The Institute of Internal Auditors (IIA) recently hosted a session on Artificial Intelligence (AI) in fraud detection. Participants of the session listened to Hatem Elsafty, partner at Mazars-Qatar. Marwan Arab AI & Machine Learning Architect with Mazars presented case studies with the'Artificial Intelligence Fraud Fight Platform (AIFF)' developed by Mazars with Pandata, provides predictive and forensic intelligence solutions for fraud detection. During the session, Elsafty explained the concept of fraud, artificial intelligence, and machine learning using real-life examples and scenarios. "We are living in an era of advanced technologies that changed the way we do business. Artificial Intelligence (AI) and the use of Big Data are two of the leading technologies that provided useful business applications to automate and significantly support the reduction of fraud and corruption," said Elsafty.

File photo - Troopers with the U.S. Army 2nd Armored Brigade Combat Team, 3rd Infantry Division fire the main gun round at a target during unit gunnery practice with newly acquired M1A1-SA Abrams tanks at Fort Stewart, Georgia, U.S. March 29, 2018. Picture taken March 29, 2018. The targets are dispersed across expansive, mountainous terrain, yet moving in coordination for attack. The armored vehicle cannot fire upon the enemy tanks and give away its position, so it "networks" the targeting specifics to an armed overhead drone which then attacks the enemy tanks -- exploding them with Hellfire missiles, all without putting soldiers at risk. In similar fashion - perhaps a forward operating unmanned ground vehicle receives the targeting information and, controlled by a human operator, fires on the enemy tanks without exposing the location of a manned crew.

It has been clear for some time that artificial intelligence has already evolved and is entering a new phase of development. While it is not entirely clear as yet how, or even if, enterprises will use this new advanced AI, before looking at new strategies for this cutting edge technology -- and edge is a key word here -- it is important to understand what is and what it can possibly do. In its recent Hype Cycle for emerging technologies (subscription required) and subsequent analysis of where the evolution of digital innovation is going, Stamford, Conn.-based, Gartner, took a look at advanced analytics and its possible role in the enterprise. According to the research, advanced analytics is the autonomous or semiautonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI). In a statement about the research, Brian Burke, research vice president at Gartner explained: "The adoption of edge AI is increasing for applications that are latency-sensitive (e.g., autonomous navigation), subject to network interruptions (e.g., remote monitoring, natural language processing [NLP], facial recognition) and/or are data-intensive (e.g., video analytics)."

Machine study empowers patterns of the supply chain to be found through calculations that quickly decide the most basic factors in the accomplishment of the supply chain information. FREMONT, CA: Logistics activities work on muddled internet services, clients, middle people, agents, and depend on everybody to convey their administrations, services, and items now. As logistics proceeds with the digitization course, 3PL (third-party logistics providers) consider fusing AI to help with the mind-blowing challenge of observing and booking a whole supply network. AI and machine learning can help logistic organizations to distinguish timing and request patterns for suppliers. To gather orders and to convey them toward the finish of the production network, stores are regularly used to make the strategy an increasingly consistent and mid-point thing accumulation.

Come meet the Fortinet team to see how we can secure your future business initiatives. Moving into 2020, digital transformation remains a top priority for business leaders – around the world and across industries. As the solutions available to enable digital transformation continue to advance, leaders are often left wondering how to best select and implement digitization tools that not only incorporate edge-to-edge technologies that align with their future business goals, but that also ensure that those transformation efforts don't compromise their security. Fortinet is participating in this year's AT&T Business Summit to help today's leadership answer questions like this. This summit will offer insight into how businesses can make smart investments in their technology, and their team, to take full advantage of the opportunities afforded by digital transformation.

Researchers in the US developed a new artificial intelligence algorithm, which manages better than experienced radiologists in detecting small cerebral bleeding. This development is expected to help physicians in the future to diagnose and better treat patients with head injuries, strokes and aneurysms. The new system can relieve radiologists from a heavy workload, as artificial intelligence technology will first distinguish imaging tests with abnormal findings and then doctors will examine them more carefully. The physicians and computer engineers of the Universities of California-San Francisco and California-Berkeley, headed by Assistant Professor of Radiology Esther Yach, published this in the journal of the US National Academy of Sciences (PNAS). The algorithm -a fully co-revolutionary neural network trained in 4,400 pre-existing tomographs- takes only one second to judge if there is any bleeding in the entire head.

Google today announced one of the biggest updates to its search algorithm in recent years. By using new neural networking techniques to better understand the intentions behind queries, Google says it can now offer more relevant results for about one in ten searches in the U.S. in English (with support for other languages and locales coming later). For featured snippets, the update is already live globally. In the world of search updates, where algorithm changes are often far more subtle, an update that affects 10 percent of searches is a pretty big deal (and will surely keep the world's SEO experts up at night). Google notes that this update will work best for longer, more conversational queries -- and in many ways, that's how Google would really like you to search these days because it's easier to interpret a full sentence than a sequence of keywords.

This was not just any math problem. On Wednesday, Google said its researchers had performed a calculation that the largest supercomputers could not complete in under 10,000 years. And they had done it in 3 minutes 20 seconds. With that calculation, the company said, its research lab in Santa Barbara, Calif., achieved a milestone that scientists had been working toward since the 1980s -- a breakthrough called "quantum supremacy" that could allow new kinds of computers to do calculations at speeds that are inconceivable with today's technology. The long-sought breakthrough could have implications for national security and cryptography and even pave the way for the creation of new medicines.

The Alan Turing Institute has this week announced the first five Turing AI Fellows, each of which will carry out different research into various roles and applications of artificial intelligence. This first wave of fellows - as well as a second wave that has this week been announced by the Institute this week - forms part of the government's £1 billion AI sector deal. Working with the Office for Artificial Intelligence and UK Research and Innovation (UKRI), the fellowships have received £37.5 million of funding for five years. The Alan Turing Institute said that the AI Fellows are drawn from a variety of disciplines and backgrounds and will be tackling research challenges from sustainable aviation to AI for discovery in data intensive astrophysics. AI has the potential to boost productivity and enhance every industry across the economy, from developing new treatments for life-threatening diseases to tackling climate change.

The room was packed at the annual Machine Learning and the Market for Intelligence conference in Toronto last week. Now in its fifth year, the lengthy name of the event matches the depth of the discussions. But one speaker and her talk stood out to me in particular: Marzyeh Ghassemi, who also happens to be a veteran of Alphabet's Verily, presented "Machine Learning From Our Mistakes." Ghassemi, an assistant professor at the University of Toronto, talked about the importance of predicting actionable insights in health care, the regulation of algorithms, and practice data versus knowledge data. But at the very end, saving the best for last, she emphasized the importance of treating health data as a resource.