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December 23, 2016
While 2016 proved to be a solid year for incremental advancements in 5G, IoT and cloud computing, 2017 is set to be a big year for a number of breakthrough technologies.
Figuring out what the next big thing is going to be and investing the right amount of time, money and resource can make the difference between becoming the next Google or simply being forgotten, so we took the chance to ask a few people in the industry what they thought.
While it didn’t necessarily breakthrough to the mainstream in 2016, artificial intelligence has never been too far away. Major players such as Facebook, Google, AWS and IBM have been investing heavily in AI technology, and minor product releases throughout the year have begun to normalise the technology in the eyes of the world. For Dik Vos, CEO of SQS, 2017 is year machines will start taking our jobs.
“Machines will steal more human jobs than ever with 30% of the working population needing to be retrained,” said Vos. “We will continue to see a rise in digital technology over the coming years, and 2017 will be the year we see the likes of AI and automated vehicles take the place of low-skilled workers.
“With machines pushing humans out of a number of jobs including, logistics drivers and factory workers, I predict we will see an increased emphasis placed on the retraining of up to 30 per cent of our working population. People want and need to work and 2017 will see those workers who have lost their jobs through digitalisation, start to filter across a variety of other sectors including manufacturing and labour.”
That said, there is some work before AI could be mainstream or a realistic function within the working world. Part of the reason is that there are not enough genuine use-cases (that have been proven to be currently viable) in place, though the technology isn’t quite there just yet. One major step forward would be the introduction of effective edge analytics technologies, which is where Deepu Talla, GM of Tegra at Nvidia sees the next breakthrough in 2017.
“In 2017, we’ll see more AI move from the cloud to the edge,” said Talla. “That is, we’ll see AI computing capability expand to the billions of devices that collect data in the field, rather than residing only on data center servers.
“This is important for applications where large amounts of data need to be processed in real-time, and where bandwidth and latency can be a challenge. Examples range from intelligent security systems that can identify potential dangers to keep our cities safer, to industrial robotics where predictive analytics can optimize manufacturing production.”
To continue on this ominous note, with the advancement of technology also comes the advancement of those who would abuse it. New legislation around the world pays testament to the fact police forces and intelligence agencies need to adapt to the digital era, as criminals have already begun. For Mark Noctor, VP of EMEA for Arxan Technologies, cyberterrorism is only just beginning, and its set to get a lot wore
“There was a lot of talk about hacking during the elections but the reality is that a proxy cyberwar has been going on for some time between various nations and it’s only going to accelerate in 2017,” said Noctor. “We expect major attacks occurring at the government infrastructure as well as commercial companies at the IoT level causing serious damage.”
On a more positive note, Chris Haddock, Head of Marketing at OpenCloud, predicts operators will turn a corner, creating new business models.
The last few years has seen the telco industry’s previously cosy profits challenged and eroded, as OTTs started offering communications services for free. The telcos were issued the challenge of finding new revenues to keep investors happy. This isn’t a case of evolution, it’s an entirely new playing field.
On that note, we saw one of the biggest acquisitions ever in 2016; AT&T’s purchase of Time Warner. It shook the industry, mainly due to the sheer size of the $109 billion acquisition, but also because of the confidence in becoming a content owner to replace lost revenues.
“2017 will be a year of new M&A activity, as operators look to acquire content providers, following the trend set by AT&T’s purchase of Time Warner this year. TV and streaming services are no longer just the remit of broadcasters and OTT players,” said Haddock. “Mobile operators will offer unique content packages, as they make the shift to become multi-play businesses, able to provide content services at any time, to subscribers anywhere.”
“Operators will not create their own content, but through strategic partnerships and acquisitions they can acquire a range of exclusive content, offering it to subscribers as a way to differentiate their propositions. Subscribers will start selecting operators based on the content that they provide (for example, choosing sports, TV or film packages). This will help to attract and retain customers, and provide an additional revenue source for multi-play operators.”
And while content may be a route to new revenues, John Schroeder, CEO at MapR sees data as a means to recover.
New legislation and regulations in the EU will aim to level the playing field for telcos in the long-standing battle with the OTTs. These new rules will enable telcos to monetize data in the same ways OTTs currently can, offering opportunities for numerous new business models and revenue channels. If data is the currency of the digital economy, telcos have bursting bank accounts and just need the PIN.
“Software development has become agile where Devops provide continuous delivery,” said Schroeder. “In 2017, processing and analytic models evolve to provide a similar level of agility as organisations realise data agility, the ability to understand data in context and take business action, is the source of competitive advantage not simply have a large data lake.
The emergence of agile processing models will enable the same instance of data to support batch analytics, interactive analytics, global messaging, database and file-based models. More agile analytic models are also enabled when a single instance of data can support a broader set of tools. The end result is an agile development and application platform that supports the broadest range of processing and analytic models.”
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