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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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News fatigue shifts Google searches in SA

Google search trends in South Africa reveal a startling insight into news appetite, writes BRYAN TURNER.

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The big searches of the year no longer track the biggest news stories of the year, suggesting a strong dose of news fatigue among South Africans.

“People ask, why are the Guptas not on the list of Google’s top searches?, says Mich Atagana, head of communications and public affairs at Google South Africa, “The Guptas are not on the list because South Africans are not actually that interested. South Africans are looking for things they don’t know. From a Gupta point of view, we’ve been exhausted by the news and we know exactly what is going on.”

Google South Africa announced the results of its 2018 Year in Search, offering a unique perspective on the year’s major moments.

“Four years ago, there were almost no South Africans on the personalities list,” says Atagana. “Over the years, South Africans have gotten more interested in South Africa, in searching on Google.”

That isn’t to say that international searches – like Meghan Markle – are not heavily searched by South Africans. But  they feature lower down on the lists.

From the World Cup to listeriosis, Zuma and Global Citizen, South Africans use search to find the things they really need to know.

These are the main trends revealed  by Google this week:

Top trending South African searches

  1. World Cup fixtures
  2. Load shedding
  3. Global Citizen
  4. Zuma
  5. Winnie Mandela
  6. HHP
  7. Listeriosis
  8. Black Panther
  9. Meghan Markle
  10. Mac Miller

Trending personalities

  1.    Jacob Zuma
  2. Cyril Ramaphosa
  3. Sbahle Mpisane
  4. Kevin Anderson
  5. Malusi Gigaba
  6. Ashwin Willemse
  7. Patrice Motsepe
  8. Cheryl Zondi
  9. Shamila Batohi
  10. Mlindo the Vocalist

Top Questions

  1. How did Avicii die?
  2. How old is Pharrell Williams?
  3. What is listeriosis?
  4. What is black data?
  5. How old is Prince Harry?
  6. How much are Global Citizen tickets?
  7. How to get pregnant?
  8. What time is the royal wedding?
  9. What happened to HHP?
  10. How old is Meghan Markle?

Top ‘near me’ searches

  1. Jobs near me
  2. Nandos near me
  3. Dischem near me
  4. McDonalds near me
  5. Guest house near me
  6. Postnet near me
  7. Steers near me
  8. Spar near me
  9. Debonairs near me
  10. Spur near me

Top women

  1. Winnie Mandela
  2. Meghan Markle
  3. Sbahle Mpisane
  4. Aretha Franklin
  5. Khloe Kardashian
  6. Sophie Ndaba
  7. Cheryl Zondi
  8. Demi Lovato
  9. Lerato Sengadi
  10. Siam Lee

The Year In Search 2018 minisite can be found here.

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Smartphones dip in 2018

According to the International Data Corporation (IDC) Worldwide Quarterly Mobile Phone Tracker, worldwide smartphone shipments are expected to decline by 3% in 2018 before returning to low single-digit growth in 2019 and through 2022.

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While the on-going U.S.-China trade war has the industry on edge, IDC still believes that continued developments from emerging markets, mixed with potential around 5G and new product form factors, will bring the smartphone market back to positive growth.

Smartphone shipments are expected to drop to 1.42 billion units in 2018, down from 1.47 billion in 2017. However, IDC expects year-over-year shipment growth of 2.6% in 2019. Over the long-term, smartphone shipments are forecast to reach 1.57 billion units in 2022. From a geographic perspective, the China market, which represented 30% of total smartphone shipments in 2017, is finally showing signs of recovery. While the world’s largest market is still forecast to be down 8.8% in 2018 (worse than the 2017 downturn), IDC anticipates a flat 2019, then back to positive territory through 2022. The U.S. is also forecast to return to positive growth in 2019 (up 2.1% year over year) after experiencing a decline in 2018.

The slow revival of China was one of the reasons for low growth in Q3 2018 and this slowdown will persist into Q1 2019 as the market is expected to drop by 3% in Q4 2018. Furthermore, the recently lifted U.S. ban on ZTE had an impact on shipments in Q3 2018 and created a sizable gap that is yet to be filled heading into 2019.

“With many of the large global companies focusing on high-end product launches, hoping to draw in consumers looking to upgrade based on specifications and premium devices, we can expect head-to-head competition within this segment during the holiday quarter and into 2019 to be exceptionally high,” said Sangeetika Srivastava, senior research analyst with IDC’s Worldwide Mobile Device Trackers.

Though 2018 has fallen below expectations so far, the worldwide smartphone market is set to pick up on the shift toward larger screens and ultra-high-end devices. All the big players have further built out their portfolios with bigger screens and higher-end smartphones, including Apple’s new launch in September. In Q3 2018, the 6-inch to less than 7-inch screen size band became the most prominent band for the first time with more than four times year-over-year growth. IDC believes that larger-screen smartphones (5.5 inches and above) will lead the charge with volumes of 947.1 million in 2018, accounting for 66.7% of all smartphones, up from 623.3 million units and 42.5% share in 2017. By 2022, shipments of these larger-screen smartphones will move up to 1.38 billion units or 87.7% of overall shipment volume.

“What we consider a so-called normal size smartphone has shifted dramatically in a few short years and while we are stretching the limits with bezel-less devices, the next big switch to flexible screens will test our imaginations even further,” said Melissa Chau, associate research director with IDC’s Worldwide Mobile Device Trackers. “While this category of device is still nascent and won’t see major adoption in the year ahead, it’s exciting to see changes to the standard monoblock we are all so used to carrying.”

Platform Highlights

Android: Android’s smartphone share will remain stable at 85% throughout the forecast. Volumes are expected to grow at a five-year compound annual growth rate (CAGR) of 1.7% with shipments approaching 1.36 billion in 2022. Android is still the choice of the masses with no shift expected. Android average selling prices (ASPs) are estimated to grow by 9.6% in 2018 to US$258, up from US$235 in 2017. IDC expects this upward trajectory to continue through the forecast, but at a softened rate from 2019 and beyond. Not only are market players pushing upgraded specs and materials to offset decreasing replacement rates, but they are also serving the evolving consumer needs for better performance.

iOS: iOS smartphones are forecast to drop by 2.5% in 2018 to 210.4 million. The launch of expensive and bigger screen iOS smartphones in Q3 2018 helped Apple to raise its ASP, simultaneously making it somewhat difficult to increase shipments in the current market slump. IDC is forecasting iPhone shipments to grow at a five-year CAGR of 0.1%, reaching volumes of 217.3 million in 2022. Despite the challenges, there is no ambiguity that Apple will continue to lead the global premium market segment.

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