Wrinkles, crow's feet and laughter lines could become a thing of the past thanks to 3D modelling. A computer programme has developed that looks at how the upper layers of the skin fold to form wrinkles. It found that drier skin plays a major role in the development of the unwanted signs of ageing. By looking at how the wrinkles form in the first place, researchers hope to develop treatments to remove the unwanted creases. 'Besides its critical physiological functions as a biochemical barrier, this very thin layer plays a key role in determining the characteristics of skin micro-wrinkles, even in younger people,' said Dr Limbert.

Eliminating poverty is the number one goal of most countries around the world. However, the process of going around rural areas and manually tracking census data is time consuming, labor intensive and expensive. Considering that, a group of researchers at Stanford have pioneered an approach that combines machine learning with satellite images to make predicting poverty quicker, easier and less expensive. Using this machine learning algorithm, the model is able to predict per capita consumption expenditure of a particular location when provided with it's satellite images. The algorithm runs through millions of images of rural regions throughout the world. It then compares the presence of light in a region during the day and at night to predict it's economic activity.

Companies generate massive amounts of data, and this will rise exponentially as new computers and sensors are connected to the system. This huge amount of data is unusable if companies do not know how to manage it and transform it effectively. Multinational computer technology corporation Oracle forecasts 2018 will be the year when laggards will finally make the move to cloud, late adopters of big data will see immense benefits straight away, and those using artificial intelligence (AI) will drive the most insights. Samina Rizwan, Oracle senior director for big data and analytics for Middle East and Africa, says Oracle has been in the business of big data since before it became the buzzword it is today. She says the conversation around big data should be expanded to include analytics, AI, the Internet of things (IOT) and machine learning (ML), all encapsulated in the cloud.

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. In late September, Egyptian authorities began a crackdown against the country's queer communities after fans of Mashrou' Leila, an outspoken Lebanese indie rock group with an openly gay band member, displayed a rainbow flag at the group's concert in Cairo. The government responded quickly in what some activists called the worst campaign against LGBTQIA Egyptians in decades. Security forces arrested more than 85 individuals on a range of charges, including "habitual debauchery." Officials convicted at least 16 and issued sentences ranging from six months to six years in prison (though a handful were later released).

Neural Network Accelerators (NNA) may have become a must-have block in high-end mobile processors. Huawei Kirin 970, Samsung Exynos 9810, and Qualcomm Snapdragon 845 (via its Hexagon DSP) processors all come with NNA or NPU (Neural Processing Unit) to speed up tasks and comsume less power for tasks related to artificial intelligence / machine learning. Mediatek has also jumped on the bandwagon with Helio P60 chipset featuring four Cortex A73 cores, four Cortex A53 cores, an Arm Mali-G72MP3 GPU and a multi-core mobile APU (AI Processing Unit) leveraging the company's NeuroPilot AI technology. Helio P60 is said to deliver 70% higher performance, 25% power savings in heavy duty games, and overall power savings of up to 12% compared to the previous generation MediaTek Helio P23 series chipset. The APU offers double the power efficiency of the GPU for AI processing.

In this paper, we study several classes of satisfiability preserving assignments to the constraint satisfaction problem (CSP). In particular, we consider fixable, autark and satisfying assignments. Since it is in general NP-hard to find a nontrivial (i.e., nonempty) satisfiability preserving assignment, we introduce linear satisfiability preserving assignments, which are defined by polyhedral cones in an associated vector space. The vector space is obtained by the identification, introduced by Kullmann, of assignments with real vectors. We consider arbitrary polyhedral cones, where only restricted classes of cones for autark assignments are considered in the literature. We reveal that cones in certain classes are maximal as a convex subset of the set of the associated vectors, which can be regarded as extensions of Kullmann's results for autark assignments of CNFs. As algorithmic results, we present a pseudo-polynomial time algorithm that computes a linear fixable assignment for a given integer linear system, which implies the well known pseudo-polynomial solvability for integer linear systems such as two-variable-per-inequality (TVPI), Horn and q-Horn systems.

Like Hollywood, the games industry is facing a moment of self-reflection. For too long it has told the same stories, centring on the same white, male heroes. Game creators are finally examining the lack of diversity in their stories, but so far, representation of black people has been timid and predictable. With the number of women in the UK industry at just 14% and BAME representation at 4%, the narrative gatekeepers in games are primarily white men. If they are to find a broader range of stories, they need to rethink their representations of black people.

Poachers are normally active at night. While tools such as infrared cameras are used to monitor living organisms, since poachers and animals they are hunting both give off heat, it is time-consuming and challenging to monitor infrared video streams for poachers all night. Thus a team of computer scientists led by USC Viterbi School of Engineering PhD student Elizabeth Bondi in Professor Milind Tambe's lab, labeled 180,000 humans and animals in infrared videos using a labeling tool they developed to expedite the process. The researchers used these labeled images and leveraged an existing deep learning algorithm known as Faster RCNN that they modified, to teach a computer to automatically distinguish infrared images of humans from those infrared images of animals. The challenge then was to deploy this algorithm to spot poachers in near real time using the laptop computers at base stations in the field, where footage is streamed from the drones that are being used to patrol national parks in Zimbabwe and Malawi.

Johannesburg - Like many global startup companies OrderIn began with limited resources, CEO and founder of the company Dinesh Patel told Fin24. "The company was started in garage. We went to a hardware store and used doors as desks. We looked at how successful startup companies started and were inspired. This taught us lessons on how we think and how to operate our business," Patel said.

Despite efforts to tackle corruption around the world, progress is still frustratingly slow, according to the latest report from Transparency International. Its annual Corruption Perception index reveals some alarming trends. It shows public service corruption is still a huge problem for two-thirds of the world's economies. The report uses a scale of zero to 100 to rank countries: zero is highly corrupt and 100 is very clean. New Zealand comes out on top but with a score of 89.