Doing business in Sudan isn't easy, but back in 2011, it should have been possible. "We were working with major telecoms company Zain based out of southern Sudan at the time – before the country split in two," explains Charlie Tryon, chief executive of Maris, an investment holding company that operates across east and southern Africa. "Sudan was on the US's Office of Foreign Assets Control (OFAC) sanctions list, but the south was exempt, so it should have been OK for us to work here. We took out all the precautions we needed – did all the necessary paperwork, spoke to all the right people, told the banks, made sure we had permission from OFAC and notified all other regulatory bodies about our cross-border transaction – everything. "But the money we transferred from our business bank account to Zain was still stopped," he says. Tryon's transaction failed to pass compliance tests. In a bind, he was forced to physically move thousands of dollars from a bank account in Uganda to Sudan to pay his suppliers – at great personal risk. "We had suitcases full of cash that we took via plane and car into Sudan," says Tryon. "This isn't the ideal way to run a business, but at the time we had very little choice." A lot has changed since 2011. Know-your-customer and anti-money laundering (AML) screening is increasingly automated, helping to remove some of the delays caused by strict compliance measures. On top of this, banks, retailers, payment service providers (PSPs) and other businesses involved in the money transfer process are using artificial intelligence (AI) to make much more accurate decisions about payments. "At the time, we spent a huge amount of money and time trying to set this right," says Tryon. "It included international travel, lobbying, meetings with banks and regulators.

That Artificial Intelligence will replace the need for a human workforce, is a misconception. Rather, AI is an effective tool that can support a business to build a more efficient workforce and assist with cost-saving initiatives. This is the view of Wessel Oosthuizen, Senior Manager, TMT, Deloitte Africa, who says that skills and capacity building in the field of AI, as well as critical thinking and a workforce that understands how to leverage this technology – are key for businesses to remain relevant in a rapidly changing world. "Individuals with finance, engineering or computer science backgrounds – who understand both the possibilities that AI presents and its limitations – are priceless. They combine their subject matter expertise, critical thinking, data analysis and innovation, with AI tools and techniques to help their organisations make the most of AI and similar technologies" said Oosthuizen. His sentiments are echoed in Deloitte's recently released 18th edition of its Technology, Media & Telecommunications Predictions (TMT Predictions), which finds that while enterprise software and cloud-based development platforms can provide effective gateways to AI, they are not a substitute for having at least some technical AI talent, in-house.

A detailed study accumulated to offer Latest insights about acute features of the LegalTech Artificial Intelligence market. The report contains different market predictions related to market size, revenue, production, CAGR, Consumption, gross margin, price, and other substantial factors. The report also offers a complete study of the future trends and developments of the market. It also examines the role of the leading market players involved in the industry including their corporate overview, financial summary and SWOT analysis. Legal technology, also known as Legal Tech, refers to the use of technology and software to provide legal services.

Automation and innovation in the work within business is necessary for the reinvention of the system landscapes. The same is possible with the machine learnings together with the help of the artificial intelligence platform. The industries in the recent time are in the tremendous need of the artificial intelligence platform to increase automation, machine interaction and to save time. Furthermore, problem-solving, social intelligence and general intelligence can also be achieved with the help of the artificial intelligence platform. The artificial intelligence platform market is expected to grow during the forecast period due to growth in adoption of cloud based application and services.

This paper presents an initial design concept and specification of a civilian Unmanned Aerial Vehicle (UAV) management simulation system that focuses on explainability for the human-in-the-loop control of semi-autonomous UAVs. The goal of the system is to facilitate the operator intervention in critical scenarios (e.g. avoid safety issues or financial risks). Explainability is supported via user-friendly abstractions on Belief-Desire-Intention agents. To evaluate the effectiveness of the system, a human-computer interaction study is proposed.

How much does someone's living room tell about how they live? Peeking into another person's life might be just part of natural human curiosity, but the answer to this question may provide insights in a wide range of aspects of human behavior. A new study published in EPJ Data Science uses the power of machine learning to explore patterns of home decors--and what they could tell about their owners--in popular accommodation website Airbnb. The Internet has provided the world with more images than can be viewed in a lifetime. Some sites, like Craigslist, Zillow, and Airbnb, specifically let us see the interiors of peoples' homes, nests of revealing human creativity, design, style and culture.

Helsinki, Finland - An audience of international peace brokers have gathered inside a room in the historic House of Estates. They have come from South Sudan, the Central African Republic, Ukraine, Colombia and elsewhere to hear a scientist speak. That scientist is Timo Honkela, and his keynote speech on the second day of April's National Dialogues conference is titled Peace from a Different Perspective - a Dialogue of a Million People. But 54-year-old Honkela is working on a machine that he hopes will facilitate world peace. "World peace would be a good goal to work for in my remaining days," he says, smiling over a cup of coffee during a break in the conference.

Artificial Intelligence (AI), machine learning, and deep learning are taking the healthcare industry by storm. They are not pie in the sky technologies any longer; they are practical tools that can help companies optimize their service provision, improve the standard of care, generate more revenue, and decrease risk. Nearly all major companies in the healthcare space have already begun to use the technology in practice; here I present some of the important highlights of the implementation, and what they mean for other companies in healthcare. AI, machine learning, and deep learning are already increasing profits in the healthcare industry. For example, according to research firm Frost & Sullivan by 2021, AI systems will generate $6.7 billion in global healthcare industry revenue.

At the SIS Global Forum 2019, Chevron, Microsoft and Schlumberger, announced the industry's first three-party collaboration to accelerate the creation of innovative digital and petro-technical technologies. The three companies will work together to build Azure-native applications in the DELFI cognitive E&P environment initially for Chevron, which will enable companies to process, visualize, interpret and eventually obtain meaningful and vital insights from numerous data sources. The collaboration will be completed in three phases, starting with the deployment of the Petrotechnical Suite in the DELFI environment. This will be followed by the development of cloud-native applications on Azure and the co-innovation of a suite of cognitive computing native compatibilities across the E&P value chain tailored Chevron's objectives. "Combining the expertise of these three global enterprises creates vastly improved and digitally-enabled Petrotechnical workflows. Never before has our industry seen a collaboration of this kind, and of this scale. Working together will accelerate faster innovation with better results, marking the beginning of a new era in our industry that will enable us to elevate performance across our industry's value chain," said Olivier Le Peuch, Chief Executive Officer, Schlumberger.

The AI market is possibly one of the toughest to keep track of, as the pace of change is relentless. Making predictions is even harder for this market, as one tends to follow what is known as Amara's Law, overestimating the potential of a technology in the short term and underestimating it in the longer term. Nevertheless, Tractica has identified 10 key predictions that cover various aspects of the ever-evolving AI market, based on our ongoing research and analysis including extensive primary research and interviews. Key trends to watch in the AI market in 2019 will include the commercialization of promising technologies, the growth of new application markets, changes in hardware architectures and infrastructure to support AI deployments, and continuing evolution of business models and public policy issues. Tractica's 10 key predictions for AI in 2019 include the following: This Tractica white paper identifies 10 key predictions for the AI market in 2019 and provides supporting details and examples behind each prediction. These trends draw from ongoing research and analysis that form part of Tractica's Artificial Intelligence advisory service.