the first hospital system in the state of Washington – and the fifth globally – to utilize the leading-edge technology to improve patient care.

“We’re leading the way in Washington with our state-of-the-art Mission Control Center, which will allow CHI Franciscan to provide a much higher level of sophistication and efficiency in our hospitals,” said Ketul J. Patel, CEO, CHI Franciscan Health. “We will be able to simultaneously monitor every single patient in our system and utilize real-time data to tailor their experience to provide the highest quality care.”

The Mission Control Center will use the power of artificial intelligence and predictive analytics to optimize care coordination, speed care delivery, and improve the patient experience, while maintaining patient privacy. The powerful system works by looking at each individual hospital as part of a larger system, continually examining real-time data and using machine learning to recommend actions that can predict and prevent risk, balance staff workload, and streamline the discharge process so patients can get home sooner.

“CHI Franciscan’s Mission Control will be among the most comprehensive in all of healthcare, combining virtual hospital, care coordination and new mission controllers working to expedite care,” said Jeff Terry, CEO, Command Centers, GE Healthcare Partners. “It’s an honor to serve CHI Franciscan.”

From the Mission Control Center, licensed providers will monitor and leverage analytic apps, or “tiles,” to optimize patient care operations at each facility, and trigger actions to best leverage resources across the system. Each tile is carefully crafted to solve a specific issue, taking into account the highly nuanced real-world challenges of caregivers and patients. For example, one tile will help streamline the discharge process by monitoring all patients scheduled for discharge and identifying and addressing “pinch points” that can cause significant and preventable delays. The key is that the real-time data in the tiles is predictive and actionable.

“Often, patients scheduled for discharge just need one more test, such as a CT scan, for the doctor to review,” said Jessica Kennedy-Schlicher, MD, medical director for care transformation at CHI Franciscan. “The people scheduling the CTs are running through a list of patients, often as first-come first-served. Mission Control will be able to prioritize the list and flag patients to move up on the list. By optimizing the process, we can speed care delivery and get patients home sooner.”

“The purpose of any new technology in health care is to enable providers to deliver better care, bringing doctors and nurses closer to their patients,” Patel said. “Mission Control’s powerful predictive analytics identify potential issues and allow our care teams to proactively solve problems and improve care rather than react when issues arise. With the AI focusing on the important nuts and bolts of operational efficiency and care logistics, our caregivers can devote more time to providing the best care and delivering the best outcomes for our patients.”

The Mission Control Center will complement CHI Franciscan’s already best-in-class Virtual Hospital, which includes regional telemetry monitoring, virtual companion, virtual ICU, virtual hospitalist, and other services. CHI Franciscan’s virtual care teams complement on-site teams, for example, by providing continuous surveillance of cardiac rhythms for inpatients, which allows on-site staff maximum time at the bedside. The virtual ICU team, which includes physicians and nurses, monitors all CHI Franciscan ICU patients, resulting in shorter ICU stays and better outcomes.

CHI Franciscan Mission Control will be organized with a systemwide Mission Control Center, and smaller centers located at St. Joseph Medical Center in Tacoma, St. Francis Hospital in Federal Way, and Harrison Medical Center in Silverdale.

CHI Franciscan is the fifth health system to join GE Healthcare’s Command Center Ecosystem, which also includes The Johns Hopkins Health System, Humber River Hospital (Toronto), Oregon Health Sciences University, AdventHealth Orlando, and Tampa General Hospital. 

About CHI Franciscan Health
CHI Franciscan Health is a Catholic nonprofit health system based in Tacoma, Washington, with $2.45 billion in total revenue and a team of more than 12,000 physicians, providers, nurses, and staff that provide expert, compassionate medical care at 11 acute care hospitals and over 200 primary and specialty care clinics throughout the greater Puget Sound. This includes St. Anthony Hospital, Gig Harbor; St. Clare Hospital, Lakewood; St. Elizabeth Hospital, Enumclaw; St. Francis Hospital, Federal Way; St. Joseph Medical Center, Tacoma; Harrison Medical Center, Bremerton and Silverdale; Highline Medical Center, Burien; Regional Hospital, Burien; CHI Franciscan Rehabilitation Hospital, Tacoma, and Wellfound Behavioral Health Hospital, Tacoma. Started in 1891 by the Sisters of St. Francis of Philadelphia, today CHI Franciscan is one of the largest health systems in Washington state. The system is comprised of more than 1,200 hospital beds and over 4,000 credentialed providers offering cardiovascular care, cancer care, orthopedics and sports medicine, neurosciences, women’s care and other health care services. CHI Franciscan’s mission is to create healthier communities, including caring for the poor and underserved. In fiscal year 2018, the organization provided $190 million in community benefit—free, subsidized, and reduced cost health care and programs. Follow CHI Franciscan on Facebook, Twitter @FHSHealth and Instagram @franciscanhealth or go to our website for information

About GE Healthcare
GE Healthcare is the $19 billion healthcare business of GE (NYSE: GE). As a leading provider of medical imaging, monitoring, biomanufacturing, and cell and gene therapy technologies, GE Healthcare enables precision health in diagnostics, therapeutics and monitoring through intelligent devices, data analytics, applications and services. With over 100 years of experience in the healthcare industry and more than 50,000 employees globally, the company helps improve outcomes more efficiently for patients, healthcare providers, researchers and life sciences companies around the world. Follow us on Facebook, LinkedIn, Twitter and The Pulse for latest news, or visit our website for more information.


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VantagePoint Trading Software Company Makes Florida Trend’s Top 100 Best Companies List

WESLEY CHAPEL, Fla., Sept. 27, 2018 /PRNewswire/ — Market Technologies, the first company in the world to bring artificial intelligence (AI) forecasting capabilities to the retail investor with VantagePoint software, was named one of Florida’s Best Companies to Work For.

Market Technologies is the company that created VantagePoint software and this year, it was included on the annual Best Companies list. The list is featured in Florida Trend Magazine each year, featuring the top one-hundred highest ranking companies in Florida.

To be considered for the list, the companies had to undergo an evaluation of their entire workplace including policies, practices, philosophy, systems and demographics. The process also included a survey to measure employee satisfaction. The combined score determined the top companies and the final ranking. Some direct quotes from employees of the company include, “Great company, great management and doing great things,” “Feels like being part of a family,” and “Best job I have ever had.”

“The best companies obviously provide strong pay and benefits to their employees, but they also offer fun diversions,” says Florida Trend Publisher Andy Corty. “And these top companies encourage employees to participate in the organization’s overall success with training and open communications.”

Florida Trend business magazine is read by influential business executives, civic leaders and government officials. Its award-winning reporting covers business news, executives, key industry sectors, regional news and lifestyle.

Market Technologies and VantagePoint software have won several other workplaces awards such as Tampa Bay Times Top Workplaces, Tampa Bay Business Journal Best Places to Work and Company of the Year by the Technology Headlines Magazine.

More info can be found at
For a free demo of the software, call 800-732-5407.

About Market Technologies
Headquartered in Wesley Chapel, Fla., Market Technologies, creators of VantagePoint Software, is a leader in trading software research and software development. VantagePoint forecasts Stocks, Futures, Forex, and ETFs with proven accuracy of up to 86%. Using artificial intelligence, VantagePoint’s patented Neural Network processes predicts changes in market trend direction up to three days in advance, enabling traders to get in and out of trades at optimal times with confidence.

Jen Aquilino
Communications Specialist

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Using AI-powered Virtual Agents to Optimize the Customer Experience of Your Contact Center

SANTA CLARA, Calif., Sept. 27, 2018 /PRNewswire/ — Artificial Intelligence-powered virtual agents present significant potential to improve the customer experience (CX) in the contact center while reducing costs. Many companies are facing business challenges such as high customer expectations, limited automation options, difficulty in implementing and deploying new contact center technologies, and agent attrition. Fortunately, the opportunity for business leaders to address such challenges through cloud-based, AI-powered engagement is considerable.

Frost & Sullivan’s new white paper, The AI-Powered Virtual Agent: Practical Realities & Actionable Strategies for Contact Center Leaders, highlights the practical applications of new cloud-based virtual agents and proposes a strategic approach to “level-up” contact center capabilities by seamlessly integrating those solutions with your existing infrastructure. It also includes different use cases across many industries such as healthcare, fashion and e-commerce.

To download the complimentary white paper, please visit:

“Companies should seek out practical AI solutions and then consider a number of action items: First, look to understand how AI agents mix with live agents to make things more efficient; second, put omnichannel CX at the center of your strategy. And third, determine which engagements are suitable for AI automation,” observed Stephen Loynd, Digital Experience Analyst at Frost & Sullivan. “This is the way to approach business-focused AI in a low-risk, high-value manner.”

By using conversational AI to automate the drudgery of data gathering or repetitive conversations, agents are empowered with more fulfilling work, allowing them to tackle challenging problems that can help them evolve into high-value employees.

“Contact centers generally have an over-reliance on live agents since natural language automation is beyond the capabilities of most IVRs,” noted Tom Lewis, CEO at SmartAction who has 30 years of contact center experience. “Cloud-based virtual agents make it easy to automate the repetitive conversations currently handled by live agents, while seamlessly integrating with the interactive voice response (IVR) and contact center platform.”

AI solutions are now demonstrating their true power in a variety of interesting and beneficial ways:

  • Enabling a voice interface for intelligent routing: Using data from the customer record, as well as from recent or repeated activity, AI can ask more intuitive questions about why a customer is calling;
  • Short- and long-term memory: AI solutions access vast amounts of data, whether it is data from a current conversation or a past one;
  • Predictive prompts: During these high-volume times, AI solutions can detect the uptick and its underlying reason and dynamically predict why customers are reaching out; and
  • Extensive personalization: With access to customer records, AI offers the ability to personalize every aspect of an automated conversation.

About Frost & Sullivan

For over five decades, Frost & Sullivan has become world-renowned for its role in helping investors, corporate leaders and governments navigate economic changes and identify disruptive technologies, Mega Trends, new business models and companies to action, resulting in a continuous flow of growth opportunities to drive future success. Contact us: Start the discussion

Mariana Fernandez
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Alternative Data Group Launches a New API Platform for Wrangling Alternative Data

NEW YORK, Sept. 27, 2018 /PRNewswire/ — Alternative Data Group (ADG), a firm specializing in alternative investment data, launched the ADG API – a programmatic platform that gives clients an ability to automatically process raw alternative datasets, making it easier for institutional investors and vendors to safely extract structured company information and ensure a dataset free of Personally Identifiable Information (PII).

With the launch of the ADG API platform, Alternative Data Group is demonstrating its capability as a premier provider of algorithmic data solutions for the growing alternative data industry. The new ticker mapping service is a direct result of four years of artificial intelligence development into the domain of structuring raw data. The unique combination of machine learning systems and live graph databases allows ADG’s mapping to reflect the daily updates in M&A activity and ownership structure. The companies identified by the API are merchants, manufacturers, hotel chains, subscription service providers, and many others, as well as their parent entities. 

Datasets such as credit card transactions, email receipts, and clickstream data could be used with the ADG platform.

The RESTful API suite will initially focus on helping firms extract structured company and ticker information from unstructured data. The individual tools in this release are:

Merchant mapper – tagging company names and tickers to unstructured text such as credit card data or email receipt data.

Domain mapper – identifying company names and tickers from domain URLs.

PII identification – detecting any personally identifiable information in unstructured text such as credit card transactions. IDSO compliant.

ADG is planning to augment its API offering with panel selection, trend detection and other tools scheduled for deployment in Q4 2018.

Alternative Data Group’s API is live and available for testing at

About Alternative Data Group:

Alternative Data Group is a provider of research and development for institutional investors. It develops algorithmic products and analyses to address challenges specific to wrangling Alternative Data. It has pioneered the use of credit card data, email receipt data, geolocation and other datasets for the purposes of improving institutional investors’ decision process. It has developed alternative data software and processes for the world’s largest hedge funds. It is headquartered in New York City. For more information visit

Alternative Data Group
Gene Ekster 

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Algorithmic Trading Market to be Worth US$ 21,807.6 Mn by 2026; Emergence of AI and Algorithms in Financial Services Sector to Drive Demand – TMR

ALBANY, New York, September 27, 2018 /PRNewswire/ —

According to a new market report published by Transparency Market Research, the global algorithmic trading market was valued at US$ 8,373.4 Mn in 2016 and is estimated to expand at a compound annual growth rate of 10.2% from 2018 to 2026, reaching US$ 21,807.6 Mn by the end of the forecast period. According to the report, North America was the largest contributor in terms of revenue to the algorithmic trading market in 2016. This is primarily due to strong technological advancement and considerable application of algorithm trading in several end-users such as banks and financial institutions across the region.

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Emergence of AI and algorithms in financial services sector and rapidly growing demand for market surveillance driving the global algorithmic trading market 

Emergence of AI and algorithms in financial services sector and rapidly growing demand for market surveillance are the major factors which are expected to fuel the growth of the algorithmic trading market across the globe. Demand for artificial intelligence (AI) and algorithmic trading solutions in the financial services sector is continuously rising. This in turn is boosting the algorithmic trading sector across the world. Furthermore, increasing adoption of non-equity trading algorithms by institutional asset managers is raising the use of artificial intelligence in the financial services sector around the globe. Apart from this, the growth of the algorithmic trading market is mainly driven by the growing demand for market surveillance. By using market surveillance technology, traders are able to keep track of their trading activities and investment pattern. In addition, the rising need to build an economy with global as well as regional interdependencies force key vendors to formulate effective marketing strategies and develop new solutions for market surveillance. This in turn is expected to drive the algorithmic trading market during the forecast period.

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In recent years, banks and financial institutions have invested in the upgrade of IT and infrastructure to perform faster trading activities, particularly in algorithmic and high frequency trading solutions. Furthermore, end-users are upgrading their system arrangement by embracing a range of managed services and platforms. Thus, unceasingly growing adoption of algorithmic trading solutions and managed services among end-users are fueling the growth of the algorithmic trading market across the world.

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Algorithmic Trading Market: Scope of the Report 

The global market for algorithmic trading is segmented on the basis of component, trading type, and geographic regions. Based on component, the market is segmented into software and services. The software segment is further split into on-premise, cloud-based, and hybrid. The services segment has been categorized into outsourced/managed services and professional services. In 2017, the software segment accounted for the largest market share, in terms of revenue of the global algorithmic trading market. Shifting trend toward cloud-based solutions is expected to accelerate the demand for cloud-based algorithmic trading software around the globe. The technology is gaining popularity in capital markets due to its flexibility, scalability, cost-effectiveness, and massive processing power. Based on trading type, the global algorithmic trading market is segmented into forex, stock markets, commodities, bonds, and cryptocurrency. In 2017, forex trading platform segment accounted for the largest share of the market, while, cryptocurrency trading platform segment is estimated to expand at a substantial rate over the forecast period.

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Based on geography, the global algorithmic trading market is segregated into North America, Asia Pacific, Europe, South America, and Middle East & Africa. Among these regions, the market for algorithmic trading in North America is expected to hold a dominant position throughout the forecast period. However, Asia Pacific and Europe are expected to contribute significant market share during the forecast period. Furthermore, the Asia Pacific algorithmic trading market is anticipated to expand at a significant growth rate during the forecast period.

Global Algorithmic Trading Market: Competitive Dynamics 

Algorithmic trading solution providers are expanding their product portfolio through mergers and acquisitions, which provide them a larger customer base with enhanced and advanced electronic trading platforms. Companies are also focusing on winning long-term contracts and providing multi-service platforms to their customers.

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The global algorithmic trading market includes different players such as Trading Technologies International, Inc., Argo Software Engineering, Inc., Automated Trading SoftTech Pvt. Ltd., InfoReach, Inc., Kuberre Systems, MetaQuotes Software Corp., Software AG, Thomson Reuters Corporation, uTrade, and Vela Trading Systems LLC (OptionsCity Software, Inc.).

Market Segmentation: Global Algorithmic Trading Market 

By Component 

  • Software
    • Cloud-based
      • Public
      • Private
    • On-premise
    • Hybrid
  • Services
    • Managed/Outsourced
    • Professional

By Trading Type 

  • Forex
  • Stock Markets
  • Commodities
  • Bonds
  • Cryptocurrency

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Our reports are single-point solutions for businesses to grow, evolve, and mature. Our real-time data collection methods along with ability to track more than one million high growth niche products are aligned with your aims. The detailed and proprietary statistical models used by our analysts offer insights for making right decision in the shortest span of time. For organizations that require specific but comprehensive information we offer customized solutions through adhoc reports. These requests are delivered with the perfect combination of right sense of fact-oriented problem solving methodologies and leveraging existing data repositories.

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