Once a computer scientist's pipe dream, artificial intelligence is now part of our daily lives in the form of voice recognition systems, product recommendation platforms and navigation tools. All of these rely on computer algorithms that process information and solve problems in a way similar to – and sometimes superior to – the human mind. Yet artificial intelligence is doing more than just recommending new restaurants and the best routes to them. It is also changing the way scientists across diverse disciplines are studying the world. Aided by the close proximity of medical researchers, computer scientists, psychologists and more, Stanford researchers are deploying artificial intelligence to map poverty in Africa, find safer alternatives to conventional rechargeable batteries and perhaps even understand our own minds.

Kernel transfer operators, which can be regarded as approximations of transfer operators such as the Perron-Frobenius or Koopman operator in reproducing kernel Hilbert spaces, are defined in terms of covariance and cross-covariance operators and have been shown to be closely related to the conditional mean embedding framework developed by the machine learning community. The goal of this paper is to show how the dominant eigenfunctions of these operators in combination with gradient-based optimization techniques can be used to detect long-lived coherent patterns in high-dimensional time-series data. The results will be illustrated using video data and a fluid flow example.

South Africa is facing a shortage of data scientists -- a new breed of analytical data experts with the technical skills to solve complex problems. And because they straddle both the business and IT worlds, they're highly sought-after and well paid. The demand for data scientists is being driven by the emergence of big data -- that unwieldy mass of unstructured information that can no longer be ignored and forgotten. It's a potential gold mine for companies -- as long as there's someone who can dig in and unearth the business insights that no one thought to look for before. South African universities like Wits and UCT have introduced data science degrees at the master's level, but this is producing about 40 data scientists a year, far short of the number that the country's banks, insurers, retailers, health companies and telecommunications providers, among others, require.

Taking African languages into the digital and the fourth industrial ages is our responsibility. We cannot just import technology, such as speech recognition machines, but we should adjust them to our particular environments, writes Professor Tshilidzi Marwala. The Vice-Chancellor and Principal of the University of Johannesburg (UJ) as well as the author of the book Artificial Intelligence for Rational Decision Making, Prof Marwala recently penned an opinion piece, 'African'clicks' outwit artificial intelligence', published by the Sunday Independent, 13 May 2018. IsiXhosa is an interesting language that has over 9 million speakers. It is a language often associated with clicks.

Many multi-agent systems (MASs) are situated in stochastic environments. Some such systems that are based on the partially observable Markov decision process (POMDP) do not take the benevolence of other agents for granted. We propose a new POMDP-based framework which is general enough for the specification of a variety of stochastic MAS domains involving the impact of agents on each other's reputations. A unique feature of this framework is that actions are specified as either undirected (regular) or directed (towards a particular agent), and a new directed transition function is provided for modeling the effects of reputation in interactions. Assuming that an agent must maintain a good enough reputation to survive in the network, a planning algorithm is developed for an agent to select optimal actions in stochastic MASs. Preliminary evaluation is provided via an example specification and by determining the algorithm's complexity.

South Africa is facing a shortage of data scientists – a new breed of analytical data experts with the technical skills to solve complex problems. They're part mathematician, part computer scientist and part trend-spotter. And, because they straddle both the business and IT worlds, they're highly sought-after and well paid. The demand for data scientists is being driven by the emergence of big data – that unwieldy mass of unstructured information that can no longer be ignored and forgotten. It's a potential gold mine for companies – as long as there's someone who can dig in and unearth the business insights that no one thought to look for before.

A link has been posted to your Facebook feed. Question: What kind of hardware and software technology do pilots use when flying planes? Answer: Hardware and software vary by manufacturer and operator. Flight management computers use very complex software to perform a myriad of tasks. The interface is improving with airplanes such as the Boeing 787 and Airbus A350.

IsiXhosa is an interesting language that has over 9 million speakers. It is a language often associated with clicks. Our famous musician, the late Mama Africa, Miriam Makeba, made isiXhosa famous by introducing the Click Song, also called Qongqothwane to the world. Despite the stereotype, isiXhosa is not a clicking language but a Bantu language. Joseph Greenberg, the US linguist classified African languages into four stocks, one of which is the Bantu language that is spoken from Tanzania to South Africa.

Security threats are major concerns to healthcare organizations due to the value and vulnerability of clinical data that is being recorded and distributed. The value of the data comes from the fact that it is historical in nature; it directly affects our ability to safely treat patients, it takes a long time to rebuild, and it contains more than just clinical data, but also a lot of personal, financial, and demographic data, which allows it to be used for wider identity theft. It is persistent, whereas you can change credit cards and their passwords, PINs and account numbers in the event of a breach, you cannot change your mother's maiden name. The vulnerability comes from the fact that there has been a revolution in healthcare with the interconnection of systems, cloud computing, Internet of Health Things (IoHT) and mobile devices and the changes in working practices of clinicians, such as remote monitoring, telemedicine, and working from home. This revolution has not always been matched with the security awareness, policies, practices, and budgets of health care organizations.

Maven is also only one of hundreds of AI initiatives being pursued across the Pentagon. So many programs spread out over such a large organization can be the stuff of nightmares for military planners, but the building's hard-charging new undersecretary for research and engineering, Michael Griffin, said recently that he is setting up a Joint Artificial Intelligence Center that will will tie together the military's efforts with those of the Intelligence Community, allowing them to combine efforts in a breakneck push to move government's AI initiatives forward.