Speaking at the Abu Dhabi International Petroleum Exhibition Conference (ADIPEC) on Wednesday, Omar Saleh said technology disruptions over the past three years had been a "wake-up call" for all oil and gas firms.He said AI would be of "massive importance" over the next to five to 10 years, before adding that of any technology, AI would also have the most impact on the oil and gas sector overall.The U.S. shale revolution paved the way for a three-year oil price downturn that sent crude spiraling from more than $100 a barrel in 2014 to about $60 today. That has piled pressure on the oil-dependent economies of OPEC nations and forced a round of production cuts this year. On Tuesday, Baker Hughes GE CEO Lorenzo Simonelli said " " in the oil and gas industry should be viewed positively. Correction: This story has been updated to reflect that Omar Saleh believes AI will have the greatest technological impact on the oil and gas industry over the coming years. Speaking at the Abu Dhabi International Petroleum Exhibition Conference (ADIPEC) on Wednesday, Omar Saleh said technology disruptions over the past three years had been a "wake-up call" for all oil and gas firms.

The Libyan National Army has been battling ISIS in the cities of Sirte and Benghazi. The U.S. military has launched airstrikes this month in Yemen, Somalia, Iraq, Syria, Afghanistan and Friday, for the first time since September, in Libya. According to a defense official, the drone strike in the desert of central Libya Friday killed "several" ISIS militants in a sign the Pentagon may be ramping up pressure on terror groups in Africa. The most recent strike comes a year after the military launched nearly 500 airstrikes against ISIS in the coastal city of Sirte, located halfway between Tripoli and Benghazi. The September strike killed 17 ISIS fighters.

We describe a method to identify poor households in data-scarce countries by leveraging information contained in nationally representative household surveys. It employs standard statistical learning techniques---cross-validation and parameter regularization---which together reduce the extent to which the model is over-fitted to match the idiosyncracies of observed survey data. The automated framework satisfies three important constraints of this development setting: i) The prediction model uses at most ten questions, which limits the costs of data collection; ii) No computation beyond simple arithmetic is needed to calculate the probability that a given household is poor, immediately after data on the ten indicators is collected; and iii) One specification of the model (i.e. one scorecard) is used to predict poverty throughout a country that may be characterized by significant sub-national differences. Using survey data from Zambia, the model's out-of-sample predictions distinguish poor households from non-poor households using information contained in ten questions.

Hamas has blamed the Israeli national intelligence agency Mossad for the assassination of one of its Tunisian members after conducting an 11-month-long investigation. The Palestinian group said Mohammed al-Zawari, a commander of its armed wing the Qassam Brigades since 2006, was fatally shot outside his home multiple times while in his car near Sfax, 270km southeast of Tunis, on December 15, 2016. Hamas had set up an investigative committee in the immediate aftermath of the assassination. Speaking at a press conference in Beirut on Thursday, Mohammed Nazzal, Hamas politburo member, called the Mossad operation a "terrorist act". "Mossad is officially accused of being behind the assassination, which is not only a terrorist act, but a violation of state sovereignty," he said.

Artificial intelligence (AI) poses the greatest threat to the oil and gas industry over the next five to 10 years, according to Microsoft's oil and gas director for the Middle East and Africa.

'A stable bright light, larger than anything practical shined into my room on the second floor, not making any noise; it disappeared.' It's one of nearly 60,000 unsettling stories revealed in a new map of the contiguous United States, compiling UFO sightings from every state, dating back to 1995. While these mysterious encounters may largely have slipped out of the public eye after the Cold War-era UFO craze died down, the map shows reports have steadily grown in the last two decades, hitting a mid-summer peak each year. The map shows these reports are concentrated in major cities and dense population hubs, making places like New York and the surrounding metropolitan area hotspots for UFO sightings, along with southern and central California. The new map of reported UFO sightings in the US was created by Data Solutions Engineer Adam Crahen of the Data Duo, using data from Kaggle UFO sightings. There's little doubt that the internet has played a role in the growth of UFO reports in recent years, though most can be explained by natural or human-caused phenomena.

Wednesday's U.S. military statement says the airstrike was carried out Tuesday evening about 60 miles (96 kilometers) northwest of the capital, Mogadishu, and occurred in coordination with Somalia's government.

It also received funding from 83North, Giza and a new investor, Vintage Investment Partners. To date, Logz.io -- which develops artificial intelligence technologies to help companies monitor their networks -- has raised $47 million.

The use of covariance kernels is ubiquitous in the field of spatial statistics. Kernels allow data to be mapped into high-dimensional feature spaces and can thus extend simple linear additive methods to nonlinear methods with higher order interactions. However, until recently, there has been a strong reliance on a limited class of stationary kernels such as the Matern or squared exponential, limiting the expressiveness of these modelling approaches. Recent machine learning research has focused on spectral representations to model arbitrary stationary kernels and introduced more general representations that include classes of nonstationary kernels. In this paper, we exploit the connections between Fourier feature representations, Gaussian processes and neural networks to generalise previous approaches and develop a simple and efficient framework to learn arbitrarily complex nonstationary kernel functions directly from the data, while taking care to avoid overfitting using state-of-the-art methods from deep learning. We highlight the very broad array of kernel classes that could be created within this framework. We apply this to a time series dataset and a remote sensing problem involving land surface temperature in Eastern Africa. We show that without increasing the computational or storage complexity, nonstationary kernels can be used to improve generalisation performance and provide more interpretable results.

Magda El Zarki recalls repeatedly telling her children to stop playing video games and enjoy the outdoors. She laughs at the memory now. A visit to Ghana in 2010 inspired the UC Irvine computer science professor to try her hand at creating virtual reality spaces and later computer games. She and Patricia Seed, a UC Irvine history professor, and Jessica Kernan, an industry professional and a staff member at the college's Institute for Virtual Environments and Computer Games, developed the computer game "Sankofa." Set in 18th-century Ghana, then known as Asante, the storyline begins when a mother sends her daughter to gather yams from the market.