A friend recently confided in me about his fertility problems. His physician had told him his sperm were small and malformed, to the point that he might struggle to get his wife pregnant. In an effort to make him feel less bad, perhaps, she added that male fertility problems were currently at "epidemic" levels in the UK. Recent articles in several major news outlets told this same worrisome tale. For instance, one BBC headline screamed, "sperm count drop'could make humans extinct'".

Capturing the effects of Low-Probability, High-Impact "Black Swans" in the existing stochastic and deterministic models is tremendously Important. On this page, I would like to share with the members an open access, peer reviewed published research findings of my PhD thesis on how to capture the effects of Low-Probability, High-Impact Events in our existing economic and financial models. I shall begin with the incorporation of fat-tailed effects of the underlying assets probability distribution in the popular LOGIT and PROBIT MODELS. INTRODUCTION The Global financial markets have experienced series of financial and economic crises right from the inception and from generation to generation. Banks, Companies and the world economy experienced catastrophic deterioration and serious corporate failures by systemic risk effect.

The topic of machine learning-enabled artificial intelligence (AI) is gaining increasing visibility in the world of investment management. Of particular interest is the application of AI to the development of smarter robo-advisers that some hope, while others fear, will yield'intelligent' and cost-effective investment management advice. This topic was raised by investment professionals during the recent CFA Institute travelling conference that went to Central and Eastern Europe and the Middle East. AI has also been the subject of a recent European Commission (EC) consultation document, to which CFA Institute submitted a response. For the uninitiated, some quick defining of terms could be helpful.

Both industry and community must develop effective mechanisms to filter bias as well as negative sentiment in the data that AI learns from - ensuring AI does not perpetuate stereotypes. Users build a relationship with AI and start to trust it after just a few meaningful interactions. With trust, comes responsibility and AI needs to be held accountable for its actions and decisions, just like humans. Technology should not be allowed to become too clever to be accountable. We don't accept this kind of behaviour from other'expert' professions, so why should technology be the exception.

Bokeh is a Python interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of novel graphics in the style of D3.js, but also deliver this capability with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.

Regardless of size, geography or industry, every organisation requires exceptional talent that is both motivated and focused to deliver on customer promises. Yet, it is getting harder to recruit and retain talented, high performing employees. When considering the costs associated with recruiting and on-boarding new employees, making the wrong decision will result in a massive impact for an organisation. "It costs an organisation 200% of a senior hires' annual salary to on board them, this includes recruitment fees, remuneration, back office administration, training and team time. It's very expensive to replace people," says Jason Davies, Africa Head of Leadership, Learning, Talent and Resourcing at Barclay's Africa Group.

Autonomous cars have been a staple of science fiction for years, appearing in films like I, Robot, Demolition Man and Minority Report. Google is nearing the final stages of testing for its autonomous car programme, Tesla drivers can enjoy an'Autopilot' feature for hassle-free motorway driving, and Pittsburgh residents can hail an Uber that drives itself. But how do driverless cars work? When can we expect to try one out for ourselves? We answer all these questions, and more, below. The tech giant finally acknowledged the truth in rumours that it was building driverless technology in June, when Cook told Bloomberg that it was "a core technology that we view as very important". But he declined to give a steer on how the tech would manifest itself in Apple products. Yesterday he painted a clearer picture of its potential on a conference call following the company's quarterly results.

I attended the first and largest of its kind, UN ITU XPRIZE Artificial Intelligence (AI) for Good Global Summit held 7-9 June 2017 in Geneva touching 300 plus million, influencing 1 billion, and meaningfully impacting 7.2 billion via more than 30 global media, social media, and television crews, including a documentary crew. If you have not done so already you want to get over to the summit website and view the rich collection of content there created by the top leaders and minds in AI, civil society, 21 UN organizations, governments, industry, academia, and media. Just a few of the notable speakers and participants were: Peter Norvig head of research at Google, Peter Lee Corporate Vice President of Microsoft AI and Research, Margaret Chan Director General of the World Health Organization (WHO), Pedro Domingos Professor of Computer Science and Engineering at the University of Washington, Jü rgen Schmidhuber, Scientific Director, Swiss AI Lab, IDSIA; Professor of AI, USI & SUPSI, Switzerland; President of NNAISENSE, Andy Chen Board Chair at IEEE Computer Society, and Vicki Hanson, President of ACM, and Distinguished Professor of Computing at the Rochester Institute of Technology. The Summit sought to speed the development of, and access to, AI solutions to address global challenges ranging from poverty, hunger, health and education to equality and environmental sustainability. In my last article, I challenged everyone including all in the business world to deliberately embrace AI in a way that results in good outcomes.

The sea and ocean environment has long been explored using some of the most sophisticated technology tools. Today's technologies make it child's play to explore natural environments under the sea. The American Goddard Space Flight Center, which belongs to NASA, relies on machine learning to track microscopic algal growth in oceans. The microalgae, which float on the water's surface, are largely responsible for producing oxygen, an element essential for supporting life. Many underwater observations rely on advanced detection technologies.

A new technique using artificial intelligence to predict where deforestation is most likely to occur could help the Democratic Republic of Congo (DRC) preserve its shrinking rainforest and cut carbon emissions, researchers have said. Congo's rainforest, the world's second-largest after the Amazon, is under pressure from farms, mines, logging and infrastructure development, scientists say. Protecting forests is widely seen as one of the cheapest and most effective ways to reduce the emissions driving global warming. But conservation efforts in DRC have suffered from a lack of precise data on which areas of the country's vast territory are most at risk of losing their pristine vegetation, said Thomas Maschler, a researcher at the World Resources Institute (WRI). "We don't have fine-grain information on what is actually happening on the ground," he told the Thomson Reuters Foundation.