The Android operating system has been the most popular for smartphones and tablets since 2012. This popularity has led to a rapid raise of Android malware in recent years. The sophistication of Android malware obfuscation and detection avoidance methods have significantly improved, making many traditional malware detection methods obsolete. In this paper, we propose DL-Droid, a deep learning system to detect malicious Android applications through dynamic analysis using stateful input generation. Experiments performed with over 30,000 applications (benign and malware) on real devices are presented. Furthermore, experiments were also conducted to compare the detection performance and code coverage of the stateful input generation method with the commonly used stateless approach using the deep learning system. Our study reveals that DL-Droid can achieve up to 97.8% detection rate (with dynamic features only) and 99.6% detection rate (with dynamic + static features) respectively which outperforms traditional machine learning techniques. Furthermore, the results highlight the significance of enhanced input generation for dynamic analysis as DL-Droid with the state-based input generation is shown to outperform the existing state-of-the-art approaches.

Facility to open in early 2020 and focus on accelerating digital transformation in the industry, and upskilling the workforce with AI. Abu Dhabi, United Arab Emirates – Microsoft today announced that it will open an AI Centre of Excellence for Energy in the United Arab Emirates – a global first for the company – to empower organisations in the industry in accelerating digital transformation, equipping the workforce with AI skills, as well as collaborating on coalitions to address sustainability and safety challenges. The company revealed its plans at the Abu Dhabi International Petroleum Exhibition and Conference (ADIPEC) 2019, held under the patronage of His Highness Sheikh Khalifa bin Zayed Al Nahyan, President of the United Arab Emirates and Ruler of Abu Dhabi. Supported by partners that include ABB, Accenture, AVEVA, Baker Hughes, C3.ai, Emerson, Honeywell, Maana, Rockwell Automation, Schlumberger, and Sensia, the Microsoft AI Centre of Excellence is expected to open in early 2020. The centre will support organizations to accelerate their digital journeys and drive innovation through active engagements with leading technologies and industry partners, as well as equipping the workforce with necessary AI readiness towards closing the skills gaps and enhancing employability.

Newswire) VSBLTY Groupe Technologies Corp. (CSE: VSBY) (5VS.F) (VSBGF), a leading retail software and technology company, announced today that-in partnership with Onyx-Cognivas Pty.-it is launching two privately-led security deployments in South Africa to support community safety initiatives. The state-of-the-art security technology will protect two prominent high-rise residential apartment buildings in the upmarket Sandton area, a high income residential, financial and business suburb of Johannesburg with a population of 225,000. The rollout plan is to deploy this technology across several apartment blocks, a hotel and commercial properties in the precinct-with the objective of deploying a "private Smart City". In addition, advanced custom sensory applications are planned to be installed in a well-known petroleum group with convenience stores/service stations throughout South Africa. The announcement was made by Jay Hutton, VSBLTY co-founder and CEO, who said, "We are excited to provide complete Smart City-like security solutions in Sandton. This state-of-the-art technology uses the power of machine learning and computer vision."

CAIRO - 21 November 2019: The Cabinet, during its meeting on Thursday under Prime Minister Mostafa Madbouli, approved a draft resolution on establishing a national council for artificial intelligence. The national artificial intelligence council, which follows the Cabinet, will be chaired by the communications and information technology minister and group a number of ministers and heads of several bodies concerned. The new national body will be responsible for outlining the national strategy for artificial intelligence and overseeing its implementation in a way that copes up with the international developments in this field. The council will be authorized to cooperate with the related regional and international bodies as well as to select the best artificial intelligence applications that could help offer safe, sustainable and smart services. During the meeting, the Cabinet approved authorizing the ICT minister to contract and sign agreements with Microsoft, ESRI, VMware and Teradata on the behalf of the government to be self-funded by the ministry during the years 2019/2020, 2020/2021, 2021/2022 and 2022/2023.

Environmental conflicts have emerged as major issues that deeply affect the socio-economic state of a region and/or an entire nation. These conflicts are related to natural resources, land, wildlife, supply chains etc. The crises are widespread around the globe and it is increasing rapidly. According to the Environmental Justice Atlas, India has the most number of environmental conflicts, followed by Colombia and Nigeria. For instance, approximately 66% of all civil cases in the Supreme court of India are related to the land disputes for more than 2.5 million hectares of land.

Timnit Gebru is a research scientist at Google on the ethical A.I. team and a co-founder of Black in AI, which promotes people of color in the field. Dr. Gebru has been instrumental in moving a major international A.I. conference, the International Conference on Learning Representations, to Ethiopia next year after more than half of the Black in AI speakers could not get visas to Canada for a conference in 2018. She talked about the foundational origins of bias and the larger challenge of changing the scientific culture. Their comments have been edited and condensed. You could mean bias in the sense of racial bias, gender bias.

We can already see the potential for artificial intelligence (AI) in international development: the seemingly endless possibilities to enhance productivity and innovation across healthcare, agriculture, education, transportation, and governance. Yet it is also becoming abundantly clear that AI could have negative repercussions as well, particularly in countries with weaker institutional capacity and legal protections. AI has the potential to threaten democratic processes, employment, human rights and -- because of the weaponization of AI tools -- privacy, policing, and defense. Apart from these potential benefits and threats, the transformative potential of AI for both good and harm will be magnified in the Global South, where existing gender and socio-economic inequalities could either be tempered or exacerbated. Given the opportunities and potential consequences of new automation and mechanization techniques and advanced analysis through machine learning and neural networks, IDRC is investing in applied research across a number of domains to advance the public good with the use of artificial intelligence for development (AI4D).

Earlier this year new health tech start-up EQL unveiled its debut product at the Google Campus in London to an audience of industry leaders in the healthcare and insurance markets. But how did they turn a dream into reality? Improving healthcare through the use of smart technology had long been a passion for EQL founders Jason Ward and Pete Grinbergs. Jason had seen his mum, a nurse and his step-dad, a GP, struggle with the inefficiency in the NHS and work hard to ensure that their patients received the best care. He started life working in finance in the City and in 2015 set up a digital primary care start-up in 2015 which sadly didn't make the grade.

Texts like news, encyclopedias, and some social media strive for objectivity. Yet bias in the form of inappropriate subjectivity - introducing attitudes via framing, presupposing truth, and casting doubt - remains ubiquitous. This kind of bias erodes our collective trust and fuels social conflict. To address this issue, we introduce a novel testbed for natural language generation: automatically bringing inappropriately subjective text into a neutral point of view ("neutralizing" biased text). We also offer the first parallel corpus of biased language. The corpus contains 180,000 sentence pairs and originates from Wikipedia edits that removed various framings, presuppositions, and attitudes from biased sentences. Last, we propose two strong encoder-decoder baselines for the task. A straightforward yet opaque CONCURRENT system uses a BERT encoder to identify subjective words as part of the generation process. An interpretable and controllable MODULAR algorithm separates these steps, using (1) a BERT-based classifier to identify problematic words and (2) a novel join embedding through which the classifier can edit the hidden states of the encoder. Large-scale human evaluation across four domains (encyclopedias, news headlines, books, and political speeches) suggests that these algorithms are a first step towards the automatic identification and reduction of bias.

Knowledge graph embedding, which aims to represent entities and relations as low dimensional vectors (or matrices, tensors, etc.), has been shown to be a powerful technique for predicting missing links in knowledge graphs. Existing knowledge graph embedding models mainly focus on modeling relation patterns such as symmetry/antisymmetry, inversion, and composition. However, many existing approaches fail to model semantic hierarchies, which are common in real-world applications. To address this challenge, we propose a novel knowledge graph embedding model--namely, Hierarchy-A ware Knowledge Graph E mbedding (HAKE)-- which maps entities into the polar coordinate system. HAKE is inspired by the fact that concentric circles in the polar coordinate system can naturally reflect the hierarchy. Specifically, the radial coordinate aims to model entities at different levels of the hierarchy, and entities with smaller radii are expected to be at higher levels; the angular coordinate aims to distinguish entities at the same level of the hierarchy, and these entities are expected to have roughly the same radii but different angles. Experiments demonstrate that HAKE can effectively model the semantic hierarchies in knowledge graphs, and significantly outperforms existing state-of-the-art methods on benchmark datasets for the link prediction task. 1 Introduction Knowledge graphs are usually collections of factual triples--(head entity, relation, tail entity), which represent human knowledge in a structured way. In the past few years, we have witnessed the great achievement of knowledge graphs in many areas, such as natural language processing (Zhang et al. 2019), question answering (Huang et al. 2019), and recommendation systems (Wang et al. 2018). Although commonly used knowledge graphs contain billions of triples, they still suffer from the incompleteness problem that a lot of valid triples are missing, as it is impractical to find all valid triples manually. Therefore, knowledge graph completion, also known as link prediction in knowledge graphs, has attracted much attention recently. Link prediction aims to automatically predict missing links between entities based on known links. It is a challenging task as we Equal contribution. Inspired by word embeddings (Mikolov et al. 2013) that can well capture semantic meaning of words, researchers turn to distributed representations of knowledge graphs (aka, knowledge graph embeddings) to deal with the link prediction problem.