Current fail-safe measures designed to ensure material generated by artificial intelligence (AI) is clearly labeled does not meet an appropriate standard and may not be possible with current technology, an expert warns. "There's no interest, and it's difficult to do," Michael Wilkowski, chief technology officer of AI-driven bank compliance platform Silent Eight, told Fox News Digital, stressing that, in his view, it's "actually nearly impossible to discover" if something was AI-generated or not. The current method of applying a watermark at first glance appears more advanced than the traditional method, which would apply a physical mark over the material to make it clear and obvious that the watermark exists. Instead, AI-generated material has an embedded code. AI companies have championed the digital watermark as a means of combating concerns that AI-generated images and videos will end up blurring the line between authentic and generated content, with everyone from OpenAI to Meta pledging to work on the technology, Wired magazine reported.

Just when you thought modern life couldn't get any crazier, a video emerged during the run-up to the recent UK election, in which the Prime Minister Boris Johnson appeared to endorse his political opponent Jeremy Corbyn. "Appeared" is the important word here, because this was actually just one of the latest in a steady stream of deepfakes – video and audio clips in which artificial intelligence simulates real people doing unreal things. Of course, humans have been faking it for centuries. From tattoos and piercings to face paints and wigs, we love altering ourselves and indulging in a bit of make-believe. My own little secret for years was that I wore green-coloured contact lenses. I did need them for short-sightedness – the colour was purely a personal choice.

We all know about machine learning when it comes to Japanese droids or Rhoomba intelligent vacuum cleaners, but how is machine learning being used in finance and fintech? As you will discover, the use of machine learning is both prolific and amazing. We will soon look back and wonder how we lived without machine learning. "Machine learning will automate jobs that most people thought could only be done by people." The brilliant way that machine learning has been implemented to help protect against fraud is amazing when you consider the sheer weight of staff/human time required to do the same job.

Dr. Akli Adjaoute, CEO of Brighterion, wrote this AI-focused piece as part of our 2018 year-end eBook. On Dec. 3, 2018, the U.S. Treasury's FinCEN and Federal Banking agencies issued a joint statement encouraging innovative industry approaches to combating money laundering, terrorist financing and other illicit financial threats. As a result, anti-money laundering (AML) has been occupying the headlines as of late. The financial industry has paid $321 billion in fines just through the end of last year, as estimated by Boston Consulting Group. JPMorgan had to pay more than $2 billion in fines due to violation of the Bank Secrecy Act, tied in part to the infamous Bernie Madoff scheme.

Naver Labs, the research subsidiary of South Korean search giant Naver, has opened the patent and design for its robotic cart, dubbed AIRCART, the company announced. Third-party developers will be able to use an open kit provided by the firm sometime within the first half of next year to create related robotic products, the company said. The kit will have the source code, circuit design board, and user guide for the patents. AIRCART is an electronic cart with physical human-robot interaction technology applied that augments strength. A strength sensor on the handle reads the user's intention and controls power and direction, and the user can then move heavy items with little exertion.

Morgan Stanley is on a mission to combine the best of machine learning, predictive analytics and workflow technology with the human touch provided by its 16,000 financial advisers. Despite the popularity of robo-advisers, clients still want a human being to help them navigate complex life questions, according to Naureen Hassan, chief digital officer for wealth management at Morgan Stanley. Recent studies show that 82% of millennials who work with a financial adviser want more time with that adviser, not less, Hassan said. At the same time, clients also want a simple mobile app to keep track of everything when these decisions have been made. "I don't want to be forced into in-person meetings or shipping and signing a bunch of paperwork," Hassan said.

One thing that makes ISIS so hard to fight is that the terrorist network is diffuse and scattered, with small cells of operatives all over the world. Not only does this make it hard for law enforcement to predict where the group might strike next; it makes it incredibly complicated to track activity on the network--activity like banking transactions. Small sums of money flow from foreign fighter to foreign fighter, yet banks struggle to identify it within their systems. Banks have long used anti-money laundering systems to flag suspicious activity, and in the aftermath of September 11th, they have turned to those same legacy tools to catch terror-related transactions, too. But these legacy tools are not up to the job.