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モバイルネットワークの人工知能(AI)

Artificial Intelligence in Mobile Networks

 

出版社 出版年月電子版価格 ページ数
Heavy Reading
ヘビーリーディング社
2018年2月US$2,495
エンタープライズライセンス(PDF)
30

サマリー

米国調査会社ヘビーリーディング社(Heavy Reading)の調査レポート「モバイルネットワークの人工知能(AI)は、モバイル通信市場において人工知能が持つ意味を査定し、使用されている技術やAI処理が最もよく使用されている場所、どのようなAIが使用されているかを特定している。モバイル事業者が使用しているAIソリューションの市場をサプライサイドから描き、多種多様な代表的な企業を特定している。この調査レポートは人工知能市場の著名な12社の企業の概要を記載している。

EXECUTIVE SUMMARY(PDF)

Artificial intelligence (AI) is everywhere in the telecom media. Along with the Internet of Things (IoT) and 5G, it is one of the most talked about topics in the industry. Of course, AI techniques have been important in mobile telecom for a long time: neural networks have been used to identify fraudulent activity for around 20 years, and AI is a fundamental part of the threat intelligence services used by operators to keep their networks safe and provide security services to customers.

More recently there has been an explosion of interest in the use of AI-enabled voice and text interaction – building on the mass-market appeal of virtual assistants and voice-activated smart home control – to automate and improve customer service, as well as reduce the cost of these activities while improving profitability. But AI usage goes much deeper in mobile operators' business than this, and we are only at the start. AI will likely become more pervasive throughout mobile operators within the next five years, in more domains of activity and in more locations within – and beyond – the operator's network.

AI techniques have been a part of mobile telecom for decades, but we are just at the start of a rapid uptick in deployment and use of ML, deep learning and other AI approaches that will complement the big data and predictive analytics approaches already used in the industry.

We believe mobile operators are only scratching the surface of what is possible to achieve using AI: vendors are optimistic about its potential, particularly for the intelligent automation of networks in the next five years, while recognizing the need for change in the way they themselves do things.

Artificial Intelligence in Mobile Networks examines what AI means to the mobile telecom market, identifying the techniques that are being used, where AI processing is best carried out and what AI is used for. It maps the supply-side of the market for AI solutions used by mobile operators, identifying some representative players of various kinds. Finally, this report profiles 12 prominent companies in the AI market.

COMPANIES COVERED

Definitions of AI are many, complex and there are different ways in which one can sensibly try to define AI for the mobile industry. For instance, one can describe the technologies developed to enable a computer to create new capabilities without explicit programming, or one can examine the types of problems that these technologies' approaches can help to solve and how the approaches are used in specific cases. The following excerpt summarizes the mobile telecom AI ontology described in the report.

Artificial Intelligence in Mobile Networks is published in PDF format.



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プレスリリース

[プレスリリース原文]

AI Is in Diverse Parts of a Mobile Operator's Business: Here’s Why

Heavy Lifting Analyst Notes
Danny Dicks
2/28/2018

You cannot escape the noise surrounding artificial intelligence (AI) right now. Over the last year, AI has become the latest in a long list of technologies to command column inches and webinar hours in the telecom industry, replacing network functions virtualization (NFV) as the industry's second most talked-about topic (after 5G, of course).

One reason for this is the rash of announcements over the last few months of virtual agents that mobile operators have developed, using AI to underpin smarter responses to text- and voice-based interactions with customers. Vodafone was an early adopter with its Hani virtual agent that uses an AI-based platform from specialist [24]7.ai. More recently, in April 2017, Orange placed an AI-powered virtual assistant at the center of its Djingo smart home solution; in November 2017, Deutsche Telekom announced that it was planning to enhance its Tinka digital assistant (launched by T-Mobile Austria) with voice-first capability, using the Omega solution from i.am+, the tech company owned by entertainer will.i.am. A host of tech startups are active in the AI chatbot and voice-based natural-language processing space.

But this active area is a tiny part of the potential for AI in mobile telecom. For 20 years, neural networks have provided the basis for fraud detection and threat intelligence services; today, as networks become increasingly complex, AI solutions are being used to optimize antenna beam patterns and to switch carriers to optimize voice-over-LTE (VoLTE) call quality at the cell edge.

Marketing departments are using AI to ensure that proposed new products are sold at the right price -- based on an intelligent evaluation of competitor products and impact on existing offers -- and offered at the best time to appeal most to potential buyers, on a per-customer basis.

Network engineering teams are offered a choice of recommended actions to undertake preventative maintenance work, with an AI system having evaluated network performance parameters and learned which actions have the best impact. And dealing with trouble tickets is getting a whole lot easier now that the learning from millions of tickets per year can be taken into account -- far too many for the best human engineering teams to match.

The success of these applications has spurred vendors of many kinds to develop and try to "productize" AI solutions and platforms for telecom applications; though, in practice, many of the telecom-specific applications involve a great deal of bespoke development. But it is the case that AI is popping up in more and more aspects of operators' systems. The next five years will see a very rapid rise in deployment and use of such systems as the value becomes clearer.

The Heavy Reading report Artificial Intelligence in Mobile Networks examines what AI means in the context of mobile telecom, identifying the techniques that are being used, where AI processing is best done and what it is being used for. It maps the supply-side of the market for AI solutions used by mobile operators, identifying some representative players of various kinds and profiling leading and interesting vendors.

— Danny Dicks, Contributing Analyst, Heavy Reading

 
 
 

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