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What do Swarovski and machine learning have in common?

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At the SAP Leonardo Live conference in Frankfurt, Swarovski revealed how it uses SAP Leonardo to integrate machine learning into its retail business model, writes TIANA CLINE.

From jewellery to tsatskes, home décor and watches, Swarovski is a global name when it comes crystal-anything. It’s also a company with humble roots – Swarovski started out in 1895 as a small crystal manufacturing business in Wattens, Austria.

You probably know Swarovski retail, but to stay ahead of the pack from both a business and creative perspective, the company relies heavily on enterprise software solutions and intelligent applications to innovate their business model.

And with the help of SAP Leonardo, the game-changing system and Internet of Things (IoT) platform launched in Frankfurt this week, they’re integrating machine learning into their retail business model to prepare, provision and analyse their data (and essentially make their damaged good process a lot simpler).

At the Swarovski global repair centre, the company was faced with a challenge when new items were sent in to be fixed. With a massive product catalogue, locating a material number, business unit, produce date or even produce often ended up in time-consuming Google searches.

And while they were successful, the results yielded were comprised of a picture and not necessarily the data required to take the next step.

With SAP machine learning, a feature of Leonardo, Swarovski created an intelligent library of classified product images which enabled faster customer interaction – the database now brings up precise images and potential product repair costs.

Unlike traditional image searches where background noise and quality affect results, machine learning is not reliant on shape and other factors, the results are bases on intelligent learning algorithms and AI-based insights that have the ability to unlock “hidden knowledge” in data. Machine-based neural networks can understand a billion pieces of data in seconds.

What’s next for the crystal company? According to Werner Huber, the IT Demand Manager at Swarovski Corporate IT, they’re looking at installing in-store sensors which can count the customers coming in, smartly being able to distinguish between those who use the store as a through path, for example, or those who return.

There is also the potential for facial recognition, so they can gather smart data based on gender, approximate age, buying patterns, etc.

(A few years back, Swarovski also built a app to showcase their crystal assortment, called the Crystal Collection App.)

With the help of SAP, Swarovski is at the forefront of design, creativity, and technological innovation.

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Smart home arrives in SA

The smart home is no longer a distant vision confined to advanced economies, writes ARTHUR GOLDSTUCK.

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The smart home is a wonderful vision for controlling every aspect of one’s living environment via remote control, apps and sensors. But, because it is both complex and expensive, there has been little appetite for it in South Africa.

The two main routes for smart home installation are both fraught with peril – financial and technical.

The first is to call on a specialist installation company. Surprisingly, there are many in South Africa. Google “smart home” +”South Africa”, and thousands of results appear. The problem is that, because the industry is so new, few have built up solid track records and reputations. Costs vary wildly, few standards exist, and the cost of after-sales service will turn out to be more important than the upfront price.

The second route is to assemble the components of a smart home, and attempt self-installation. For the non-technical, this is often a non-starter. Not only does one need a fairly good knowledge of Wi-Fi configuration, but also a broad understanding of the Internet of Things (IoT) – the ability for devices to sense their environment, connect to each other, and share information.

The good news, though, is that it is getting easier and more cost effective all the time.

My first efforts in this direction started a few years ago with finding smart plugs on Amazon.com. These are power adaptors that turn regular sockets into “smart sockets” by adding Wi-Fi and an on-off switch, among other. A smart lightbulb was sourced from Gearbest in China. At the time, these were the cheapest and most basic elements for a starter smart home environment.

Via a smartphone app, the light could be switched on from the other side of the world. It sounds trivial and silly, but on such basic functions the future is slowly built.

Fast forward a year or two, and these components are available from hundreds of outlets, they have plummeted in cost, and the range of options is bewildering. That, of course, makes the quest even more bewildering. Who can be trusted for quality, fulfilment and after-sales support? Which products will be obsolete in the next year or two as technology advances even more rapidly?

These are some of the challenges that a leading South African technology distributor, Syntech, decided to address in adding smart home products to its portfolio. It selected LifeSmart, a global brand with proven expertise in both IoT and smart home products.

Equally significantly, LifeSmart combines IoT with artificial intelligence and machine learning, meaning that the devices “learn” the best ways of connecting, sharing and integrating new elements. Because they all fall under the same brand, they are designed to integrate with the LifeSmart app, which is available for Android and iOS phones, as well as Android TV.

Click here to read about how LifeSmart makes installing smart home devices easier.

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Matrics must prepare for AI

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students writing a test

By Vian Chinner, CEO and founder of Xineoh.

Many in the matric class of 2018 are currently weighing up their options for the future. With the country’s high unemployment rate casting a shadow on their opportunities, these future jobseekers have been encouraged to look into which skills are required by the market, tailoring their occupational training to align with demand and thereby improving their chances of finding a job, writes Vian Chinner – a South African innovator, data scientist and CEO of the machine learning company specialising in consumer behaviour prediction, Xineoh.

With rapid innovation and development in the field of artificial intelligence (AI), all careers – including high-demand professions like engineers, teachers and electricians – will look significantly different in the years to come.

Notably, the third wave of internet connectivity, whereby our physical world begins to merge with that of the internet, is upon us. This is evident in how widespread AI is being implemented across industries as well as in our homes with the use of automation solutions and bots like Siri, Google Assistant, Alexa and Microsoft’s Cortana. So much data is collected from the physical world every day and AI makes sense of it all.

Not only do new industries related to technology like AI open new career paths, such as those specialising in data science, but it will also modify those which already exist. 

So, what should matriculants be considering when deciding what route to take?

For highly academic individuals, who are exceptionally strong in mathematics, data science is definitely the way to go. There is, and will continue to be, massive demand internationally as well as locally, with Element-AI noting that there are only between 0 and 100 data scientists in South Africa, with the true number being closer to 0.

In terms of getting a foot in the door to become a successful data scientist, practical experience, working with an AI-focused business, is essential. Students should consider getting an internship while they are studying or going straight into an internship, learning on the job and taking specialist online courses from institutions like Stanford University and MIT as they go.

This career path is, however, limited to the highly academic and mathematically gifted, but the technology is inevitably going to overlap with all other professions and so, those who are looking to begin their careers should take note of which skills will be in demand in future, versus which will be made redundant by AI.

In the next few years, technicians who are able to install and maintain new technology will be highly sought after. On the other hand, many entry level jobs will likely be taken care of by AI – from the slicing and dicing currently done by assistant chefs, to the laying of bricks by labourers in the building sector.

As a rule, students should be looking at the skills required for the job one step up from an entry level position and working towards developing these. Those training to be journalists, for instance, should work towards the skill level of an editor and a bookkeeping trainee, the role of financial consultant.

This also means that new workforce entrants should be prepared to walk into a more demanding role, with more responsibility, than perhaps previously anticipated and that the country’s education and training system should adapt to the shift in required skills.

The matric classes of 2018 have completed their schooling in the information age and we should be equipping them, and future generations, for the future market – AI is central to this.

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