SYDNEY – After applying his machine-learning programs to central bank policy statements to churn out trading calls, a hedge fund-backed political economy specialist is aiming his sights on corporate earnings announcements. Evan Schnidman, a 31-year-old who set up his own firm after a Harvard University Ph.D. dissertation that looked at the Federal Reserve's communications, is hoping the approach that lured $3.3 million in a fundraising round last December will work in the corporate sphere. St. Louis-based Prattle has until now focused on applying the artificial intelligence method known as natural-language processing to make assessments of Fed and other central bank policy statements. At a time when analysis is poised to get its own price tag, with the introduction of Europe's MiFID II regulations, research costs are an increasing focus for investment banks and asset managers. BlackRock Inc. has even moved to use robots to design funds.

A Shanghai company has claimed to have developed an AI that can recognize a face among at least two billion people in a matter of seconds. Yitu's AI algorithm Dragon Eye not only recognizes faces but with a network of connected cameras can plot the movement of their owners. "Our machines can very easily recognize you among at least two billion people in a matter of seconds," says chief executive and Yitu co-founder Zhu Long, "which would have been unbelievable just three years ago." As of now, the Dragon Eye platform has around 1.8 billion photographs to work with: those logged in China's national database and those who have ever entered through its borders. Talking to the South China Morning Post, Zhu said the objective of the algorithm is to make the world a much safer place by curbing crime.

Labour's Tom Watson will call on society to "embrace an android" as he argues that the rise of automation in the workplace need not cause mass unemployment and should instead be welcomed. The party's deputy leader will make the comments at the launch of the final report of the Future of Work Commission, which has concluded that people should not fear the "march of the robots". Instead, it claims that if government investment is sensibly targeted, the technological revolution has the potential to reverse the UK's economic decline and create as many jobs as it destroys. Watson, who convened and co-chaired the commission, is expected to say: "Much has been written about the impact of technological change and the dystopian future we could all face as a result of the rise of the robots. "It can sometimes feel like we are preparing for a world in which artificial intelligence, algorithms and automation, rather than human endeavour and hard work, will shape every aspect of our society and our economy.

Despite these efforts, it is clear that there remain real vulnerabilities, and the sluggish nature of government means that it is not responsive enough to what is a rapidly evolving threat. The way to avoid this is, ultimately, by investing heavily in ensuring that old systems are upgraded and to stop treating information security as an afterthought. This is no easy feat. The Federal government is a behemoth with millions of workers, many of whom need to be better trained in good practice. There needs to be more invested in blockchain and machine learning as a means of cyber security - many agencies even still lack cloud systems.

But that job is suddenly looking iffy as A.I. gets better at reading scans. A start-up called Arterys, to cite just one example, already has a program that can perform a magnetic-resonance imaging analysis of blood flow through a heart in just 15 seconds, compared with the 45 minutes required by humans. Maybe she wants to be a surgeon, but that job may not be safe, either. Robots already assist surgeons in removing damaged organs and cancerous tissue, according to Scientific American. Last year, a prototype robotic surgeon called STAR (Smart Tissue Autonomous Robot) outperformed human surgeons in a test in which both had to repair the severed intestine of a live pig.

Investment in unmanned aerial systems is soaring, but challenges remain. Here's what stakeholders need to know about the evolving landscape. Most people think of a drone, also known as an unmanned aerial system (UAS), as a sophisticated military technology or a hobbyist's tool for capturing images of foliage, sporting events, and cityscapes. But businesses across industries realize that drones have multiple commercial applications, some of which go beyond basic surveillance, photography, or videos, and they are already using them to transform daily work in some industries. Insurance companies are using drones to inspect damaged assets, for instance, and farmers are sending them to monitor crops and collect soil data.

Originally posted on The Horizons Tracker. As artificial intelligence (AI) has progressed at quite a pace in recent years, it is inevitable that governments have tried to get a handle on things and better understand how it might influence society. For instance, I wrote recently about a report by the British government's Science & Technology Select Committee into AI, which looked at a number of topics, from ethics to employment. Hot on the heels of this is another British government report, this time from the office of the Chief Scientific Advisor. It examines the increasingly blurred lines between big data and AI, and particularly the benefits of this for the state.

While just over a fifth of UK businesses have already invested in Artificial Intelligence (AI), more than eight in every ten executives will do so over the coming years. According to the latest analysis, half of all UK organisations will have sunk over £10 million into digital technology by 2020, as companies look to avoid being left by the wayside amid a period of major innovation. However, concerns regarding a digital skills shortage are hampering efforts to get the most out of AI. A new study from Deloitte has examined the opinions of 51 executives from the UK's most influential companies and public sector entities – worth a combined market value of £229 billion – regarding the implementation of AI in their businesses. The findings of Deloitte's Digital Disruption Index showed that 85% of the leaders responsible for digital technologies intend to invest in AI by the turn of the decade.

Fending off fraudsters is no easy task for banks and credit unions (CUs). That's especially true for smaller financial institutions (FIs) that may not have the resources for a cybersecurity redo. But, can the old adage of working "smarter, not harder" also help those fighting against financial fraud? That's the goal behind a new wave of cybersecurity technology being deployed and adopted by FIs in the United States and around the world. Increasingly, banks, credit unions and financial services firms are turning to new technology like artificial intelligence (AI) and machine learning to help safeguard their customers from breaches like those that have garnered headlines in recent months.

A remarkably inquisitive artificial-intelligence system developed by a team of researchers at NYU has learned to play a game similar to Battleship with mind-blowing skill. In the simple game the researchers created, players seek to find their opponent's ships hidden on a small grid of squares by asking a series of questions that can be answered with a single number or word. Their program figures out how to ask these questions as efficiently as possible. Taking inspiration from cognitive psychology, and using a fundamentally different approach from most of today's AIs, the system shows how machines may learn how to ask useful questions about the world. The program treats questions as miniature programs, allowing it to learn from just a few examples and to construct its own questions on the basis of what it has learned.