England

AI has been talked about since the very early days of computing and has attained mainstream use in recent years with the likes of Amazon's Alexa and Apple's Siri. "Just as in the last 40 years, computation has enabled us to change the way we do business and create new products, AI will help us to make better decisions," Carlos Kuchovsky, chief of technology and R&D at BBVA, tells Finextra. "We are now looking at the ways in which it can help us change the way we operate and bring value." The Bank of England has recently reported that machine learning tools are in use at two thirds of UK financial firms, with the average company using it two business areas, which is expected to double in the next three years. It may be through interoperation with cloud and blockchain technology that AI's capabilities will be fully harnessed.

The University of Toronto and the affiliated Vector Institute for Artificial Intelligence have announced the recruitment of two rising stars in machine learning research as part of a continued drive to assemble the best AI talent in the world. Chris Maddison and Jakob Foerster will both come to U of T having completed their doctoral research at the University of Oxford. He earned his undergraduate and master's degrees in computer science at U of T – the latter under the supervision of University Professor Emeritus Geoffrey Hinton. A senior research scientist at Google-owned AI firm DeepMind, Maddison will join U of T's departments of computer science and statistical sciences in the Faculty of Arts & Science as an assistant professor next summer. Foerster, a research scientist at Facebook AI Research, will start as an assistant professor in the department of computer and mathematical sciences at U of T Scarborough in fall of 2020.

Machine learning technology is poised to be huge thing in financial services. In fact, two-thirds of UK-based firms are already using it. That is according to two of the UK's top financial regulators. The Financial Conduct Authority (FCA) and the Bank of England have taken a deep dive into how the financial services industry in the country is using machine learning. The research is based on a survey sent out to 300 firms, including banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms.

An autonomous boat under developments could be the first ship to cross the Atlantic that is able to navigate around ships and other hazards by itself. The Mayflower Autonomous Ship (MAS) is an autonomous vessel due to depart from Plymouth in England on the fourth centenary of the original Mayflower voyage, on 6 September 2020, with its destination Plymouth, USA. The project was put together by marine research and exploration company ProMare in an effort to expand the scope of marine research. The boat will carry three research pods equipped with scientific instruments to measure various phenomena such as ocean plastics, mammal behaviour or sea level changes. IBM has now joined the initiative, and it will supply technical support for all navigation operations.

A fully autonomous ship called the "Mayflower" will make its voyage across the Atlantic Ocean next September, to mark the 400-year anniversary of the trip of the first Mayflower, which was very much not autonomous. It's a stark way to drive home just how much technology has advanced in the last four centuries, but also a key demonstration of autonomous seafaring technology, put together by marine research and exploration organization Promare and powered by IBM technology. The autonomous Mayflower will be decked out with solar panels, as well as diesel and wind turbines to provide it with its propulsion power, as it attempts the 3,220-mile journey from Plymouth in England, to Plymouth in Massachusetts in the U.S. The trip, if successful, will be among the first for full-size seafaring vessels navigating the Atlantic on their own, which Promare is hoping will open the doors to other research-focused applications of autonomous seagoing ships. To support that use case, it'll have research pods on board while it makes its trip. Three to be specific, developed by academics and researchers at the University of Plymouth, who will aim to run experiments in areas including maritime cybersecurity, sea mammal monitoring and even addressing the challenges of ocean-borne microplastics.

How are experts looking at the same present and arriving at such different and contradictory futures? Here's a look at five scenarios, and the paths that getting there might take. As artificial intelligence becomes more powerful, a lot of current jobs are doomed to disappear. University of Oxford researchers in 2017 estimated that nearly half of all U.S. jobs were at risk from AI-powered automation. Other forecasts come up with different estimates, but by any measure, the number of lost jobs is potentially huge. Automation has already made manufacturing, mining, agriculture and many other industries much less labor-intensive. One study estimated that from 1993 to 2007, each industrial robot replaced 3.3 workers.

If you thought taking a few machine learning courses on Udemy might be enough to inure you against future unemployment then yesterday's report on machine learning in financial services from the Bank of England and Financial Conduct Authority (FCA) will come as a bit of a shock. The report is based on a survey of 106 banks and finance firms in London. It turns out that, yes, machine learning is being used in banks. But, no, it's not hard to find anyone to fill the roles and that this is the least of the worries as machine learning is rolled out across the finance sector. The charts below, from the report, show where machine learning (ML) is already most in use in the banking sector (defined as building societies, international banks, retail banks, UK deposit takers, and wholesale banks) and in the investments and capital markets sector (defined as alternatives, corporate finance firms, fund managers, principal trading firms, wealth managers and stockbrokers, and wholesale brokers.)

Machine learning tools are now in use at two-thirds of UK financial institutions, with the technology entering a new phase of maturity and more advanced stages of deployment, according to a survey conducted by the Bank of England.

Machine learning technology is poised to be huge thing in financial services. In fact, two-thirds of UK-based firms are already using it. That is according to two of the UK's top financial regulators. The Financial Conduct Authority (FCA) and the Bank of England have taken a deep dive into how the financial services industry in the country is using machine learning. The research is based on a survey sent out to 300 firms, including banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms.

Who's involved: German re/insurer Talanx and US-headquartered automation software provider, WorkFusion. What's happening: Talanx and WorkFusion have agreed a strategic partnership. In an initial step, the software from WorkFusion is being used for automated checking and processing in the claims division at Talanx's subsidiary HDI. The software will initially be used for invoices dealing with glass breakage and motor insurance. Significance of development: Talanx has described the new software as "automation 4.0" because the artificial intelligence platform can take end-to-end decisions, known as Intelligent Process Automation.