The Future Digital Economy is ERP3 In technology or at least the application and security areas I sit within, acronyms are everywhere,... As cloud computing progresses forward, an ages-old problem for IT is resurfacing--how to integrate and secure data stores that are disbursed geographically and across a growing diversity of applications. SAN FRANCISCO--(BUSINESS WIRE)--DeepBrain Chain is an Artificial Intelligence Computing Platform driven by blockchain. Sir, Your editorial "The paradox in ceding powers of decision to AI" (FT Weekend, December 30) makes the correct observation that "without care, … The IT infrastructure landscape is evolving rapidly. What will it look like in 2020?

– This article is only meant for discussion and healthy arguments, its not a conclusion by any means this is just an assumption and current picture focused on African & few other markets. Today payment industry can be compared with either payment war, payment jungle or even just payment storm. On the other hand how Mobile Financial Services have brought FinClusion (financial inclusion) to millions of people that have no access to traditional methods of banking. In many parts of Africa, there simply exists no bank infrastructure for people to be able to bank in the traditional way. Even where they do exist, people do not dare to enter into the big bank halls due to killing charges, KYC requirement equivalent to climbing the mount everest and time to travel miles to go or even time to stand in long queues or have the patience to go through the bank's processes.

I was invited as a keynote speaker in Khartoum – Sudan on November 27 and November 28 2017 by Lutfi Self Development Centre (Lutfi SDC Sudan) It was big event in Khartoum and opening speech was done by Sudan central bank officials. It was amazing experience and lot of learning came out. The event was attended by MTN, Oracle, GSMA and many big names of the industry. I presented my topic of AI in FinTech focused on my area of advocacy on how AI is reinventing FinTech by disrupting and non disrupting methodologies. Bringing Artificial intelligence to make FinTech better, demystified and simple.

Next time a trip to the doctor seems daunting, consider this: in parts of sub-Saharan Africa, patients must travel long distances to access treatment. Even once they see a practitioner, there is still concern about receiving the medicine and treatments they need. In developed countries, healthcare challenges are different -- often revolving around improving quality, outcomes and costs -- but they are challenges nonetheless. Startups and more experienced organizations alike look to mobile healthcare innovation to address these challenges across the globe, helping provide better access to care, improving quality and driving better outcomes. These innovations are built on top of standard mobile technologies, such as SMS messaging and Bluetooth, and through emerging technologies including artificial intelligence (AI), machine learning (ML), natural language processing, voice assistants (VA) and the IoT.

Fintech and automation are critical to growing transaction-banking services in the era of Big Data. Faced with more-demanding corporate clients in a multibank environment, transaction banks have invested millions of dollars in creating a seamless technological experience by integrating their banking platforms with those of their corporate and institutional clients. Treasurers want real-time visibility and control over their cash and liquidity, to minimize external borrowings, effectively manage working capital and maximize returns, according to Chet Kamat, CEO of Oracle Financial Services Software. "It is critical to have systems that not only effectively manage and monitor transaction-based liquidity but also help corporates project their positions based on future cash flows," he says. "Treasurers are looking for an integrated system that makes it simple to monitor positions across multiple geographies, with multiple banks, and that eases reconciliation between bank systems and corporate systems."

In tropical regions, populations continue to suffer morbidity and mortality from malaria and arboviral diseases. In Kedougou (Senegal), these illnesses are all endemic due to the climate and its geographical position. The co-circulation of malaria parasites and arboviruses can explain the observation of coinfected cases. Indeed there is strong resemblance in symptoms between these diseases making problematic targeted medical care of coinfected cases. This is due to the fact that the origin of illness is not obviously known. Some cases could be immunized against one or the other of the pathogens, immunity typically acquired with factors like age and exposure as usual for endemic area. Then, coinfection needs to be better diagnosed. Using data collected from patients in Kedougou region, from 2009 to 2013, we adjusted a multinomial logistic model and selected relevant variables in explaining coinfection status. We observed specific sets of variables explaining each of the diseases exclusively and the coinfection. We tested the independence between arboviral and malaria infections and derived coinfection probabilities from the model fitting. In case of a coinfection probability greater than a threshold value to be calibrated on the data, duration of illness above 3 days and age above 10 years-old are mostly indicative of arboviral disease while body temperature higher than 40{\textdegree}C and presence of nausea or vomiting symptoms during the rainy season are mostly indicative of malaria disease.

Marking the coming of the fourth industrial revolution, the use of artificial intelligence (AI) is permeating every major industry from healthcare to transportation, education, finance and insurance. The McKinsey Global Institute (pdf) says that AI is contributing to a transformation of society "happening ten times faster and at 300 times the scale or at roughly 3,000 times the impact" of the Industrial Revolution. In the healthcare industry, AI's ability to help clinicians make diagnoses is one major way in which patients are benefiting directly. Technology giant IBM brought AI into the mainstream of healthcare, when it offered its AI platform Watson to cancer centres in 13 countries to aid oncologists in identifying evidence-based treatment options for patients. The promise of AI is not limited to commercial applications.

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Dawit Haile fought against the odds when he decided to study computer science in Eritrea, East Africa, despite having no internet connectivity. His perseverance paid off, first landing a job with the Eritrean government department of education, and later as an engineer in Lithuania. Today, Dawit is a data scientist in the San Francisco Bay Area, and he credits this new job to the knowledge and experience he gained from fast.ai. On the side, he's building an algorithm to translate between English and his native language of Tigrinya. Dawit is just one of many impressive fast.ai

Shiraz Khota, SAP SAThe use of artificial intelligence techniques is revolutionising a number of technologies today, including internet search, game theory, business intelligence and medicine. What's not as well known is how it's changing finance for the better. AI is making finance faster, more efficient and more innovative. Plugging large amounts of historical data into deep learning systems can yield surprising – and profitable – results, but there are also the more run-of-the-mill benefits such as reducing the day-to-day grind of repetitive tasks. Where could AI make a difference in financial work right now? Shiraz Khota, head of S/4 Hana Cloud at SAP South Africa: A lot of the technology that is out there right now already has AI technology in it, even if it's rudimentary.