Helping operators build next generation intelligent networks
7 September 2017, Shenzhen, China – ZTE Corporation (0763.HK / 000063.SZ), a major international provider of telecommunications, enterprise and consumer technology solutions for the Mobile Internet, officially released its Artificial Intelligence (AI) Solution to help operators build next generation highly-intelligent and cost-effective automated AI networks. From platform, services, network and chip aspects, the solution fully elaborates on future-oriented AI end-to-end architecture, applications, as well as typical scenarios.
With a unified AI platform, ZTE's AI Solution can provide diversified applications, for cloud service, intelligent network, as well as chip and terminal. AI-based cloud service application can provide voice and video services which are based on face recognition, human and vehicle identification, speech recognition and Natural Language Processing (NLP) technologies. AI-based intelligent network application, which is based on precision algorithms, can provide intelligent network operation & maintenance (O&M) solution, intelligent network optimization solution, as well as intelligent network operation solution and more. In chip and intelligent terminal perspective, the solution can provide self-research AI chip, self-research robot module, and self-research intelligent terminals such as smart phone and smart home terminals.
Complemented with high computing power, precision algorithm and data analytics capability, AI technology will lead to the evolution of highly intelligent autonomous, automatic, self-optimizing and self-healing networks. At this stage, operators and vendors are still proactively exploring and seeking more efficient, stable and accurate AI algorithms and solutions to reduce the operation labor cost and effectively improve operating income.
Presently, ZTE has taken the lead in collaboration with a number of leading global and domestic operators. Through joint R&D design, joint field tests, actual network data acquisition, training and optimization, algorithm and solution iteration as well as commercialization processes have been expedited. In addition, this helps operators introduce new technologies and build next generation intelligent network more conveniently amidst the ongoing advancement of AI technologies.
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