The global threat of fraud shows no signs of slowing down. Losses related to fraud are valued at $14.7 billion, according to the most recent DataVisor Fraud Index Report. As fraudsters become increasingly aggressive, new global regulations and solutions are being deployed to keep consumers, merchants and banks safe. In the latest Digital Fraud Tracker, PYMNTS highlights the fraud trends and patterns that regulators are closely monitoring, as well as the solutions -- including artificial intelligence (AI) and machine learning (ML) -- that are being deployed to shift the anti-fraud effort from defense to offense. Fraud has become particularly problematic in the United Kingdom, where last year card-based losses increased by 19 percent compared to the previous year.

A whole bunch of fresh info on Microsoft Flight Simulator has come up thanks to a recent preview event, and that includes some notable detail on how the game's cloud tech actually shapes the world you're flying around. In short, the answer to the obvious question is yes: you can totally seek out and fly by your house in-game. That's a pretty simple idea in concept, but making it happen requires a combination of satellite imagery – pulled from Microsoft's own Bing maps – and cloud processing – similarly built from Microsoft's Azure tech. It all works together through the process of photogrammetry, which interprets two-dimensional imagery into three-dimensional game objects. So as long as you're connected to Microsoft servers, you will find the entirety of the real world recreated in the simulator, down to the last detail.

Last year the United States Food and Drug Administration (FDA) cleared a total of 12 AI tools that use machine learning for health (ML4H) algorithms to inform medical diagnosis and treatment for patients. The tools are now allowed to be marketed, with millions of potential users in the US alone.Because ML4H tools directly affect human health, their development from experiments in labs to deployment in hospitals progresses under heavy scrutiny. A critical component of this process is reproducibility. A team of researchers from MIT, University of Toronto, New York University, and Evidation Health have proposed a number of "recommendations to data providers, academic publishers, and the ML4H research community in order to promote reproducible research moving forward" in their new paper Reproducibility in Machine Learning for Health. Just as boxers show their strength in the ring by getting up again after being knocked to the canvas, researchers test their strength in the arena of science by ensuring their work's reproducibility.

Artificial Intelligence (AI) is ripe for development and investment for health information management (HIM). The major initiatives towards Interoperability and AI is just beginning in the US. The National Institute of Health has invested $1.5B into the All of Us Research Program, which invites participants across the country to share their biology, lifestyle and environment. Aggregated data sources like this one promise to enable AI technologies to improve diagnostic accuracy, clinical and operational efficiency and the overall patient experience.1 While these innovations are promising, they are also in a preliminary phase for HIM applications from an accuracy and reliability or practical use perspective.

American leadership in Artificial Intelligence (AI) is critical to driving innovation and maintaining our nation's economic competitiveness. Today, U.S. Department of Energy (DOE) laboratories house four of the ten fastest and most powerful supercomputers in the world, uniquely positioning DOE to redefine what is possible in AI. DOE established its Artificial Intelligence Program (DOE AI) to harness and accelerate the Department's world-class leadership in high-performance computing, facilities, and team science in applying AI across the entire National Laboratory system to increase the pace of discovery in energy, materials science, health care, transportation, and beyond. InnovationXLab: Artificial Intelligence, hosted by Argonne National Laboratory, is the fourth in DOE's InnovationXLab series: a showcase of the remarkable assets and capabilities of the Department's National Laboratories. These summits facilitate a two-way exchange of information and ideas between industry, universities, investors, and end-use customers with Lab innovators and experts.

Microsoft has invested $1 billion in the Elon Musk-founded artificial intelligence venture that plans to mimic the human brain using computers. OpenAI said the investment would go towards its efforts of building artificial general intelligence (AGI) that can rival and surpass the cognitive capabilities of humans. "The creation of AGI will be the most important technological development in human history, with the potential to shape the trajectory of humanity," said OpenAI CEO Sam Altman. We'll tell you what's true. You can form your own view.

Revealing a disconnect in UK workplaces, 83% of leaders claim not to have been asked by staff about AI. The absence of transparency and open communication is fuelling fears about job security among workers while, at the same time, preventing them from understanding exactly how AI can help augment their roles. More than a third of staff (36%) would use the time they saved by using AI to learn new skills at work. Lord Clement-Jones, Chairman of the House of Lords Select Committee on AI, said: "There is absolutely no excuse for anybody in business, at whatever age, for not reinventing themselves in terms of really understanding how AI works." The rate of AI adoption also varies depending on sector, with financial services leading the way. Nearly three-quarters (72%) of the nation's finance leaders say their organisation is using AI – a 7% increase from 2018 and considerably higher than the national average of 56%. Half of leaders in the field want their organisation to be a leader in AI. More than half (51%) of manufacturing leaders who were interviewed for Microsoft's report said they were using AI, falling to 46% for healthcare and 43% for retail. Microsoft has launched a number of initiatives to boost the level of digital skills in the UK, including a free online AI Business School enabling executives to learn about strategies and use of AI at their own pace in their own time.

Butterfly Network is reinventing medical imaging and championing a new era of healthcare by creating the first ever pocket-sized, whole-body ultrasound device – the Butterfly iQ. This breakthrough technology has reduced the cost of the traditional ultrasound system by miniaturizing it onto a single semiconductor silicon chip. Our mission is to democratize healthcare by making medical imaging accessible to everyone around the world. Since inception, Butterfly has raised over $375 million. The iQ is FDA-cleared and is being sold in hospitals and clinics around the globe.

This February, China's best-known contemporary actress, Yang Mi, surfaced in a video of a 1983 Hong Kong television drama The Legend Of The Condor Heroes. Given the prevailing China-Hong Kong friction, the fake video wherein the original actress' face was replaced with Yang garnered almost 240 million views before it was removed by Chinese authorities. Similarly, videos of US President Donald Trump mocking Belgium for joining the Paris Climate agreement, or a video of Facebook CEO Mark Zuckerberg boasting that the social network owns its users, were widely circulated until they were found to be fake. Known as deepfakes, this new breed of fake videos first surfaced back in 2017 with fake porn videos of some Hollywood celebrities. While initially simple open source video editing tools were used to manipulate audio and video, criminals are now using more sophisticated machine learning (ML) tools like generative adversarial networks, or GANs, that use a pair of contrasting unsupervised ML algorithms to create a deepfake.

Machine learning is automating the more manually-based, routine incident analysis, and escalation tasks that are overwhelming security analysts today. Capitalizing on supervised machine learnings' innate ability to fine-tune algorythms in milliseconds based on the analysis of incidence data, endpoint security providers are prioritizing this area in product developnent. Demand from potential customers remains strong, as nearly everyone is facing a cybersecurity skills shortage while facing an onslaught of breach attempts. "The cybersecurity skills shortage has been growing for some time, and so have the number and complexity of attacks; using machine learning to augment the few available skilled people can help ease this. What's exciting about the state of the industry right now is that recent advances in Machine Learning methods are poised to make their way into deployable products," Absolute's CTO Nicko van Someren added.