The word deepfake combines the terms "deep learning" and "fake," and is a form of artificial intelligence. In simplistic terms, deepfakes are falsified videos made by means of deep learning, said Paul Barrett, adjunct professor of law at New York University. Deep learning is "a subset of AI," and refers to arrangements of algorithms that can learn and make intelligent decisions on their own. More specifically deepfake refers to manipulated videos, or other digital representations produced by sophisticated artificial intelligence, that produce fabricated images and sounds that appear to be real. But the danger of that is "the technology can be used to make people believe something is real when it is not," said Peter Singer, cybersecurity and defense-focused strategist and senior fellow at New America think tank.

We asked 9 industry experts to contribute their thoughts on the year ahead, and a common theme was the need for these technologies to mature, with the genuinely useful implementations finally getting to market. Expanding on last year, we have chosen seven areas of interest to focus on in 2019. Each represents a vital area of innovation in the financial industry, and has a particular relevance to Luxembourg's thriving financial technology ecosystem. Each week we will be choosing one of the topics to focus on, both in the content we share on social media, but also in a dedicated newsletter looking at the top five stories from that week. First, let's introduce the topics with some of our favourite summaries for the uninitiated: "Regtech growth will explode in 2019 because regulators worldwide will start truly driving it. Multiple countries will hold a joint hackathon at midyear, aiming to use technology to remove one of the biggest regtech blockers: how to share data widely to find risk patterns and fight financial crime, while fully protecting privacy and cybersecurity. Solutions will solve myriad regulatory problems. Even more importantly, the shared experience will move regulatory bodies into a new era of active innovation and collaboration with each other, industry, and academia. Anti-money laundering will continue to be a leading use case, because the current system is so broken and costly and there's so much low-hanging fruit to harvest through technology. We'll also see AI and blockchain solving more problems, from digital identity and financial fairness and inclusion to API-based regulatory reporting, machine-readable regulations, and even machine-executable compliance. These regulatory breakthroughs are not just nice-to-have. They are essential, if fintech innovation is to flourish. The regulations are the rules of the road we're all traveling."

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since the early days of artificial intelligence, computer scientists have been dreaming of creating machines that can see and understand the world as we do. The efforts have led to the emergence of computer vision, a vast subfield of AI and computer science that deals with processing the content of visual data. In recent years, computer vision has taken great leaps thanks to advances of deep learning and artificial neural networks. Deep learning is a branch of AI that is especially good at processing unstructured data such as images and videos.

Fox News Flash top headlines for Dec. 31 are here. Check out what's clicking on Foxnews.com One day after Colorado and western Nebraska counties reported a series of mysterious, nocturnal drone flights, the Federal Aviation Administration is promoting a rule change last week that requires most drones to be identifiable remotely, a report said Monday. The rule change, announced Thursday, have been in works for more than a year, FAA spokesman Ian Gregor said in an email to the Denver Post Monday. Under the legislation, law enforcement, federal security agencies and the FAA would be allowed to identify drones flying through their jurisdiction, the FAA said.

The earliest roots of deepfakes were a source of social media fun. Anyone capable of taking a selfie could superimpose their face onto a super model's body and share it for all of their followers to see. Users could also apply any one of the ubiquitous face filters that allow you to add some floppy dog ears or bunny whiskers to your Instagram photos. These types of distorted images were the first incarnations of the deepfake era, and until recently, it was harmless. Today, however, deepfakes are shaking the very foundation of our trust in what we see, hear and believe, to the point that we're not sure what is real and what is fake.

U.S. spies are no longer being tailed by foreign governments in about 30 different countries because advances in facial recognition, biometrics and artificial intelligence have made it almost impossible for the agents to hide. Whereas governments would once physically follow CIA officers, facial recognition at airports and general CCTV surveillance in those countries makes it far easier to track people. It comes as U.S. intelligence agencies face a growing crisis in intelligence gathering, as developments in technology are making it increasingly more difficult to protect operatives and mask their digital footprints. In one attempt to tackle the crisis, the CIA created a multi-million dollar program called the Station of the Future, intelligence officials revealed to Yahoo News. The program, created over the past decade, was run out of a diplomatic facility in Latin America and involved a team of spies trying to build tools and test techniques that could help the industry battle the digital age.

Artificial Intelligence and its inherent bias may not be as judgmental as previously thought, at least in the case of home loans. It appears the use of algorithms for online mortgage lending can reduce discrimination against certain groups, including minorities, according to a recent study from the National Bureau of Economic Research. This could end up becoming the main tool in closing the racial wealth gap, especially as banks start using AI for lending decisions. The Breakdown You Need to Know: The study found that in person mortgage lenders typically reject minority applicants at a rate 6% higher than those with comparable economic backgrounds. However, when the application was online and involved an algorithm to make the decision, the acceptance and rejection rates were the same.

Health products powered by artificial intelligence, or AI, are streaming into our lives, from virtual doctor apps to wearable sensors and drugstore chatbots. IBM boasted that its AI could "outthink cancer." Others say computer systems that read X-rays will make radiologists obsolete. "There's nothing that I've seen in my 30-plus years studying medicine that could be as impactful and transformative" as AI, said Dr. Eric Topol, a cardiologist and executive vice president of Scripps Research in La Jolla, Calif. AI can help doctors interpret MRIs of the heart, CT scans of the head and photographs of the back of the eye, and could potentially take over many mundane medical chores, freeing doctors to spend more time talking to patients, Topol said. Even the Food and Drug Administration ― which has approved more than 40 AI products in the past five years ― says "the potential of digital health is nothing short of revolutionary."

Fox News Flash top headlines for Dec. 30 are here. Check out what's clicking on Foxnews.com A squadron of drones flying over the Midwest every night for nearly two weeks have left both residents and officials wondering who's flying them and what purpose they are serving, a report said Sunday. In the past week, three more rural counties have experienced nightly flyovers from the northeast corner of Colorado to at least one county in neighboring Nebraska, the Denver Post reported. Sheriffs in Lincoln, Washington and Sedgwick counties say their offices have been inundated with calls this week about the devices, the newspaper reported.

Open Banking promises increased access to customer data, but with newfound transparency comes a greater need to understand how that data is utilised. Together with developments in machine learning (ML), markets are changing. So far, ML has been used in financial services to manage content and data, detect fraud and money laundering, facilitate biometric identification, trade via algorithms, and assist with regulatory compliance. A survey by the Bank of England, undertaken in the first half of this year, found that two-thirds of UK financial services companies are now using ML. Nineteen percent of companies surveyed have or are creating centres for promoting the technology internally.