The Sharjah City Municipality announced its partnership with digital powerhouse Evoteq, an innovative artificial intelligence solution that will enable a driver to book parking through their phone. This initiative will manifest the ability of the AI to help ease the parking dilemmas in Sharjah, as part of their agreement, both parties will be researching for smart transport platform solutions for driver behavior, traffic congestion, and parking. Jihad Tayara, CEO of Evoteq, said, "We are honoured to partner with the Sharjah City Municipality to provide its leading expertise in digital transformation and new ICT technology. As a trusted partner, we are developing solutions that will establish Sharjah as a leading digital economy and smart city." When fully digitize, "Sharjah Smart Parking" will allow car owners and drivers to identify a reserve space in censored parking lots through their phones.

Amgen's drug discovery group is a few blocks beyond that. Until recently, Barzilay, one of the world's leading researchers in artificial intelligence, hadn't given much thought to these nearby buildings full of chemists and biologists. But as AI and machine learning began to perform ever more impressive feats in image recognition and language comprehension, she began to wonder: could it also transform the task of finding new drugs? The problem is that human researchers can explore only a tiny slice of what is possible. It's estimated that there are as many as 1060 potentially drug-like molecules--more than the number of atoms in the solar system. But traversing seemingly unlimited possibilities is what machine learning is good at. Trained on large databases of existing molecules and their properties, the programs can explore all possible related molecules. Drug discovery is a hugely expensive and often frustrating process.

The three-body problem is a special case of the n-body problem. Unlike two-body problems, no general closed-form solution exists. However, researchers from the University Of Edinburgh and the University of Cambridge made an attempt to solve this with the help of deep learning. The 3 body problem has been long-standing as one of the most unsolved significant ones so far in the scientific community. Significant because, predicting where a certain object will end up in future, has many applications.

SHANGHAI – Panasonic Corp. will begin a business developing housing for the elderly next spring in China, featuring houses equipped with health care-related home appliances and nursing care devices, company sources said Wednesday. Panasonic will make the new housing business a pillar of its new operations in China where society is rapidly aging similarly to Japan and the market for businesses aimed at the elderly is expanding. The manufacturer will create a "Panasonic Town" with a total of 800 houses in Jiangsu. The houses will be equipped with home appliances and devices using artificial intelligence and "internet of things" technologies, the sources said. Panasonic plans to start building houses in Yixing in Jiangsu Province in March next year and sell them as early as March 2021 by collaborating with major Chinese health care company Yada International Holdings Ltd., the sources said.

As Japan's construction firms are squeezed by the tightest labor market since the 1970s and a rapidly aging population, they are pouring investment into technology -- and providing unexpected support to an economy reeling from the bitter U.S.-China trade war. The industry sees artificial intelligence and robots -- which can scurry around building sites day and night, preparing equipment and moving materials for the next day's construction -- as a way to future-proof and close the labor gap. But a side effect is that one of the country's least-productive sectors is bolstering capital expenditures even as the world's third-largest economy flirts with recession amid a global growth slowdown. Construction company Shimizu Corp., which spent about ¥3 billion ($27.7 million) on robots over three years, is a case in point. Equipped with state-of-the-art AI, cameras and sensors, the machines handle everything from transporting building materials and welding steel to installing ceilings.

Prescient are the entrepreneurs who predicted data would become the new oil, like Ali Ghodsi, Andy Konwinski, Ion Stoica, Matei Zaharia, Patrick Wendell, Reynold Xin, and Scott Shenker. They're the cofounders of Databricks, a San Francisco-based company that provides a suite of enterprise-focused scalable data science and data engineering tools. Since 2013, the year Databricks opened for business, it's had no trouble attracting customers. But this week kicked into high gear the company's uninterrupted march toward market domination. Databricks this morning announced that it's closed a $400 million series F fundraising round led by Andreessen Horowitz with participation from Microsoft, Alkeon Capital Management, BlackRock, Coatue Management, Dragoneer Investment Group, Geodesic, Green Bay Ventures, New Enterprise Associates, T. Rowe Price, and Tiger Global Management.

Dealing with misinformation in the digital age is a complex problem. Not only does misinformation have to be identified, tagged, and corrected, but the intent of those responsible for making the claim should also be distinguished. A person may unknowingly spread misinformation, or just be giving their opinion on an issue even though it is later reported as fact. Recently, a team of AI researchers and engineers at Dartmouth created a framework that can be used to derive opinion from "fake news" reports. As ScienceDaily reports, the Dartmouth team's study was recently published in the Journal of Experimental & Theoretical Artificial Intelligence.

When it comes to using artificial intelligence (AI) for credit-card fraud management, the benefits are more than meets the eye. Yes, AI-powered detection systems spot fraud more quickly and help contain losses. But the systems also put a new spin on fraud for credit card providers: Real-time fraud detection helps inspire customer confidence and boost loyalty. Call it the upside of fraud. According to at least one study, organizations with a formalized program in place to monitor and prevent fraud dramatically improve their customer satisfaction and retention rates.

Editor's Note: Get caught up in minutes with our speedy summary of today's must-read news stories and expert opinions that moved the precious metals and financial markets. The Australian government is setting up two mining research centres in partnership with universities and commercial supporters, according to an announcement made on Tuesday. The centers will be based in Sydney and Adelaide. The Australian government said research activity at the University of Sydney "...will focus on data analytics related to the long-term impact of resource use on Australia's economy, society and environment. It will help develop the necessary data science skills for Australia's resource industries to make the best possible evidence-based decisions when using our natural resources." The University of Adelaide will focus on advanced sensors and data analytics.

Urban traffic roughly follows a periodic pattern associated with the typical "9 to 5" work schedule. However, when an accident happens, traffic patterns are disrupted. Designing accurate traffic flow models, for use during accidents, is a major challenge for traffic engineers, who must adapt to unforeseen traffic scenarios in real time. A team of Lawrence Berkeley National Lab computer scientists are working with the California Department of Transportation (Caltrans) to use high performance computing (HPC) and machine learning to help improve Caltrans' real-time decision making when incidents occur. The research was done in conjunction with California Partners for Advanced Transportation Technology (PATH), part of UC Berkeley's Institute for Transportation Studies (ITS), and Connected Corridors, a collaborative program to research, develop, and test an Integrated Corridor Management approach to managing transportation corridors in California.