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AI slashes treatment time

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ANESHAN RAMALOO, Senior Business Solutions Manager at SAS, looks into how 2018 will see how technology trends will shape developments through the year.

It used to take months to be able to say whether a particular treatment for cancer was working – wasting precious time which might otherwise have been used to save a patient’s life. Now using analytics, we can predict that treatment’s effectiveness within days.

When addressing the question of what to expect in the tech space in 2018, there is no limit. AI is already doing things we never before would have dreamed possible. From writing music to creating videos, we are achieving milestones which we previously would have considered strictly human.

And yes, it is even helping to save lives.

One of the major forces driving the world of tech and AI is the increasing volume and availability of data. Think of devices like the Fitbit, which provides a wealth of data concerning your health, such as heart rate and sleeping patterns.

At the same time, we’ve developed technology that allows us to analyse more data than ever before. And thanks to a massive improvement in compute power, analytical solutions can now analyse these massive volumes of data at blistering speed. Data scientists can develop machine learning models in minutes, which can enable businesses to deliver results quickly.

A great example of the technology that allows this is SAS VIYA, which is an end-to-end analytical platform. The platform fuels the analytics life cycle from data preparation to model development and finally deployment. This is all done in a single interface

One feature of the SAS platform that I’m particularly excited about is the ability to analyse images. This capability is already helping when it comes to wildlife conservation. In the past game rangers had to manually take pictures of particular species of animals and tag them. While this wasn’t part of their core focus, it absorbed a great deal of time. But using SAS’s new technology they can simply take the picture and allow the AI to classify, not only the species of the animal, but other helpful traits such as the sex as well. At the end of the day this frees up the rangers to tackle more important tasks.

More accurate predictions

While the algorithms used in machine learning have been relatively unchanged for decades, we are now seeing the emergence of new algorithms, such as extreme gradient boosting, which have proven to be very successful in data mining competitions like Kaggle. Extreme gradient boosting is a significant development in analytics because it generalises well, enabling more accurate predictions.

While we’ve been drawing on structured data sources like transactional data for some time, no-one has really been tapping into unstructured data sources. For example, customer complaints, reviews and other text data sources.

But these two sources when combined together can be extremely powerful. Say, for instance, you wanted to develop a customer churn prediction model. By including data sources like customer complaints, as opposed to just structured and traditional data sources, you can develop a model that is more accurate at predicting churn.

Deep learning has created a lot of hype, and for good reason.

It is a type of machine learning, based on a set of algorithms that model high-level abstractions in data, by using multiple processing layers with complex structures.Instead of organising data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognising patterns using many layers of processing. This means it can train computers to perform human-like tasks, such as recognising speech, identifying images or making predictions.

Deep learning is already being used to make significant inroads into areas such as image recognition, fraud detection and the highly regulated credit risk modelling. In fact, SAS is currently working with credit bureau, Equifax, using deep learning techniques in credit risk modelling. The results are promising as the accuracy of the models has improved traditional techniques.

Bots that understand emotion

Another exciting space in AI is bot technology. Chatbots are programmes that use natural language processing and AI to create conversations between machines and humans.

Instead of having a human respond to complaints or queries, this can now be done by a chatbot to save time and money on mundane and repetitive tasks. For example, responses to queries on bank accounts. Some banks are using bots to advise customers on financial advice and investments.

Until now, AI has generally been designed to do specific things like fraud detection. The human ability to perform tasks has always been greater than machines as we can generalise and perform a much wider set of functions.

But incredibly we’re starting to see AI train itself to learn.

In 2016 Google created a programme called AlphaGo. It was capable of beating even the most skilled human players at the ancient Chinese strategy game, Go – considered to be one of the most complicated games on earth.

But this was taken a step further through the creation of AlphaGo Zero, a programme provided with a very limited amount of training data. The idea was that it would learn by playing against itself. Over a period of time, AlphaGo Zero beat AlphaGo.

Essentially it had taught itself to think.

On the threshold of a future in which machines can think and learn: as we step into 2018, one could say nothing is impossible.

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CES: And thanks for all the beer!

Last week, the Las Vegas expo showed off its fun side with state-of-the-art technologies for making and enjoying beer, writes BRYAN TURNER

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From craft beer-making machines to robots that pour beer, CES had more beer than usual in Las Vegas last week. And even free beer if you found the right stand. Stampede’s saloon-style booth offered beer to visitors who tried out its latest drones, virtual reality, and other gaming products. No beer tech, though.

Here are some of the beer technologies that stood out:

LG HomeBrew – Craft beer made at home

LG’s HomeBrew craft beer-making machine,  debuted at CES 2019, brings the brewing process home thanks to single-use capsules,  a self-cleaning feature, and an algorithm optimised for fermentation. 

Like a Nespresso coffee machine, the beer maker uses capsules, which contain malt, yeast, hop oil and flavouring. At the press of a button, LG HomeBrew automates the whole procedure from fermentation and carbonation to ageing. A companion app lets users check HomeBrew’s status at any time during the process, from their handsets.

The beer machine not only offers a simple way to make craft beer, but also enhances the quality of beer it makes. The fermentation algorithm intelligently controls the fermenting process with precise temperature and pressure control. It automatically sanitises itself, using nothing more than hot water, ensuring everything is hygienically clean for the next batch.

Designed with discerning beer lovers in mind, HomeBrew allows for in-home production of batches of more than 4 litres of beer in a variety of styles. The following five distinctive, flavoured beers are available now: 

  • Hoppy American IPA
  • Golden American Pale Ale
  • Full-bodied English Stout
  • Zesty Belgian-style Witbier
  • Dry Czech Pilsner

The only catch? It takes about two weeks to make, depending on the beer type.

“LG HomeBrew is the culmination of years of home appliance and water purification technologies that we’ve developed over the decades,” said Dan Song, president of LG Electronics Home Appliance & Air Solutions Company. “Homebrewing has grown at an explosive pace, but there are still many beer lovers who haven’t taken the jump because of the barriers to entry, like complexity, and these are the consumers we think will be attracted to LG HomeBrew.”

Click here to read about the party speaker that holds beer and robots that pour beer.

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CES: Alienware gets Legend-ary

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At CES in Las Vegas last week, Dell’s Alienware released a family of high-end, thin, light, and affordable machines for both amateur and professional gamers – and a new identity.

Alienware marked CES 2019 as a brand milestone with the debut of a new design identity, Alienware Legend. It aims to set a new bar of excellence for what gamers want most – performance and function. Alienware says it evaluated multiple concepts and chose one that was the biggest and boldest departure from its current look.

Alienware Legend, says the company, stays true to the brand’s core design tenets, taking cues from its deep roots in sci-fi culture and its early industrial designs, to distinguish the brand from the rest of the industry. The new Legend design is optimised with cutting-edge thermal cooling technology to achieve and sustain overclocking power, improved AlienFX lighting, and ultra-thin screen borders. It also unveiled a new “three-knuckle hinge” design that reduces the overall dimension while creating a stronger assembly, all combining to yield a better gaming experience.

“We’re excited to come to this year’s CES with some truly groundbreaking products, next-gen software and strategic partnerships that will bring more people to experience PC gaming and advance the industry,” said Frank Azor, vice president and general manager of Alienware. “The legend design answers the call for more and better from our gaming community, and the new G Series laptops will make PC gaming even more accessible to those looking for high-performance gaming at a cost they can appreciate.”

Click here to read about Alienware Legend in action with the Area-51m and m-series laptops

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