IT Brief New Zealand - Technology news for CIOs & IT decision-makers
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IoT and machine learning are driving network transformation
Tue, 21st Aug 2018
FYI, this story is more than a year old

Artificial Intelligence (AI), machine learning and the internet of things (IoT) lead emerging technology conversations across the world. Companies recognise that these technologies are ready to be used to drive real business benefits.

The Asia Pacific and Japan (APJ) region is set to pick up the pace on these two fronts. According to a recent cloud survey by MIT Technology Review Custom and VMware, more than 70% of non-users of AI in APJ said their organisations will adopt the technology within five years.

IDC forecasted global IoT spending to surpass $1 trillion USD in 2020, with APJ leading the way.

As APJ businesses ramp up investment and adoption in IoT and machine learning, what does this mean for IT and networking infrastructure?

The Road to IoT and Machine learning

MENACE is an early example of IoT and machine learning, in that it gradually became better at playing noughts and crosses. At a recent emerging technologies event in Asia, Bruce Davie, CTO for APJ at VMware, talked about one of the earliest learning machines, MENACE. Designed by Donald Michie in the 1960s, the “Machine Educable Noughts and Crosses Engine” gradually learned to play tic-tac-toe more proficiently with each new game. Fast forward to today, machine learning has made significant advances.

It has, for instance, outstripped humans at many image recognition tasks. A striking example is the classification of a set of images of puppies and muffins. The error rate for such an algorithm in 2010 was 30%, but by 2016, after enough exposure to training data, that error rate dropped below 4%, outperforming humans. The common theme of both examples is the way algorithms improve over time with increases in both compute power and increased exposure to data.

Machine learning can help transform security from a process of chasing bad to ensuring good, by understanding the intended (“good”) state of an application and automatically detecting and responding to deviations from that state.

With its vast compute requirements and dependence on large amounts of data, machine learning frequently relies on the cloud. India and China are particularly bullish about adopting these emerging technology trends. In China, local tech giants Tencent, Baidu, and Alibaba received government support in their quest to develop these platforms across autonomous driving, healthcare, and smart cities.

Data Centers to Centres of Data

In APJ IoT is becoming a top business focus, 70% of companies view the technology as critical for the future success of their organisation. The enthusiasm for IoT is by no means unfounded. More than half of adopters in the region say IoT made significant improvements to their market competitiveness.

A New Approach to Networking

With the rise of IoT and machine learning, data and applications are becoming more distributed, from data centers to clouds to edge. This distribution of data and applications creates a new challenge for businesses and IT.

The rapid amount of change over the last 15 years is challenging the traditional network model. What new network approach will companies need to face the next 20 years or more?

CIOs in APJ lead their global counterparts in IoT and machine learning enthusiasm. For forward-thinking businesses, these emerging technologies can spark new innovations and profit streams.

To successfully unlock the true potential of emerging technologies like IoT and machine learning, businesses must embrace a Virtual Cloud Network that sharpens their edge, not one that holds it back.