AI could fundamentally change the nature of patient care delivery. Are consumers and clinicians prepared for this much-anticipated innovation? Today's unprecedented increase in the volume of patient healthcare data has left the industry struggling to put that data to practical use. Artificial intelligence (AI), with its capability to draw "intelligent" inferences based on vast amounts of raw data, may hold the solution. Smart devices and robotics are already making tentative inroads to the healthcare marketplace.

AI has taken some steps into banking, but it also poised to transform how banks learn from and interact with customers. Financial services will lead the charge in the implementation of AI. Africa's mobile phone market has expanded to become larger than either the EU or the United States with some 650 million subscribers (2016 data). At the same time, Internet bandwidth has grown 20-fold as hundreds of thousands of kilometres of new cables have been laid across the continent to serve an increasing number of its 1.2 billion Africans. Augmented experience on how to recommend how much to spend and on what.

The Kangbashi district of Ordos, China, looks like a cosmopolitan city of the future. It's just 14 years old but already has all the trappings of a mature municipality. It has a large public library designed to mimic the shape of books on shelves. Elsewhere are a contemporary and cavernous airport, a spectacular-looking stadium, clusters of towering apartment buildings, spacious plazas and parks, a five-story food court with 400 vendors, an intricate opera house, and perfectly paved streets designed to connect more than 300,000 residents to the places they live, work, and play. Although Kangbashi has the appearance of a modern metropolis, the truth is apparent in the one thing it lacks: people. Kangbashi is one of hundreds of "ghost cities" rumored to dot the Chinese countryside. Erected at the height of China's real estate boom, they're pet projects of wealthy local governments that built them to be the center of a virtuous circle: Spending their economic windfalls on megacities, governments believed, would attract inhabitants from outlying agrarian communities, creating new urban centers with which to generate even more wealth.

Millions of children around the world don't have access to basic education, such as reading, writing and arithmetic skills, and the problem is only getting worse. XPRIZE is looking to do something about it. Today, the organization announced the five finalists for the Global Learning XPRIZE; each will receive a $1 million. This particular challenge is designed around teaching basic learning to children around the world. The competition wanted easily scalable software solutions that would be relatively simple to implement.

But turbulence could be a thing of the past thanks to new technology that promises to predict the type that lurks unseen - and steer planes around it. That's according to Boeing, which will be trialing remote-sensing technology that can detect clear-air turbulence early next year. The concept, which they hope could be rolled-out across all commercial carriers, comes from a seven-tear collaboration with the Japan Aerospace Exploration Agency (JAXA) and has huge potential for travellers. According to the Federal Aviation Administration, the number of turbulence-related injuries doubled in 2016, from 21 to 44. But this could be slashed by lidar (light detection and ranging technology), which will work by emitting pulses of laser light from the plane's nose, scattering small dust and other particulates.

Pattern recognition is identified as a key human skill that has supported the rise of people to become the dominant species. However, there are limits to this crucial ability, especially when confronted with masses of information that differ only slightly. Small, but significant, variations are more easily recognised by machines that can minutely inspect and compare differences without fatigue and with low margins of error. Humans are, thus, using machines to augment their pattern-recognition capability by teaching machines how to recognise patterns and correlate seemingly disparate data to gain new insights. "Specialised machine-learning algorithms are used to evaluate large quantities of data and derive and/or exploit relationships in the data," says IBM Watson Advanced Cognitive Technology and Solutions data scientist Stefan van der Stockt. "The basic idea behind machine learning is that we want to learn relationships and corelationships between the different elements of the data, whether it be recognising a face or identifying a potentially cancerous lesion on an X-ray image," says Council for Scientific and Industrial Research (CSIR) Mobile Intelligent Autonomous Systems unit principal researcher Dr Benjamin Rosman.

Are you a data analyst, data scientist, or a researcher looking for a guide that will help you increase the speed and efficiency of your machine learning activities? If yes, then this course is for you! Google's brainchild TensorFlow, in its first year, has more than 6000 open source repositories online. It has helped engineers, researchers, and many others make significant progress with everything from voice/sound recognition to language translation and face recognition. It has also proved to be useful in the early detection of skin cancer and preventing blindness in diabetics.

For some, the spread of artificial intelligence and robotics poses a threat to our privacy, our jobs – even our safety, as more and more tasks are handed over to silicon-based brains. The 21st Century is continually throwing us new challenges and expecting us to adapt – but for every earth-shattering megatrend, there are dozens of genius solutions. Follow them all in BBC Future's special series, Grand Ideas. But even the most vocal critics highlight the potential good that AI and automated systems could do for humanity. As part of BBC Future Now's Grand Challenges, a panel of experts recently described how they saw our world changing as the machines we use grow smarter.

With recent advances in science and technology, particularly in machine learning, organizations need to adopt more comprehensive analytics strategies rather than basic analytics as large volumes of data is needed to be analyzed. Predictive learning is a technique of machine learning which aims to build a model that makes predictions based on evidence in the presence of uncertainty. It can be called as an attempt to learn with a minimum of pre-existing mental structure. Predictive learning helps in solving real world's problems in economics, business and government sector. Apart from this, it can be applied to a range of businesses to influence the future strategies including BFSI companies on account of escalating incidences of defaulters and stringent regulations for ensuring compliance with banking principles.

A team of researchers at Wits University in Johannesburg, South Africa have made a major breakthrough in the field of biomedical engineering. According to a release published on Medical Express, for the first time ever, researchers have devised a way of connecting the human brain to the internet in real time. It's been dubbed the "Brainternet" project, and it essentially turns the brain "…into an Internet of Things (IoT) node on the World Wide Web." The project works by taking brainwave EEG signals gathered by an Emotiv EEG device connected to the user's head. The signals are then transmitted to a low cost Raspberry Pi computer, which live streams the data to an application programming interface and displays the data on an open website where anyone can view the activity.