Erratic oil prices in recent years have made economic diversification essential, and AI is an alternate solution. Having made an early start, these states are positioned to become a key player in AI technology. Dividing the Middle East into four main regions, first, the UAE, second, Saudi Arabia, the GCC 4 comprising of Bahrain, Kuwait, Oman and Qatar on third and lastly Egypt, a PWC research expects the Arab states to accrue two percent of the total global benefits in the next ten years. Projected to mark the highest gains, the UAE would get nearly 14 percent on its GDP in 2030 while the kingdom of Saudi Arabia should make over US $135 billion by that time as well, this being nearly 12.4 percent of its GDP. Assigning large budgets for the speedy implementation of AI, these two GCC states have made a major impact.

The company's app and platform lets wineries and wine producers create, manage, and market an augmented reality experience for their own labels via a smartphone app. Now, says the company, 524 wineries from across the world are participating in the trial and accessing the marketing potential of a marriage of artificial intelligence and augmented reality. "I don't believe anything like this has been done to this level before – bringing together artificial intelligence, augmented reality, clever technology, 500 different wineries with different visuals and branding, as well as different languages," says app creator and Winerytale founder Dave Chaffey. "This platform is purpose-built for mass adoption and accessibility to any winery wanting to take advantage of a brand marketing and sales future that will undeniably involve augmented reality." The technology is designed to work on any wine label, using artificial intelligence to scan and recognize labels, and augmented reality to showcase the wine's backstory by beaming it from an imaginary space inside and outside of the bottle.

Michael Kwet is a Visiting Fellow of the Information Society Project at Yale Law School. He is the author of Digital Colonialism: US Empire and the New Imperialism in the Global South, and hosts the Tech Empire podcast. "Beggars" and "vagrants" are not welcome in Parkhurst, South Africa, a mostly white, middle-class suburb of about 5,000 on the outskirts of Johannesburg's inner city. Criminals are on the prowl, residents warn, and they threaten their neighborhood security. To combat crime, the locals came up with a solution: place CCTV surveillance cameras everywhere. However, these are not the camera networks of times past. Thanks to advancements in machine learning and AI, CCTV systems are now equipped with sophisticated video analytics that can track a wide range of behaviors, objects, and patterns, in addition to individual faces. Armed with powerful new tech, communities of color can be watched, flagged, policed, and intimidated into submission. I've spent the past several years studying the video surveillance industry in South Africa. During that time, a private corporation called Vumacam has been quietly assembling a "smart" CCTV surveillance network in the suburbs of Johannesburg. Earlier this year, the company announced it would blanket Joburg with 15,000 cameras.

Processes are a crucial artefact in organizations, since they coordinate the execution of activities so that products and services are provided. The use of models to analyse the underlying processes is a well-known practice. However, due to the complexity and continuous evolution of their processes, organizations need an effective way of analysing the relation between processes and models. Conformance checking techniques asses the suitability of a process model in representing an underlying process, observed through a collection of real executions. One important metric in conformance checking is to asses the precision of the model with respect to the observed executions, i.e., characterize the ability of the model to produce behavior unrelated to the one observed. In this paper we present the notion of anti-alignment as a concept to help unveiling runs in the model that may deviate significantly from the observed behavior. Using anti-alignments, a new metric for precision is proposed. In contrast to existing metrics, anti-alignment based precision metrics satisfy most of the required axioms highlighted in a recent publication. Moreover, a complexity analysis of the problem of computing anti-alignments is provided, which sheds light into the practicability of using anti-alignment to estimate precision. Experiments are provided that witness the validity of the concepts introduced in this paper.

Hierarchical Task Network (HTN) planning is showing its power in real-world planning. Although domain experts have partial hierarchical domain knowledge, it is time-consuming to specify all HTN methods, leaving them incomplete. On the other hand, traditional HTN learning approaches focus only on declarative goals, omitting the hierarchical domain knowledge. In this paper, we propose a novel learning framework to refine HTN methods via task insertion with completely preserving the original methods. As it is difficult to identify incomplete methods without designating declarative goals for compound tasks, we introduce the notion of prioritized preference to capture the incompleteness possibility of methods. Specifically, the framework first computes the preferred completion profile w.r .t.the prioritized preference to refine the incomplete methods. Then it finds the minimal set of refined methods via a method substitution operation. Experimental analysis demonstrates that our approach is effective, especially in solving new HTN planning instances.

Data collection in economically constrained countries often necessitates using approximate and biased measurements due to the low-cost of the sensors used. This leads to potentially invalid predictions and poor policies or decision making. This is especially an issue if methods from resource-rich regions are applied without handling these additional constraints. In this paper we show, through the use of an air pollution network example, how using probabilistic machine learning can mitigate some of the technical constraints. Specifically we experiment with modelling the calibration for individual sensors as either distributions or Gaussian processes over time, and discuss the wider issues around the decision process.

Titled "Beginners' Artificial Intelligence and Python Programming", the book was written by the convener of Data Science Nigeria, Olubayo Adekanmbi, …

Fox News Flash top headlines for Nov. 27 are here. Check out what's clicking on Foxnews.com A Georgia man is accused of scamming a Virginia woman out of more than $6.5 million after wooing her into a romantic relationship through an online dating site. Nnamdi Marcellus MgBodile, 35, from Marietta, Georgia, was charged with 20 counts of bank fraud, money laundering and conspiracy to commit bank fraud, according to a Justice Department press release on Wednesday. MgBodile and others also allegedly tried to scam a company out of $350,000 using an email scheme, according to the DOJ.

Black Friday or Cyber Monday, take your pick; it's that time of year again. If you're in the market for a smartphone -- and it's statistically likely you are, given that 403.5 million handsets shipped last holiday season -- there's no better month to seek out promotions, discounts, and limited-time deals on new devices. Samsung is hosting a sale on Galaxy phones including the Galaxy S10e, S10, S10 Plus, and S10 5G, and OnePlus recently knocked $150 off the price of the OnePlus 7 Pro. Carriers like T-Mobile, Sprint, AT&T, and Verizon are awarding up to $700 in trade-in credits, and as for retailers, there's the usual doorbusters. It's almost too much of a good thing -- particularly if you aren't committed to a brand, a model, or a manufacturer. Conventional wisdom would have you judge a device by its screen or perhaps its camera, but we took a different tack last year with our guide to the best phones for the AI enthusiast.

Over the past year, business leaders worldwide have been sensing that confidence is low – but where's the data to support that? The 2019 Worldcom Confidence Index fills that void with hard data gathered using a revolutionary methodology powered by artificial intelligence (AI). Last year, we predicted that AI would be the big issue of 2019, and we were right. The 2019 Worldcom Confidence Index is just one example of how AI has fundamentally altered our operating concept across a range of industries – from healthcare to manufacturing and now to survey methodology. This forward-thinking approach to gathering and analyzing data is emblematic of the work Worldcom Public Relations Group does and is one of the reasons we're proud to be a member of this global PR network.