Fraym is using artificial intelligence and machine learning to help aid organizations in Africa and South Asia identify populations at risk due to Covid-19 using new geospatial visualizations. Fraym identifies high-risk populations and how to best communicate with them – making it an invaluable tool for more than 40 organizations and governments fighting the pandemic, including the Nigerian CDC, Kenyan presidential office, Zambian public health policymakers and aid organizations in Pakistan. Fraym has mapped communities based on concentrations of common transmission variables and then combined this with data from household surveys and remote sensing data, to then understand how these individuals consume news at a hyper-local level. The company is providing this information, which is at a 1-square kilometer level, for free to help fight the spread of Covid19. Since March 2020, Fraym has produced more than 300 COVID-19 related data layers in nearly 20 different countries.

The term artificial intelligence (AI) was coined 64 years ago at a scholarly conference. The AI field hasn't remained the theoretical province of computer scientists and mathematicians; it now is a pervasive part of everyday life. With a technology this powerful, it is critical to include the perspectives of all women, including those from underrepresented communities. AI applications -- based on algorithms -- are found in robotics, machine learning, natural language processing, machine vision, speech recognition and more. These applications are found in homes, vehicles and myriad other aspects of daily life.

We propose and study Collpasing Bandits, a new restless multi-armed bandit (RMAB) setting in which each arm follows a binary-state Markovian process with a special structure: when an arm is played, the state is fully observed, thus "collapsing" any uncertainty, but when an arm is passive, no observation is made, thus allowing uncertainty to evolve. The goal is to keep as many arms in the "good" state as possible by planning a limited budget of actions per round. Such Collapsing Bandits are natural models for many healthcare domains in which workers must simultaneously monitor patients and deliver interventions in a way that maximizes the health of their patient cohort. Our main contributions are as follows: (i) Building on the Whittle index technique for RMABs, we derive conditions under which the Collapsing Bandits problem is indexable. Our derivation hinges on novel conditions that characterize when the optimal policies may take the form of either "forward" or "reverse" threshold policies. (ii) We exploit the optimality of threshold policies to build fast algorithms for computing the Whittle index, including a closed-form. (iii) We evaluate our algorithm on several data distributions including data from a real-world healthcare task in which a worker must monitor and deliver interventions to maximize their patients' adherence to tuberculosis medication. Our algorithm achieves a 3-order-of-magnitude speedup compared to state-of-the-art RMAB techniques while achieving similar performance.

Predicting the behavior of surrounding traffic participants is crucial for advanced driver assistance systems and autonomous driving. Most researchers however do not consider contextual knowledge when predicting vehicle motion. Extending former studies, we investigate how predictions are affected by external conditions. To do so, we categorize different kinds of contextual information and provide a carefully chosen definition as well as examples for external conditions. More precisely, we investigate how a state-of-the-art approach for lateral motion prediction is influenced by one selected external condition, namely the traffic density. Our investigations demonstrate that this kind of information is highly relevant in order to improve the performance of prediction algorithms. Therefore, this study constitutes the first step towards the integration of such information into automated vehicles. Moreover, our motion prediction approach is evaluated based on the public highD data set showing a maneuver prediction performance with areas under the ROC curve above 97% and a median lateral prediction error of only 0.18m on a prediction horizon of 5s.

In September, Mohamed bin Zayed University for Artificial Intelligence (MBZUAI) will welcome its first batch of local and international students. UAE has been long encouraging the cultivation of future talent through knowledge and science. MBZUAI will set up master of science and PhD programs in core AI areas such as machine learning, computer vision and natural language processing. To compete with top AI programs around the world, especially those from North America, China and the UK, all students enrolled will be provided with full scholarships, salary, medical insurance and accommodation. The UAE has been putting great emphasis on education as one of the nation's key strategies, and well-known international educational programs include cooperation with NYU Abu Dhabi and BFSU Zayed Center for Arabic Language and Islamic Studies.

Secretary of State Mike Pompeo seized on a U.N. report confirming Iranian weapons were used to attack Saudi Arabia in September and were part of an arms shipment seized months ago off Yemen's coast; State Department correspondent Rich Edson reports. A fire and an explosion struck a centrifuge production plant above Iran's underground Natanz nuclear enrichment facility early Thursday, analysts said, one of the most-tightly guarded sites in all of the Islamic Republic after earlier acts of sabotage there. The Atomic Energy Organization of Iran sought to downplay the fire, calling it an "incident" that only affected an under-construction "industrial shed," spokesman Behrouz Kamalvandi said. However, both Kamalvandi and Iranian nuclear chief Ali Akbar Salehi rushed after the fire to Natanz, a facility earlier targeted by the Stuxnet computer virus and built underground to withstand enemy airstrikes. The fire threatened to rekindle wider tensions across the Middle East, similar to the escalation in January after a U.S. drone strike killed a top Iranian general in Baghdad and Tehran launched a retaliatory ballistic missile attack targeting American forces in Iraq. While offering no cause for Thursday's blaze, Iran's state-run IRNA news agency published a commentary addressing the possibility of sabotage by enemy nations such as Israel and the U.S. following other recent explosions in the country.

They may seem tiny and fragile, but mosquitoes can be extremely dangerous. Malaria has been a notoriously life-threatening disease for people of all ages which is spread by mosquitoes. More so because during the initial stages, the symptoms could easily be mistaken for fever, flu, or the common cold. But, in the advanced stages, it could wreak havoc by infecting and rupturing cell structure which could be potentially life-threatening. And if left untreated, it could even result in death.

Vaccines for COVID-19 are currently under clinical trials. These vaccines are crucial for eradicating the novel coronavirus. Despite the potential, there exist conspiracies related to vaccines online, which can lead to vaccination hesitancy and, thus, a longer-standing pandemic. We used a between-subjects study design (N=572 adults in the US and UK) to understand the public willingness towards vaccination against the novel coronavirus under various circumstances. Our survey findings suggest that people are more reluctant to vaccinate their children compared to themselves. Explicitly stating the high effectiveness of the vaccine against COVID-19 led to an increase in vaccine acceptance. Interestingly, our results do not indicate any meaningful variance due to the use of artificial intelligence (AI) in developing vaccines, if these systems are described to be in use alongside human researchers. We discuss the public's expectation of local governments in assuring the safety and effectiveness of a future COVID-19 vaccine.

A Dutch artist is using modern technology to create realistic photo-style portraits of famous figures only depicted in paint and sculpture. Bas Uterwijk, from Amsterdam, explained that he wanted to see if he could create realistic digital renderings of key faces in history, including Vincent Van Gogh and Napoleon. He also turned his talents to statues like Michelangelo's David and the Statue of Liberty. Bas uses Artbreeder, a'deep-learning' software which can create life-like images from scratch or based on a composite of different portraits. Bas Uterwijk, from Amsterdam, can create likenesses of famous historical figures using'deep-learning' technology.

MIT has had to take offline a giant dataset that taught AI systems to assign'racist and misogynistic labels' to people in images. The database, known as '80 Million Tiny Images', is a massive collection of photos with descriptive labels, used to teach machine learning models to identify images. But the system, developed at the US university, labelled women as'whores' and'bitches' and used other abhorrent terms against ethnic minorities. It also contained close-up pictures of female genitalia labelled with the C-word and other images with the labels'rape suspect' and'molester'. Images labelled with the slur'whore' ranged from a woman in a bikini to a photo of'a mother holding her baby with Santa', tech website the Register reported.