5G + AI: better together (Part One)
Artificial Intelligence (AI) is no longer the fodder of badly written Hollywood scripts. The technology is here and emerging just as a new wave of connectivity makes its way across the globe.
As 5G networks are implemented in developed nations worldwide to stream data at several gigabytes per second while connected to the IoT (Internet of Things), the sheer volume of information being shared and collected globally is growing at a phenomenal rate.
This continuous and growing data harvest creates another phenomenon called data gravity. Finding solutions to manage and analyse such vast oceans of information, has led technocrats to AI and it’s deep computing capacity.
What is Artificial Intelligence?
Artificial Intelligence (AI) is a wide spectrum of computer sciences designed to replicate human-like abilities such as perception, logic, and learning. This constantly developing sphere uses different systems like deep learning and reinforcement learning to advance generalised intelligence.
Put simply, AI has the potential to extract business insights from previously indecipherable data to improve operations. AI is not the same as machine learning (ML) because although the concept of ML is that machines learn and adapt through experience, AI is a much wider term that involves deep learning so that computers can carry out tasks “smartly” with problem-solving intelligence.
AI has some negative connotations too in terms of its predicted ability to usurp all humanity. As the Late Professor Stephen Hawkings once told the BBC, “It [AI] would take off on its own, and re-design itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”
But for now, AI technology as it stands can be a tool instrumental in managing the gigantic swathes of data generated by human connectivity.
AI and data management
The most useful tasks AI performs today concern the repetitive learning and insight generation from data. Unlike hardware-driven robotic automation, AI can tackle high numbers of data-driven tasks consistently and without human error.
AI also gets the most out of data because it extracts useful answers from it. The role of the data is now more important than ever before because it can create a competitive advantage in business and can provide logistical solutions to manufacturing challenges. AI can even aggregate information from healthcare providers and generate solutions to improve health.
But the technoloy can also be used to harness, sort and analyse the data generated by telecom networks, with many positive outcomes, from predicting maintenance issues to optimising networks.
Wei Shi, Intelligent content manager for Telecoms.com, writes, “The exponential growth of available data is probably manifested most visibly in none other than the communications industry itself, which is powering many of the other sectors. This is a curse and a blessing. While the data available to us has vastly increased and has made advanced data analysis possible, it has also quickly made it impossible to manually process all of it.”
AI and 5G
In a report issued in 2019 by Qualcomm, predictions suggested there would be an estimated 200mn 5G smartphones by the end of 2020. Twelve months on and the market is set to more than double to 450mn in use by the end of 2021.
With the global telecom industry embracing 5G technology, communication service providers (CSP) are investing in AI in four use case areas, namely, preventative maintenance, virtual assistance, robotic process automation and network optimisation.
In terms of network optimisation, AI’s advanced algorithms search for signals within the data, helping telecom companies to detect and predict network irregularities, and allowing them to address problems before customers are negatively impacted.
Studies by the IDC (International Data Corporation) suggests that 63.5% of operators are already investing in AI solutions to streamline their infrastructure. For example, Nokia uses a self-developed, machine learning-based cloud platform called AVA to manage capacity planning and forecast service problems on cell sites a week in advance of issues happening.
Other AI solutions used by telecoms are ZeroStack’s ZBrain Cloud Management, which analyses private cloud telemetry storage for better capacity planning, upgrades and management, Sedona System’s NetFusion and an optimisation solution by Aria Networks.
AI and 5G for XR/VR
Extended reality is one of the exciting, new future use cases for AI and 5G. Both services complement each other perfectly, as AI improves the capability and experience of the renderings, while 5G can stream the high-quality content, improve performance and even device battery life.
Senior analyst at Moor Insights and Strategy, Anshel Sag says “Combining on-device AI-accelerated hand tracking with 5G enables a controller-free high-quality experience that leverages cloud-rendering. This would eliminate the need for a power cable, Wi-Fi connection or controllers, enabling applications outside of gaming, like retail.”
Sag explains, “Headsets like the nReal Light and Oculus Quest, with Qualcomm’s XR2, are great windows into 5G and AI’s potential for XR. Companies like XRSpace, with its Manova headset, are already using 5G and AI to create new virtual worlds that allow for more natural human interactions.”
Virtual assistants for use in customer service roles would also reduce business expenses by up to $8bn in 2023, according to Juniper Research.
Many telecom companies have already begun using virtual assistants to handle the large volume of support requests for installation, set up, troubleshooting and maintenance, which often overwhelm customer service call centres. But AI operators can offer self-service capabilities that advise customers on how to install and operate their own devices.
