In machine learning, if the training data is an unbiased sample of an underlying distribution, then the learned classification function will make accurate predictions for new samples. However, if the training data is not an unbiased sample, then there will be differences between how the training data is distributed and how the test data is distributed. Standard classifiers cannot cope with changes in data distributions between training and test phases, and will not perform well. Domain adaptation and transfer learning are sub-fields within machine learning that are concerned with accounting for these types of changes. Here, we present an introduction to these fields, guided by the question: when and how can a classifier generalize from a source to a target domain? We will start with a brief introduction into risk minimization, and how transfer learning and domain adaptation expand upon this framework. Following that, we discuss three special cases of data set shift, namely prior, covariate and concept shift. For more complex domain shifts, there are a wide variety of approaches. These are categorized into: importance-weighting, subspace mapping, domain-invariant spaces, feature augmentation, minimax estimators and robust algorithms. A number of points will arise, which we will discuss in the last section. We conclude with the remark that many open questions will have to be addressed before transfer learners and domain-adaptive classifiers become practical.

Researchers at the University of Wollongong, Deakin University, Monash University and Kyushu University have developed a framework that could be used to build a smart, AI-powered agile project management assistant. Their paper, pre-published on arXiv, has been accepted at the 41st International Conference on Software Engineering (ICSE) 2019, in the New Ideas and Emerging Results track. "Our research was driven by our experience working in and with the industry," Hoa Khanh Dam, one of the researchers who carried out the study, told TechXplore. "We saw the real challenges in running agile software projects and the serious lack of meaningful support for software teams and practitioners. We also saw the potential of AI in offering significant support for managing agile projects, not only in automating routine tasks, but also in learning and harvesting valuable insights from project data for making predictions and estimations, planning and recommending concrete actions."

In April 2018, the department of economic development, Dubai, launched a "Smart Protection" service, which adopts Artificial Intelligence (AI) to respond efficiently to consumer queries and resolve their complaints. Through an app called Dubai Consumer, the service engages consumers in a direct dialogue to gather information and, within a few minutes, issues an "empowerment letter" stating details of complaint and instructions to the retailer to resolve relevant grievance within a pre-specified time frame, failing which the retailer risks attracting fines. It was reported in November that retailers comply with instructions in empowerment letters in more than 90% cases. The service has been trained to handle grievances in more than 12 sectors and understands more than 40 laws and regulations relating to consumer protection. Imagine the utility of such a service in our country, wherein the standard of customer support and grievance redressal is abysmally poor.

The right to privacy has become a pressing human rights issue. Big data -- combined with artificial intelligence and facial recognition software -- has the capacity to intrude on people's lives in unprecedented ways, in some cases on a massive scale. While much of the discussion has focused on how social media and tech companies use the data they collect about their users, more attention needs to be paid to the wider relationship between violations of privacy and other types of human rights abuses. Mass invasions of privacy can undermine the rights of millions, if not billions, of people around the world as governments gain a greater capacity to discriminate -- or worse -- across gender and sexuality lines, and stifle dissent, including through violence. So what can be done to limit the human rights fallout?

Russia Rolls Out New Drones: Modern Combat Drones Needed to'Master the Skies' ussia must acquire a fleet of combat drones that can go toe to toe with modern air forces, Russian air force Colonel General Viktor Bondarev said Tuesday. "The entire world is on the way to developing drone aircraft, including strike aircraft," he told state news agency Itar-Tass at Russia's MAKS aerial combat arms fair, outside Moscow. "We have no right to fall behind, which is why we are carrying out analogous work in this direction. In the future, the (drone) operator will be on the ground and still master the skies."

Yemen's government has announced that the chief of its military intelligence has died of wounds he sustained during a drone attack on an army parade last week.

I don't know how self-driving car technology ranks on a difficulty scale. Perhaps it's not as difficult as rocket science, but it still must be very hard. Add to that the challenge of programming a self-driving car to make moral decisions. Take for example the MIT Media Lab experiment called "The Moral Machine," which was "designed to test how we view…moral problems in light of the emergence of self-driving cars." If a self-driving car were in a'moral bind' in which it would have to hit either an elderly person, a child or a pet to avoid the others, what should it do?

Artificial Intelligence (AI) is arguably the most revolutionary technology in several decades that would completely turn the world upside down and then shape it along with new contours. AI will reinvent everything from the nature of work to our modes of communication and transportation. The'creative destruction' unleashed by AI would make a large number of current skills and jobs redundant while opening avenues for new skills. The preeminence of AI and its far-reaching influence can be gauged from the fact that the nascent AI rivalry between USA and China has been dubbed as'The New Space Race'. In 2018, increase in AI-based applications, anxiety about a'war of the worlds' esque robotic workforce and China outpacing USA in the number of AI startups and AI related patents were the most highlighted AI trends.

The Houthis said in November they were halting drone and missile attacks on Saudi Arabia, the United Arab Emirates and their Yemeni allies, but tensions have risen over how to implement a U.N.-sponsored peace deal reached in December in the Red Sea port city of Hodeidah.

He adds: "We do this with natural language. In the third wave of AI, we may submit natural language into an AI engine and then the AI engine converts the natural language into data structures called canonicals." The data structures are the key to third wave AI tech. "We allow artificial intelligence to use deductive, inductive and abductive reasoning on whatever text it is given," says Mr. Bang. Mind AI's internationally patented core technology, Mind, has no need for supercomputers.