Recently, a researcher showed that he could create Deepfake text with artificial intelligence that is so real that US government officials did not know it was computer-generated, and accepted it as legitimate public comment. He then did a Turing Test to see if humans trained on spotting natural language processing could tell the difference between bot and human text. They were right about 50% of the time – essentially as good as flipping a coin. While reading the academic paper, I thought to myself, "Could machine learning to do the same for international development?" We have so much nuance, arcane language, and peculiarities, I didn't think it was possible.

Despite huge advancements and progress in the world of global health over the past decades, many middle and low-income countries are still falling behind, unable to reach their sustainable development goals. This, in turn, is creating an urgency to prioritize wellbeing, and AI holds enormous promise in transforming the provision of healthcare in resource strained environments. The Artificial Intelligence in Global Health report, funded by the USAID's Center for Innovation and Impact, Rockefeller Foundation, and the Bill & Melinda Gates Foundation, outlined 27 cases of AI in global healthcare, and the massive potential it holds for drastically improving health in LEDC's. The use of AI was split into four key areas - population health, patient and front line health worker virtual assistants, and physician clinical decision support. Not only does the report provide solutions that could improve the access, quality, and effectiveness of global healthcare, but it also takes into account the current maturity of AI systems and the feasibility of these solutions.

WASHINGTON – U.S. President Donald Trump on Thursday said he supported expanding the North American Treaty Organization to include Middle Eastern nations, as the United States seeks to limit its troop footprint globally. "I think that NATO should be expanded and we should include the Middle East, absolutely," Trump told reporters at the White House. Trump proposed increased NATO involvement in the Middle East on Wednesday, when he addressed the Iranian strikes against U.S. troops in Iraq, carried out in retaliation for a U.S. drone strike that killed a top Iranian military commander. The military leader, Qassem Soleimani, played a major role in the fight against Islamic State militants in the region. Trump said Islamic State presented an international problem that other countries should help address. "We can come home, largely come home and use NATO," Trump said.

WASHINGTON – The U.S. House of Representatives voted Thursday to limit President Donald Trump's authority to strike Iran, a mostly symbolic move Democrats say defends Congress's constitutional powers but Republicans say endangers national security. The resolution was adopted on a 224-194 vote, as tensions in the Middle East remain high after a U.S. drone strike killed Iranian general Qassem Soleimani. Iran retaliated with missiles striking an Iraqi base used by U.S. troops late Tuesday, without casualties, leaving uncertainty about future hostilities. With Thursday's resolution, the House is saying that Congress should be consulted before the conflict with Iran escalates. The Senate now can either consider the House-passed measure or move forward with a different version introduced by Sen. Tim Kaine, a Democrat from Virginia.

In this research, an extensive literature review was performed on the recent developments of the ambulance routing problem (ARP) and ambulance location problem (ALP). Both are respective modifications of the vehicle routing problem (VRP) and maximum covering problem (MCP), with modifications to objective functions and constraints. Although alike, a key distinction is emergency service systems (EMS) are considered critical and the optimization of these has become all the more important as a result. Similar to their parent problems, these are NP-hard and must resort to approximations if the space size is too large. Much of the current work has simply been on modifying existing systems through simulation to achieve a more acceptable result. There has been attempts towards using meta-heuristics, though practical experimentation is lacking when compared to VRP or MCP. The contributions of this work are a comprehensive survey of current methodologies, summarized models, and suggested future improvements.

The entropy models have been recently adopted in many studies to evaluate the distribution of the shear stress in circular channels. However, the uncertainty in their predictions and their reliability remains an open question. We present a novel method to evaluate the uncertainty of four popular entropy models, including Shannon, Shannon-Power Low (PL), Tsallis, and Renyi, in shear stress estimation in circular channels. The Bayesian Monte-Carlo (BMC) uncertainty method is simplified considering a 95% Confidence Bound (CB). We developed a new statistic index called as FREEopt-based OCB (FOCB) using the statistical indices Forecasting Range of Error Estimation (FREE) and the percentage of observed data in the CB (Nin), which integrates their combined effect. The Shannon and Shannon PL entropies had close values of the FOCB equal to 8.781 and 9.808, respectively, had the highest certainty in the calculation of shear stress values in circular channels followed by traditional uniform flow shear stress and Tsallis models with close values of 14.491 and 14.895, respectively. However, Renyi entropy with much higher values of FOCB equal to 57.726 has less certainty in the estimation of shear stress than other models. Using the presented results in this study, the amount of confidence in entropy methods in the calculation of shear stress to design and implement different types of open channels and their stability is determined.

The connectivity structure of graphs is typically related to the attributes of the nodes. In social networks for example, the probability of a friendship between two people depends on their attributes, such as their age, address, and hobbies. The connectivity of a graph can thus possibly be understood in terms of patterns of the form 'the subgroup of individuals with properties X are often (or rarely) friends with individuals in another subgroup with properties Y'. Such rules present potentially actionable and generalizable insights into the graph. We present a method that finds pairs of node subgroups between which the edge density is interestingly high or low, using an information-theoretic definition of interestingness. This interestingness is quantified subjectively, to contrast with prior information an analyst may have about the graph. This view immediately enables iterative mining of such patterns. Our work generalizes prior work on dense subgraph mining (i.e. subgraphs induced by a single subgroup). Moreover, not only is the proposed method more general, we also demonstrate considerable practical advantages for the single subgroup special case.

Can effective international governance for artificial intelligence remain fragmented, or is there a need for a centralised international organisation for AI? We draw on the history of other international regimes to identify advantages and disadvantages in centralising AI governance. Some considerations, such as efficiency and political power, speak in favour of centralisation. Conversely, the risk of creating a slow and brittle institution speaks against it, as does the difficulty in securing participation while creating stringent rules. Other considerations depend on the specific design of a centralised institution. A well-designed body may be able to deter forum shopping and ensure policy coordination. However, forum shopping can be beneficial and a fragmented landscape of institutions can be self-organising. Centralisation entails trade-offs and the details matter. We conclude with two core recommendations. First, the outcome will depend on the exact design of a central institution. A well-designed centralised regime covering a set of coherent issues could be beneficial. But locking-in an inadequate structure may pose a fate worse than fragmentation. Second, for now fragmentation will likely persist. This should be closely monitored to see if it is self-organising or simply inadequate.

In a televised address to the nation from the White House, Trump emphasized there were "no Americans harmed" in the ballistic missile salvo aimed at two bases on Wednesday. While he promised to immediately impose "punishing" new economic sanctions on Tehran, Trump welcomed signs the Islamic republic "appears to be standing down" in the tit-for-tat confrontation. The comments cooled what threatened to become an uncontrolled boiling over of tensions after Trump ordered the killing last Friday of a top Iranian general, Qassem Soleimani. The president, facing both an impeachment trial in Congress and a tough re-election in November, defended his targeting of a man seen by many as Iran's second-most-influential official. Soleimani, a national hero at home, was "the world's top terrorist" and "should have been terminated long ago," Trump said.