IMAGE: Andrew Trapp, an associate professor in the Foisie Business School at Worcester Polytechnic Institute (WPI), and PhD student Narges Ahani are working on an NSF-funded grant to develop software to... view more Built upon ongoing work with an international team of computer scientists and economists, the tool integrates machine learning and optimization algorithms, along with complex computation of data, to match refugees to communities where they will find appropriate resources, including employment opportunities. "There is a great deal of information to consider when helping a refugee begin a new life in the United States," said Trapp, associate professor in the Foisie School and lead investigator for the project. "It is a labor-intensive process whose ultimate goal is to help a refugee land in a place where he or she has as many opportunities as possible to successfully integrate and contribute to the community. Technological solutions can have a profound societal impact." Each year, tens of thousands of refugees--many fleeing war, violence, and persecution--are resettled in dozens of host countries around the world.

In a particularly pungent case of victim-blaming, "hard-line Republicans and conservative commentators are mounting a whispering campaign against Jamal Khashoggi that is designed to protect President Trump from criticism of his handling of the dissident journalist's alleged murder by operatives of Saudi Arabia -- and support Trump's continued aversion to a forceful response to the oil-rich desert kingdom," The Washington Post reports, citing four GOP officials involved in the discussions. The campaign includes "a cadre of conservative House Republicans allied with Trump" who in recent days have been "privately exchanging articles from right-wing outlets that fuel suspicion of Khashoggi," a Post columnist and Saudi government critic, the Post says. Still, the murmurs have begun to "flare into public view" as conservative media organizations and personalities -- Rush Limbaugh, Front Page, Donald Trump Jr., and a sanitized version on Fox News, to name a few -- "have amplified the claims, which are aimed in part at protecting Trump as he works to preserve the U.S.-Saudi relationship and avoid confronting the Saudis on human rights." The main lines of attack -- pushed by pro-Saudi accounts on Twitter -- focus on and distort Khashoggi's association with the Muslim Brotherhood in his young and interactions as a journalist with late Al Qaeda leader Osama bin Laden in the 1980s and '90s. "The GOP officials declined to share the names of the lawmakers and others who are circulating information critical of Khashoggi," the Post explains, "because they said doing so would risk exposing them as sources."

President Trump's threat of "severe" repercussions if the Saudis are found to have killed journalist Jamal Khashoggi were met with more threats from the Saudi side, including from a media figure close to the royal family who warned of high oil prices and a shift of alliances.

The size of the AI sector in India is difficult to determine, given that a lot of AI applications are in intermediary phases of production. Globally, one popular means of measuring the size of AI sectors is by adding up private sector investment in AI start-ups. According to one estimate, total AI funding worldwide has increased from $862 million in 2012 to $6.4 billion in 2017.1 The Indian AI sector, too, has seen growth in this period, with a total of $150 million invested in more than 400 companies over the past five years.2 Most of these investments have come in the last two years, when investment nearly doubled from $44 million in 2016 to $77 million in 2017.3 In India, too, the government is spearheading investments in AI and other emerging technologies. In the latest budget, the government set aside $480 million for investment into emerging technologies including AI. This commitment could help put India on the map, as this outlay compares favorably to those of Australia, Canada, and the European Union.5

How big of a role do you see AI having in the cyber security industry in the next 5 to 10 years? Often, people are using the terms automation and AI interchangeably. But they are actually quite different concepts. Automation is taking a repeatable manual process and programming a machine or computer to do it more efficiently. This is not a new or transformative concept.

The biggest problem, or opportunity, for the current and many successive governments, is, and would be this - how to provide gainful employment to the millions of Indians entering the labour market every month? That one question has several corollaries to it. What role would automation play in all of this? What kind of jobs would be the first victims of automation? Is it wrong to expect manufacturing sector to provide jobs at a large scale now?

Paul Duan was working as a data scientist at Eventbrite in San Francisco by day, and volunteering at homeless shelters and soup kitchens by night. He realized one day that he wanted to use AI to help unemployed people find jobs--a core mission of his Paris, France-based nonprofit Bayes Impact. Bayes Impact uses data to build social services fit for a better future. "When you work at a soup kitchen, you serve a soup one by one to each individual, and it feels great," says Duan, "But then it gets really sad because you see that there are 50 people in line behind the person, and you know that behind the closed door of the shelter you have 10,000 more on the streets. So the one question that came to mind was, 'how can we impact people at the biggest scale?'"

Reliance on artificial intelligence (AI) to combat cybersecurity threats looks set to increase by several orders of magnitude over the next few years. A recent report from P&S Market Research suggests that the global AI cybersecurity market will reach US$18.1 billion by 2023. As the overall size of the attack surface continues to expand, it's simply not feasible for cybersecurity teams to defend against every threat without some additional help. AI's playing an important role in helping automate threat detection and response, which in turn, eases the burden on these teams. If we take a look at social engineering attacks such as spear phishing and business email compromise (BEC), they're extremely hard to detect.

It is designed to plug in to Metacorps, an experimental web app for annotating metaphor. As Metacorps users annotate metaphors, the system will use user annotations as training data. When the system is confident, it will suggest an identification and an annotation. Once approved by the user, this becomes more training data. This naturally allows for transfer learning, where the system can, with some known degree of reliability, classify one class of metaphor after only being trained on another class of metaphor. For example, in our metaphorical violence project, metaphors may be classified by the network they were observed on, the grammatical subject or object of the violence metaphor, or the violent word used (hit, attack, beat, etc.).

Spectral features of the empirical moment matrix constitute a resourceful tool for unveiling properties of a cloud of points, among which, density, support and latent structures. It is already well known that the empirical moment matrix encodes a great deal of subtle attributes of the underlying measure. Starting from this object as base of observations we combine ideas from statistics, real algebraic geometry, orthogonal polynomials and approximation theory for opening new insights relevant for Machine Learning (ML) problems with data supported on singular sets. Refined concepts and results from real algebraic geometry and approximation theory are empowering a simple tool (the empirical moment matrix) for the task of solving non-trivial questions in data analysis. We provide (1) theoretical support, (2) numerical experiments and, (3) connections to real world data as a validation of the stamina of the empirical moment matrix approach.