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新興の技術:CSPによる機械学習 (ML) の大きな可能性

Emerging Technology Focus Group: CSPs See Big Promise in Machine Learning

発行 Heavy Reading 商品コード 576706
出版日 ページ情報 英文 12 Pages
納期: 即日から翌営業日
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新興の技術:CSPによる機械学習 (ML) の大きな可能性 Emerging Technology Focus Group: CSPs See Big Promise in Machine Learning
出版日: 2017年11月09日 ページ情報: 英文 12 Pages
概要

当レポートでは、通信サービスサービスプロバイダー (CSP) による機械学習 (ML) への取り組みについて調査分析し、体系的な情報を提供しています。

第1章 エグゼクティブサマリー

第2章 技術の探査

第3章 変換の戦略

第4章 仮想化 vs. 自動化戦略

用語集

目次

An overwhelming majority of communications service providers (CSPs) in the new Thought Leadership Council (TLC) recently identified machine learning as an emerging technology they're exploring.

Machine learning is just one of many emerging technologies service providers are exploring; Heavy Reading has developed a forum in which to discuss the technologies, how CSPs are using them and whether the hype over the technologies matches what's happening at the network level.

The TLC utilizes a focus group approach to glean insights directly from service providers. What makes this initiative so unique is that participants discuss topics in a completely anonymous forum, enabling them to share insights and express business realities that otherwise could not be shared.

Emerging Technology Focus Group: CSPs See Big Promise in Machine Learning was generated from a Q&A with service providers about emerging technologies. The focus group was asked about technology exploration, target service provider transformation strategies and virtualization and automation. The results clearly illustrate that many service providers are well on their way to using emerging technologies to improve their networks, make their products and services more competitive and, in as much as is possible, reduce churn.

More than 80 percent of service providers in the forum are exploring machine learning, as shown in the following excerpt. Another 13 percent of service providers in the focus group said they're planning to invest time and resources in the near future into machine learning, which is an offshoot of AI that enables systems to automatically learn and improve from experiences without being explicitly programmed. The primary goal is to enable computers to learn automatically without human intervention and adjust actions accordingly.

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Table of Contents

1. EXECUTIVE SUMMARY

  • Key Findings
  • About the Thought Leadership Council

2. TECHNOLOGY EXPLORATION

  • Figure 1. Is Your Company Actively Exploring Any of the Following Technologies?
  • Figure 2. When Will Your Company Start Taking a Serious Look at AI?
  • Figure 3. Is Blockchain Being Explored in Your Company?

3. TRANSFORMATION STRATEGIES

  • Figure 4. Has Your Company Adopted a DevOps Model Within the Network Operations Environment?
  • Figure 5. Has Your Company Adopted a DevOps Model Elsewhere?
  • Using Microservices to Create New Types of Services
  • Figure 6. What Technologies Will Be Most Critical to Achieving Your Company's Operations Transformation Goals?

4. VIRTUALIZATION & AUTOMATION STRATEGIES

  • Figure 7. When Will Automation Deliver Opex Savings to Your Organization?
  • Figure 8. When Will You Make Cloud-Native a Requirement for VNFs?
  • Figure 9. Are Any of the Applications Currently Used in Your Network Operations Environment Delivered in Containers?
  • Using PaaS to Develop Applications

TERMS OF USE

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