by
Adrian Bridgwater
In terms of events featuring multiple vendors, outside of these two we have to look to security, education or open source to find events of comparative stature. So it is then, in the age of mobile-first cloud-first computing, the GSMA’s efforts to represent the global mobile communications industry with Mobile World Congress has resulted in an event that appears to be getting bigger every year.
Mobile of course doesn’t just mean cellphones. Mobile today means smart city Internet of Things (IoT) devices and whole gamut of ‘embedded computing’, it means software specifically designed to serve smaller ‘form factor’ devices, it means cloud datacenters to pump Internet-based web services from data analytics to Artificial Intelligence (AI) onto our devices... and mobile means networks and automation layers to connect our machines with each other in the right place with the right data at the right time.
Top 7 themes
Given the white noise that will naturally be generated by the hundreds of companies exhibiting and over 100,000 attendees, can we draw out any key trends and themes to give us an approximation of the state of the mobile software union as of 2018? Here's a stab at what could be the top seven trends and topics:
1. Artificial Intelligence everywhere + Machine Learning
2. 5G enablement & LTE
3. IoT & edge computing
4. Software-Defined Networks (SDN)
5. Big data & data analytics
6. Enhanced voice services
7. Devices, some product launches are inevitable, so let's add net neutrality here too
Developing this thought, the GSMA’s own ‘suggested themes’ range are interesting, but perhaps at risk (as they have to be, really) of being somewhat generic. Yes, we know people will talk about Industry 4.0 and the so-called fourth industrial revolution.
We would also expect a lot of discussion around networks and how network operators are going to work with newer technologies including Network Function Virtualization (NFZ) and Software Defined Networks (SDN) - both essentially ways of controlling network behavior with greater software-based flexibility as opposed to hardware-based functions which may be more set and established at the point of manufacture.
We, the humans, may rise to the fore in the mobile discussion this year. As we look at ‘technology in society’ and the reality of the ‘digital consumer’ (both of which are GSMA suggested themes), we hope to hear deeper level commentary relating to the way we use devices. Shouldn’t international cultural ethics be applied to Artificial Intelligence (AI) these days?
Can we trust AI to cross borders and make the same judgments when used in the West, in China and across the Middle East? Surely we need to now look for a more sophistication and more nuanced level of development with these technologies -- and surely that intelligence must come from software engineering, right?
The age of unarticulated needs
The GSMA does provide one (arguably) rather lovely turn of phrase when it suggests that this year we will focus on, “Innovation [as] the application of better solutions that meet new requirements [and] unarticulated needs.” In other words: we know what we want, but we don’t know when we want it, how to quantify it or how to ask for it -- so we want AI and data intelligence to provide us with enough software services automation to work that part out for us -- and we want it on our smartphone. Oh… and we want it now.
But what does the industry think?
Mark Foster is senior vice president of IBM Global Business Services. Foster asserts the suggestion that mobile, connectivity and pervasive access to globally shared data has now allowed businesses to look outward in news ways. There is a new alignment of processes, data and systems in the modern digital business.
"We [IBM] believe we’re on the cusp of the next big shift in business architectures -- driven by the pervasive application of AI and cognitive technologies to the core processes and workflows of organizations. This generational shift will take the digital wave that business and governments are currently surfing to the next level and transform the way employees add value and sustain their differentiation.
We call this the era of the 'cognitive enterprise'. This new business model combines proprietary data, unique tech platforms and specialist expertise to enable companies to continually reinvent themselves for competitive advantage, ultimately winning the time and advocacy of their customers," said IBM's Foster.
Bernd Gross, senior vice president for IoT & cloud at Germany headquartered data analytics company Software AG paints a picture. He asks us to imagine for a moment the many sensors in an electronic smart IoT refrigerator. There could be one sensor each to monitor the temperature, the food on each shelf, the lights, the power and so on.
Gross explains that in a cloud computing configuration designed to serve that smart fridge, all the data would need to be sent back to a central location, analyzed and then an alert or action initiated. Now imagine not one or even six sensors, but billions of sensors all firing off all the captured data to a central location.
The bandwidth and power to support such a configuration would be untenable, so Gross suggests that more and more of our analytics is about to move outward to the edge of the devices themselves - a place we quite logically call the ‘edge’ computing space.
“We believe that while the central cloud computing model is still fundamentally important, the ‘edge’ will be critical to support the growth of the IoT in the total global mobile marketplace. Because of this, we will see the growth of new technologies coming to the forefront such as Low Power Wide-Area Networks (LPWANs), ‘special’ cellular networks and edge IoT analytics.
This means that IoT intelligence will remain at the edge with a small software footprint. What does this mean for our fridge example? First, the sensors will now include a small software footprint that captures the data and performs analytics. This means the only data sent back to a central location will be the resultant analysis or alerts. Now imagine the complexity in managing these billions of sensors or devices. This is something we are very focused on,” said Gross.
It's a virtualized world, after all
Sanjay Bhatia is VP of strategy and solutions marketing at Ribbon, a secure real time enterprise communications company that is the result of a 2017 merger between Sonus Networks and Genband. Bhatia points to a key trend in the shape of mobile network operators and their continued march towards next generation Network Function Virtualization (NFV) cloud networks that rely less on purpose built hardware solutions.
He says that these inherently ‘software-defined’ NFV worlds are a more agile, flexible and cost effective method of using cloud-native functions that employ microservices architectures running on common hardware infrastructure. No surprise this is key for Ribbon, that is - the company has already deployed virtualized NFV functions commercially and plans to make the most of this space in 2018.
Ribbon’s Bhatia also points to new mobile technologies such as Enhanced Voice Services (EVS). “The new EVS premium HD voice codec will bring dramatically improved call quality and reliability, while using lower bandwidths for improved efficiency and coverage,” he said. “EVS is a path to offer customers better user experiences by addressing issues like spotty coverage with dramatically improved call quality and reliability, while using lower bandwidth and enhancing network efficiency.”
Also commenting on this story, we heard from CTO of mobile application development platform company Kony, Bill Bodin. Insistent that AI will play a profound role in changing how we live and work, Bodin says that AI frameworks have now matured to a point where developers can create chatbots and conversational apps for virtually any global market segment.
“Major AI engines have moved beyond simple utterance and intent matching, pairing automatic speech recognition (ASR’s) and natural language understanding (NLU) components capable of highly accurate speech to text conversions and intent matching. The API’s for these services have never been easier to integrate, and with RESTful (Representational State Transfer) based calls and JSON (JavaScript Object Notation) formatted payloads, the programmatic chore of interpreting AI output has also been drastically simplified,” said Bodin.
A new era of mobile conversational apps
Kony’s Bodin further explains that developers will ultimately be creating completely conversational enterprise mobile apps, with many of them also focusing on using machine learning (ML) as a means of bridging disparate systems of record, avoiding much of the legacy programming and allowing different systems to converse, discover their syntactical differences, learn from each other, and ultimately interoperate.
“Rules based systems will also dominate when paired with ML and AI. We can no longer think simply ‘mobile-first’, but now in terms that provides integration for all digital channels, delivered to any digital device. This is not just a vision, but the reality we are creating every day,” he added.
Not about the ‘shiny shiny’ anymore
There are plenty of shiny devices, clever smartphones, flashy Virtual Reality (VR) headsets and fabulous video-screen watches on show at Mobile World Congress 2018. But it’s not really about the ‘shiny shiny’ anymore and we’ve been saying that for most of this decade.
Today we want to know more about what happens down at the network level (you could say inside the cloud computing brain, if you wish) and where we are going to apply all that smart intelligence to solve life problems that we haven’t even properly identified as yet.
Software runs the world and mobile-first software is at the vanguard. Now, please set your phones to silent or vibrate, wipe your screen and wash your hands.
*First published in forbes.com
By: N. Peter Kramer
