The artificial intelligence industry is phenomenally broad and defining it has become something of a Rorschach Test depending on who’s asking – and who’s answering – the question. What are you looking for? Deep learning? Neural networks? Big data analysis? AGI? Machine learning? Data science?
I find a more productive approach is to first chip away at what artificial intelligence isn’t, since there are many misconceptions associated with the term that simply get in the way of understanding and utilizing AI’s practical power.
In popular culture artificial intelligence is mistrusted – frequently portrayed as technology that reaches a magical threshold of brute computing power and suddenly gains self-awareness, usually with malevolent or amoral intentions. But functional artificial intelligence has nothing to do with the pursuit of machine consciousness or self-awareness. Instead, leading edge advances in AI are better characterized by ChatGPT or the recently launched Google Bard – Chatbots whose AI engines are finding uses as varied as the co-writing of scientific papers to contributing to the diagnosis and early detection of diseases. Indeed most business processes use AI to successfully find previously hidden efficiencies.
PowerX AI is continuous and its efficiencies can be monitored forever, so the yielded savings and improvements become part of the fabric of your business; not just an initial consequence of a new investment.
At present however, the telecommunications sector has a somewhat unbalanced adoption of AI technology. On one side – forward and customer-facing – AI has made terrific improvements in customer support. Vodafone’s AI driven chatbots for example are providing exceptional levels of customer service and problem solving, often indistinguishable from human counterparts (presenting as a human is of course wholly different from being sentient, and a topic worthy of its own blog).
But on the network operations side of the industry, the take-up of AI technology has yet to reach critical mass. For many, it’s still seen as a tech buzzword rather than a viable solution that will produce tangible business and customer service benefits. Aside from early investments in maintenance prediction software, the complex operation of managing thousands of towers spread across large terrains and complicated geographies has been left relatively behind by this technological wave.
This is why understanding what AI actually is becomes critical, recognizing AI’s role as an augmenter and enricher of people, processes and projects rather than a replacement.
So, returning to our opening “What is AI?” it might be more helpful to frame the question – specifically in terms of tower operations – as “What can AI do?”. Tower networks produce unimaginably huge troves of data, terabytes of potential insight into day-to-day operations that remain unutilized in archived spreadsheets and dormant data banks. AI algorithms can sift through immense quantities of seemingly sterile data and uncover hidden patterns in the micro-operation of a single tower or across a sprawling network. The more data, the higher quality the model, the more evolved, impactful and meaningful the proposed solutions. The benefits are large – reduced operating costs, improved maintenance, huge reductions in carbon emissions.
A recent PowerX application in Africa for example – a network spanning over 10,000 towers – used AI to reveal over 70,000 previous unseen anomalies on the network. No human – or team of humans – could have discovered these anomalies. But PowerX’s AI, like Microsoft’s Open AI and Google’s Bard, combines phenomenal data crunching capabilities with pattern recognition algorithms to excavate and tease out issues buried deep in the noise. Whether it’s detecting rectifier step change problems, reducing unavoidable generator run times or spotting inefficient generator loads, AI works for the humans in the mix, not as potential replacements. In fact, the insights and alerts generated by AI can increase the efficiency of tower operation teams by a factor of 30 – 50x.
For a sector that has a well-deserved reputation as a technology innovator, the telecommunications industry has been slow to embrace the big data benefits of employing AI. If you’re interested in why a sector that has been built on innovation and keeping ahead of the curve isn’t exploring the full potential of this crucial tool, this white paper addresses some of the issues I’ve touched upon in this blog. At PowerX we believe it’s time we flipped the discussion from “Why AI?” to “Why not AI?”
