Artificial Intelligence is a hot topic right now, with the potential to help improve efficiency both across the network, and from a cost perspective. Kailem Anderson vice president for software and services at Blue Planet, a division of Ciena, speaks to Fibre Systems about the role of AI in operator networks

There has been a lot of buzz about AI recently, but there is still some confusion around how it should be defined. What is your perspective? AI is a bit of a nebulous term, and despite having the same underpinning concepts across market verticals, AI in the workplace tends to be a very diverse concept among our customers. At the core of AI, we have intelligent automation, a thinking machine which harnesses the power of data to make decisions and introduce greater efficiency to the workflow. The current vision of AI for operator

networks is largely based in security functions such as Distributed Denial of Service (DDoS) prevention, migration/real time automation and path selection in the network. In the future, we expect to see AI expand into new areas such as defining network topology and eventually automating decision making – using policy and human oversight to ensure consistency and reliability.

Where and how would AI best be implemented? As an immature technology, AI should be implemented in stages, with rigorous testing to ensure it has both enough data and the

24 FiBRE SYSTEMS n Issue 23 n Spring 2019

right data to form solid decision-making policies. Operators should develop projects individually, and once satisfied with the results in one area, scale deployments to cover more functions. One thing that is certain – at least for

the near future – is that operators will not surrender control of their networks to automation entirely. Rather than automated networks, they are looking to develop adaptive networking practices that harness the power and efficiency of data-driven AI, and combine it with the invaluable experience of their engineers.

How does AI play into data and analytics in the telecoms industry? There is an opportunity in the telecoms industry to nurture the growth of powerful AI technologies, as the data generated by today’s networks is vast and extremely valuable, in terms of training machines to think for themselves. By taking the data generated in the daily

operation of communications networks, it will be possible to identify patterns and form effective policies to guide the machine’s decision-making skills, as and when new situations arise.

Analytics are also critical to AI and it is

important to know how the two are related, to understand the full proposition. Analytics concerns the mining of unstructured data to aggregate information to identify patterns and implement new measures to drive efficiency. Traditionally, the data could be collected by machines, but the analysis and the implementation of new policies would need to be handled by humans. AI has therefore entered the space as an enabler, which can evaluate data without human intervention and then determine the correct action before implementing within the workflow. For network operators, this offers

considerable time and resource savings, as data collection and analysis can be automated, and with intelligent decision making, engineers can be freed up from routine maintenance, to deal with more challenging core issues affecting the network. In addition, AI offers increased security through proactive network monitoring, using historical data to spot anomalies on network services and signs of intruder connections, and thereby identify a threat and conduct self-healing functions to protect the network and preserve functionality. @fibresystemsmag

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