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AI for everyone

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Companies are seeing the benefits of machine learning and artificial intelligence, but many are unsure about how to truly leverage these innovations in the tech space, writes WERNER VOGELS, CTO of Amazon.com.

When a technology has its breakthrough, can often only be determined in hindsight. In the case of artificial intelligence (AI) and machine learning (ML), this is different. ML is that part of AI that describes rules and recognizes patterns from large amounts of data in order to predict future data. Both concepts are virtually omnipresent and at the top of most buzzword rankings.

Personally, I think – and this is clearly linked to the rise of AI and ML – that there has never been a better time than today to develop smart applications and use them. Why? Because three things are coming together. First: Users across the globe are capturing data digitally, whether this is in the physical world through sensors or GPS, or online through click stream data. As a result, there is a critical mass of data available. Secondly, there is enough affordable computing capacity in the cloud for companies and organizations, no matter what their size, to use intelligent applications. And thirdly, an “algorithmic revolution” has taken place, meaning it is now possible to train trillions of algorithms simultaneously, making the whole machine learning process much faster. This has allowed for more research, which has resulted in reaching the “critical mass” in knowledge that is needed to kick off an exponential growth in the development of new algorithms and architectures.

We may have come a relatively long way with AI, but the progress came quietly. After all, during the last 50 years, AI and ML were fields that had only been accessible to an exclusive circle of researchers and scientists. That is now changing, as packages of AI and ML services, frameworks and tools are today available to all sorts of companies and organizations, including those that don’t have dedicated research groups in this field. The management consultants at McKinsey expect that the global market for AI-based services, software and hardware will grow annually by 15-25% and reach a volume of around USD 130 billion in 2025. A number of start-ups are using AI algorithms for all things imaginable – searching for tumors in medical images, helping people learn foreign languages, or automating claims handling at insurance companies. At the same time, entirely new categories of applications are being created whereby a natural conversation between man and machine is taking center-stage.

Progress through machine learning

Is the hype surrounding AI and ML even justified? Definitely, because they offer business and society fascinating possibilities. With the help of digitization and high-performance computers, we are able to replicate human intelligence in some areas, such as computer vision, and even surpass the intelligence of humans. We are creating very diverse algorithms for a wide range of application areas and turning these individual pieces into services so that ML is available for everyone. Packaged into applications and business models, ML can make our life more pleasant or safer. Take autonomous driving: 90% of car accidents in the US can be traced to “human failure”. The assumption is that the number of accidents will decline over the long term if vehicles drive autonomously. In aviation, this has already been reality for a long time.

MIT pioneers Erik Brynjolfsson and Andrew McAfee predict that the macroeconomic effect of the so-called “second machine age” will be comparable to what the steam engine once unleashed when it replaced humans’ muscular strength (“the first machine age”). Many are uncomfortable with the idea that an artificial intelligence exists alongside human intelligence. That is understandable. We must therefore discuss – parallel to the technological developments – how humans and AI can co-exist in the future; the moral and ethical aspects that arise; how to ensure we have a good grip on AI; and which legal parameters we need in order to manage all this. Answering these questions will be just as important as the effort to solve the technological challenges, and neither dogmas nor ideologies will help. Instead, what’s needed is an objective, broad-based debate that takes into account the wellbeing of society as a whole.

Machine Leaning at Amazon

For the past 20 years, thousands of software engineers at Amazon have been working on ML. We dare to claim that we are the company that has been applying AI and ML as a business technology the longest. We know that innovative technologies always take off whenever barriers to entry fall for market participants.

That is the case right now with AI and ML. In the past, anyone who wanted to use AI for himself had to start from scratch: develop algorithms and feed them with enormous amounts of data – even if he later needed an application for a strictly confined context. This is referred to as so-called “weak” AI. Many of the consumer interfaces that everyone is familiar with today, such as recommendations, similarities or autofill functions for search prediction – they are all ML driven. In the meantime, they can predict inventory levels or vendor lead times, detect customer problems and automatically deduct how to solve them; and discover counterfeit goods and sort out abusive reviews, thereby protecting our customers from fraud. But that is only the tip of the iceberg. At Amazon, we are sitting on billions of historical order information data, which allows us to create other AI/ML-based models based on AI for many different kinds of functionalities. For example programming interfaces that developers can use to analyze images, change text into true-to-life language or create chatbots. But ultimately, there is something to be found for everyone who wants to define models, train them, and then scale. Pre-configured, attuned libraries and deep learning frameworks are widely available, which allow anyone to get started very fast.

Companies like Netflix, Nvidia, or Pinterest use our capabilities in ML and deep learning. More and more layers are being created in a kind of ecosystem on which companies and organizations can ‘dock’ their business – depending on how deep they want to, and are able to, immerse themselves in the subject matter. Decisive is the openness of the layers and the reliable availability of the infrastructure. In the past, AI technologies were so expensive that it was hardly worth it to use them. Today, AI and ML technologies are available off the shelf, and they can be called up according to one’s individual requirements. They form the basis for new business models. Even users who are not AI specialists can very easily and affordably incorporate the building blocks into their own services. In particular small and medium-sized companies with innovative strength can benefit. They do not have to learn any complex ML algorithms and technologies, and they can experiment without incurring high costs.

Artificial intelligence helps to satisfy the customer

One of the most advanced areas of application is e-commerce. AI-supported pre-selection mechanisms help companies to free their customers’ decision making from complexity. The ultimate goal is customer satisfaction. If there are only three types of toothpaste, the customer can easily pick one and feel good about it. When more than 50 kinds are on offer, the choice becomes complicated. You have to decide, but you’re not sure if the decision is the right one. The more possibilities there are, the more difficult it becomes for the customer. Our best-known algorithms come from this field: filtering product suggestions based on one’s purchase history of products with similar attributes, or on the behavior of other customers who were interested in similar things.

Of course, consistent quality also contributes to the satisfaction of the customer. Intelligent support makes life easier for the provider and the customer. For Amazon Fresh, for example, we have developed algorithms that learn how fresh groceries have to look, how long this state lasts, and when food should no longer be sold. Airlines or rail transport companies could also use this for their quality control by running an algorithm based on the image data of the freight; the algorithm would recognize damaged goods and automatically sort them out.

If you can predict demand, you can plan more efficiently

In B2B and B2C businesses, it is critical that goods are available quickly. It is for this reason that we at Amazon have developed algorithms that can predict the daily demand of goods. This is particularly complex for fashion goods, which are always available in many different sizes and variations and for which reorder possibilities are very limited. Information about past demand, among others, is fed into our system, as well as fluctuations that can occur with seasonal goods, the effect of special offers, and the sensitivity of customers to price shifts. Today we can predict precisely how many shirts in a certain size and color will be sold on a defined day. We have tackled this issue and made the technology available to other companies as a web service. MyTaxi, for example, benefits from our ML-based service to plan at what time and at which place the customer will need the vehicle.

New division of labor

But AI is much more than just forecasting. In the field of fulfillment, which is relevant for numerous industry sectors, we are thinking of ideas of how AI can contribute the most to taking another step away from a Tayloristic work pattern. Applied in robots, AI can free people from routine activities that are physically difficult and often stressful. Machines are very good at, and sometimes even outperform, tasks that are complicated for a human to do, such as finding the optimal route in a warehouse for a certain number of orders and transporting heavy goods to the point where it is sent to the customer. For supposedly easy tasks, by contrast, the robot is overwhelmed; an example is recognizing a box that has landed on the wrong shelf. So how to bring together the best of both players? By letting intelligent robots learn from humans how to identify the right goods, take on various orders and navigate their way autonomously through the warehouse on the most efficient route. This is how we take away the most tedious part of the task and shift resources to more interaction with the customer.

Our client SCDM uses the core idea of freeing up resources for “human” strengths, but in a completely different context. SCDM is a service provider that supports banks and insurance companies with digitization. Using AI, SCDM enables its customers to classify documents that are of very different formats (PDF, Excel or photos), for example a report about the performance of an investment product that contains hundreds of pages. By scanning hundreds of thousands of documents simultaneously, SCDM’s algorithm recognizes which document is relevant for a specific request, finds out where relevant data for a specific type of preparation is located, and then extracts the data from the document. As a result, there is less bias and fewer errors in the number crunching, and more time for human interaction with important stakeholders like investors, analysts and other customers.

Machine learning in education, medicine and development aid

In addition to their potential for things like efficiency and productivity, ML and AI can also be used in education. Duolingo, which offers free language course apps, uses text-to-language algorithms to assess and correct learners’ pronunciation. In medicine, AI supports doctors in analyzing X-Ray CTs or MRT images. The World Bank also uses AI in order to implement infrastructure programs, development aid and other measures in a more targeted manner in the future.

More room for optimism

Despite all these developments, many people from academia, business and government have a critical view of ML and AI. There have been warnings that a new super-intelligence is jeopardizing our civilization – and these warnings have been effective in attracting publicity.

However, neither hysteria nor euphoria should be allowed to get the upper hand in the public debate. What we need instead is a pragmatic-optimistic view of the emerging possibilities. AI enables us to get rid of tasks in our work which damage our health or where machines are better than we are. Not with the goal of making ourselves redundant. Rather, in order to gain more personal and economic freedom – for interpersonal relationships, for our creativity and for everything that we humans can do better than machines. That is what we should strive for. If we don’t, we will ultimately forego the economic and societal opportunities that we could have grasped.

 

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Android Go puts reliable smartphones in budget pockets

Nokia, Vodacom and Huawei have all launched entry-level smartphones running the Android Go edition, and all deliver a smooth experience, writes BRYAN TURNER.

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Three new and notable Android Go smartphones have recently hit the market, namely the Nokia 1, the Vodafone Smart Kicka 4 and the Huawei Y3 (2018). These phones run one of the most basic versions of Android while still delivering a fairly smooth user experience.

Historically, consumers purchasing smartphones in the budget bracket would have a hit-and-miss experience with processing speed, smoothness of user interface, and app stability. The Google-supported Android Go edition operating system optimises the user experience by stripping out non-important visual effects to speed up the phone. Thish allows for more memory to be used by apps. 

Google also ensures that all smartphones running Android Go will receive feature and security updates as they are released by Google. This is a major selling point for these smartphones, as users of this smartphone will always be running the latest software, with virtually no manufacturer bloatware.

Vodafone Smart Kicka 4

At the lowest entry-level, the Vodafone Smart Kicka 4 performs well as a communicator for emails and WhatsApp messages. The 4” screen represents a step up for entry-level Android phones, which were previously standardised at 3.5”.

The display is bright and very responsive, while the limited screen real estate leaves the navigation keys off the screen as touch buttons. It uses 3G connectivity, which might seem like an outdated technology, but is good enough to stream SD videos and music. Vodacom has also thrown in some data gifts if the smartphone is activated before the end of September 2018. 

Its camera functionalities might be a slight let down for the aspirant Instagrammer, with a 2MP rear flash camera and a 0.3MP selfie snapper. Speed wise, the keyboard pops up quickly, which is a huge improvement from the Smart Kicka 3. However, this phone will not play well with graphics-intensive games. 

Nokia 1

Next up is the Nokia 1, which adds a much better 5MP camera, improved battery life and a bigger 4.5” screen. It supports LTE, which allows this smartphone to download and upload at the speed of flagships. It also sports the Nokia brand name, which many consumers trust.

Although the front camera is 2MP, the quality is extremely grainy, even with good lighting. This disqualifies this smartphone for the social media selfie snapper, but the 5MP rear camera will work for the landscape and portrait photographer. 

The screen also redeems this smartphone, providing a display which represents colours truly and has great viewing angles. Xpress-on back covers allows the use of interchangeable, multi-coloured back covers, which has proven to be a successful sales point for mid-range smartphones in the past. 

Huawei Y3 (2018)

The most capable of the Android Go edition competitors, the Huawei Y3 (2018) packs an even bigger screen at 5”, as well as an improved 8MP rear camera and HD video recording. The screen is the brightest and most vibrant of the three smartphones, but seems to be calibrated to show colours a little more saturated than they actually are. 

Nevertheless, the camera outperforms the other smartphones with good colour replication and great selfie capabilities via the 2MP front camera – far superior to the Nokia 1 despite the same spec. LTE also comes standard with this smartphone and Vodacom throws in 4G/LTE data goodies until the end of September 2018. The battery, however, is not removable and may only be replaced by a warranty technician.

Comparing the 3

All three smartphones have removable back covers, which provide access to the battery, SIM card and SD card slots. The smartphones have Micro USB ports on the bottom with headphone jacks on the top. The built-in speakers all performed well, with the Y3 (2018) housing an exceptionally loud built-in speaker. 

Although all at different price points, all three phones remain similar in performance and speed. The differentiators are apparent in the components, like camera quality and screen quality. It would be fair to rank the quality of the camera and battery life by respective market prices. The Vodafone Smart Kicka 4 performed well, for its R399 retail price. The Nokia 1, on the other hand, lags quite a bit in features when compared to the Huawei Y3 (2018), bwith oth retailing at R999.

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SA gets digital archive

As the world entered the centenary of Nelson Mandela’s birth on Mandela Day, 18 July 2018, South Africa celebrated the launch of a digital living archive. 

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The southafrica.co.za  site carries content about the country’s collective heritage in South Africa’s eleven official languages.

Designed as a nation building,  educational and brand promotion web based tool, the free-to-view platform features award-winning photographic and written content by leading South African photographers, authors, academics and photojournalists.

The emphasis is on quality, credible, factual content that celebrates a collective heritage in terms of the following: Cultural Heritage; Natural Heritage; Education; History; Agriculture; Industry; Mining; and Travel.

At the same time as reflecting on the nation’s history, southafrica.co.za celebrates South Africa’s natural, cultural and economic assets so that the youth can learn about their nation in their home language.

Southafrica.co.za Founder and CEO Hans Gerrizen conceptualised southafrica.co.za as a means for youth and communities from outlying areas to benefit from the digital age in terms of the web tool’s empowering educational component.

“We can only stand to deepen our collective experience of democracy and become a more forward planning nation if we know facts about our nation’s past and present in everyone’s home language,” he says.

Southafrica.co.za, with sister company Siyabona Africa, is the organiser and sponsor of the Mandela: 100 Moments photographic exhibition that runs until 30 September at Cape Town’s V&A Waterfront-based Nelson Mandela Gateway to Robben Island.  The 3-month exhibition, which runs daily from 08h00 until 15h00, is showcasing one hundred iconic Nelson Mandela images taken by veteran South African photojournalist and self-taught lensman Peter Magubane.

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