NEC aims to give operators a commercial boost with AI
NEC has weighed into the artificial intelligence debate launching a new offering which makes use of machine learning technologies to allow for more efficient data analytics.
February 20, 2017
NEC has weighed into the artificial intelligence debate launching a new offering which makes use of machine learning technologies to allow for more efficient data analytics.
Such an idea is not new, but there does seem to be a bit of jostling for prominence in a very crowded segment. NEC’s Net2Vec proposition uses deep learning algorithms that allow the efficient analysis of users’ data in real-time, the company claims. Better use of data analytics tools will eventually allow telcos to proactively manage customer retention, protect users from threats, identify users’ needs and respond with different tariff plans, and monetize network data via advertising.
It’s a talking point which could be well received by the telcos; making money off assets which they already control. Although the telcos control an extraordinary amount of data, regulations have prevented them from capitalizing on such information in the same way OTTs can. New potential changes to regulations could offer more freedom, giving a ray of hope to the telcos where bottom lines have been taking blow after blow.
Appealing to the telcos financial insecurities is a solid move from NEC, but diversification is another hot topic for the struggling giants. As the industry stumbles towards commoditization, telcos are desperately fighting to secure alternative revenues to ensure a fight for the bottom price isn’t the only means to generate cash moving forward. Monetizing data in the same way OTTs have is one of the options which has proven to be quite popular.
“At present, there are neither any AI solutions to address all of these problems for operators, nor existing solutions optimized for network data,” said Saverio Niccolini, GM at NEC Laboratories Europe. “Net2Vec provides an optimized system, tailored to the network, and based on existing deep learning solutions.”
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