Banks tend to use customer analytics to cross-sell products to consumers and do things that benefit their own bottom line. Doing so might not help profits, but it might make for more loyal customers, says wallet.ai's Green, who formerly worked at Intuit, wants to help consumers benefit from their account data, just as Wall Street firms benefit from buying anonymized data. Banks' customer analytics programs are typically set up to learn about customer behavior in order to market them certain products. Green recalled an event where he spoke on this topic -- bankers in the audience accused him of being anti-marketing.

If you use your credit card to buy a latte in Vancouver and a couple of minutes later that card is making a purchase in Singapore, that's a red flag for fraud. But increasingly sophisticated fraud calls for more sophisticated measures to deal with it, and that is among the challenges behind RBC Research's announcement today that it is launching a new lab to explore the use of artificial intelligence and machine learning in the financial sector. Richard Sutton, a computer scientist and pioneer in artificial intelligence, has been named head academic advisor to RBC Research in machine learning. The new lab will work with the Alberta Machine Intelligence Institute at the University of Alberta, where Sutton is a professor. Foteini Agrafioti, head of RBC Research, which was launched last fall in Toronto, said the announcement will help her organization to play a major role in advancing AI research in the future of banking. Agrafioti said that as the complexity of fraud evolves over time, it becomes increasingly difficult to detect it.

Mountain View, California-based Drive.ai is a startup created by former lab mates from Stanford University's Artificial Intelligence Lab. Originally founded in 2015 by Carol Reiley and Fred Rosenzweig, Drive.ai raised $12 million in Series A funding earlier this year to develop deep learning algorithms to control the operation of autonomous vehicles. Building on experience gained from the DARPA Grand Challenge, Google and other self-driving pioneers programmed the first self-driving car to rely primarily on light detection and ranging (LIDAR), which is a remote sensing method that uses pulses of laser light to measure distances, and detailed mapping. Although this has worked pretty well, the current technology is expensive. Making autonomous vehicles easier to manufacture with less expensive parts will make them more affordable.

Putting your future at your fingertips: read this article and thousands more about emerging technology and it's impact on your life, your business and your society at www.globalfuturist.org. As many companies, large and small will tell you, creating a good artificial intelligence (AI) is difficult, really difficult, and for companies such as Alibaba, Facebook, Google, IBM and Microsoft where AI could literally make or break their futures it's a battle they have to win. And now the team at Google's AI research lab, Google Brain, think they have the answer – get AI's to design and build new AI's, and they're not alone – late last year Facebook also hoped on the same bandwagon and were already ahead of the curve. What could possibly go wrong with that great idea!? If you were one of the people who said "nothing" and "that sounds like a great idea" then you might want to go and stand in the corner with everyone else who said that – and it's a lonely corner.

Reading through all of the 2017 predictions about Artificial Intelligence set out by tech publications the world over, it can be easy to think that we are all about to experience a series of seismic changes. The impact of the upcoming discoveries and inventions can feel so overwhelming, so immeasurable that, really, you're more than likely setting yourself up for disappointment by virtue of allowing yourself to dream. We've been promoting improved digitalization in the workplace, and extolling the virtues of Artificial Intelligence tools for a while. With that experience in mind, we like to think that we're fairly grounded when it comes to thinking about the possible impact of AI on wider industries over the coming year. From experience, we have seen that more companies have been switching on to the power of Artificial Intelligence, and to the importance of digital transformation, over the last few years.

The internet was supposed to become an overwhelming democratizing force against illiberal administrations. It was supposed to open repressed citizens eyes, expose them to new democratic ideals and help them rise up against their authoritarian governments in declaring their basic human rights. It was supposed to be inherently resistant to centralized control. In fact, in many countries, the internet, the very thing that was supposed to smash down the walls of authoritarianism like a sledgehammer of liberty, has been instead been co-opted by those very regimes in order to push their own agendas while crushing dissent and opposition. And with the emergence of conversational AI -- the technology at the heart of services like Google's Allo and Jigsaw or Intel's Hack Harassment initiative -- these governments could have a new tool to further censor their citizens.

The apocalyptic future shown in sci-fi films--the ones where robots have gain consciousness and destroy humanity--is not one you need to worry about according to a report from the United States Department of Defense. The document, produced by JASON--an independent advisory group comprised of scientists and experts that brief the government on matters of science and technology--outlines trends in the field of artificial intelligence as it pertains to the U.S. military. According to the report, most computer scientists believe the possible threats posed by AI to be "at best uninformed" and those fears "do not align with the most rapidly advancing current research directions of AI as a field." It instead says these existential fears stem from a very particular--and small--part of the field of research called Artificial General Intelligence (AGI), which is defined as an AI that can successfully perform any intellectual task that a human can. The report argues we are unlikely to see the reality of an AGI come from the current artificial intelligence research and the concept "has high visibility, disproportionate to its size or present level of success."

Scientists have teamed up in a $27 million global initiative to ensure that artificial intelligence doesn't turn against humanity. The MIT Media Lab and the Berkman Klein Center for Internet and Society at Harvard University are spearheading the effort, serving as the founding institutions. As AI becomes increasingly integral in our everyday lives, the researchers say it is necessary to bridge the gap between humans and machines, while preventing the'plagues' of society from being adopted in the process. Scientists have teamed up in a $27 million global initiative to ensure that artificial intelligence doesn't turn against humanity. The initiative, known as the Ethics and Governance of Artificial Intelligence Fund, is backed with $27 million from the Knight Foundation, LinkedIn co-founder Reid Hoffman, the Omidyar Network, the William and Flora Hewlett Foundation, and Jim Pallotta, founder of the Raptor Group.

Are you ready to put your organization on a path of continuous improvement using the most valuable decision support techniques? Check out Microsoft Senior Program Manager Christian Berg's timely series of essays on how to become your organization's strategic advisor using Machine Learning and Power BI, available on the Community Blog. Each post takes on a different aspect of business intelligence, and includes a how-to section to get you started creating customized solutions for your team. Most analysis in the posts is done using the R language, but Christian tries to keep any scripts generic enough that anyone can apply them to their own data even without prior hands-on R experience. The posts also share examples of how businesses use these techniques today to drive deeper insights and better outcomes across a variety of scenarios and industries.

Elon Musk was right when he said that Artificial Intelligence (AI) systems and automation will eventually take over most human jobs and, in what can be seen as a first case in India where the country's software giant Infosys has "released" 8,000-9,000 employees in the past one year because of automation of lower-end jobs, which is confirmed by the company's human resources head Krishnamurthy Shankar in a statement to ET. Notably, these released employees are now working on more advanced projects, so its not that automation or AI has stole the human jobs but it actually transforming at least in this case of Infosys. Machine learning and Artificial Intelligence previously required expensive computing machines, but costs have now come down dramatically. As part of its Automation, Artificial Intelligence and machine learning adaptation drive, the company has been releasing about 2,000 people every quarter and also training them in special courses that will help them in their new assignments. In a research report, released by Infosys itself said that the majority -- 85 percent -- plan to train employees about the benefits and use of AI, and 80 percent of companies replacing roles with AI technologies will retrain or redeploy displaced employees. The report also predicts that organizations that have already deployed or have plans to deploy AI technologies expect to see a 39 percent average increase in revenue by 2020, alongside a 37 percent reduction in costs.