Possible applications of A/I in asset and wealth management are endless and impact the entire value chain. Imagine sentient, real time optimization of sales and marketing interactions and client services, predictive market modeling based on instantaneous processing of teraflops of data, self-creating exchanges with complete price transparency. It is not unrealistic to think that research analysts will have their own bots using real time big data to do a majority of their market and financial analysis, and even assembly of reports and recommendations to the CIO. Laborious trade reconciliation could be a thing of the past, with AI bots on both ends of the transaction across back, middle and front office doing it all and alerting humans only in rare cases of disputes. If (or when) quantum computing becomes pervasive all trading, investment and distribution decisions could be done through bots leaving asset and wealth managers free to focus more on client relationships and business strategy.

The Bharat Bandh on April 2 called by Dalit groups was a result of the successful use of artificial intelligence (AI), the geographic information system (GIS) and big data, according to a core group of US-based Dalit activists. The protest, which surprised many because of its sudden eruption, was organised against the alleged dilution of the SC/ST (Prevention of Atrocities) Act. New Jersey-based Deelip Mhaske, who heads a secretive network of some 100 overseas Dalit activists based in the US, the UK, Australia and the Middle East said the protest shows that Dalits no longer need to be affiliated to any political establishment. "A new era for Dalit politics has begun by adopting artificial intelligence, the GIS and social media," Mhaske told PTI in an interview as he gave an insight into how Dalit groups were mobilised during the protest. Most of these Dalit activists in the secretive group are from the IT sector and work in some of the top info-tech companies.

New developments in artificial intelligence do not yet need specific new laws to control possible harmful effects, a landmark inquiry by peers recommends today. However the House of Lords Select Committee on Artificial Intelligence's 180-page report proposes that the government draft an international ethical code - which would include a ban on autonomous weapons, so-called'killer robots'. In researching the report, the lords' investigation took evidence from a wide range of ethical and legal experts, including the Law Society, law firms and Gazette columnist Joanna Goodman, as well as figures from industry and academia. Its overall finding was that the UK is in a strong position to lead developments, with its'constellation of legal, ethical, financial and linguistic strengths'. However committee chair Lord Clement-Jones (DLA Piper partner Timothy Clement-Jones) noted that: 'AI is not without its risks and the adoption of the principles proposed by the committee will help to mitigate these.'

The dependency on digital and smart technology these days is on the rise, on top of that there are issues of ransomware and distributed denial of service (DDoS), the average number of focused cyberattacks per organization has more than doubled this year compared to the previous 12 months (232 through January 2018 versus 106 through January 2017). A new research conducted by Accenture has concluded that in spite of these growing cyber threats, the organizations are demonstrating far more success in detecting and blocking them. It was revealed that despite making significant progress, only two out of five organizations are currently investing in breakthrough technologies like machine learning, artificial intelligence (AI) and automation, indicating there is even more ground to be gained by increasing investment in cyber resilient innovations and solutions. The study conducted from January to mid-March 2018 investigated focused attacks defined as having the potential to both penetrate network defenses and cause damage, or extract high-value assets and processes from within organizations. Regardless of the increased pressure of ransomware attacks, which more than doubled in frequency last year, the study disclosed that organizations are upping their game and now preventing 87 percent of all focused attacks compared to 70 percent in 2017.

The U.S. Defense Department (DOD), which is trying to improve the military's artificial intelligence capabilities, is considering setting up a joint office focused on just that. "We would we concentrate all of DOD's efforts since we have a number of AI efforts underway right now," Mattis testified before the U.S. House Armed Services Committee. Mattis made his comments in response to a question from Rep. Seth Moulton, who expressed concern that China aims to match U.S. artificial intelligence (AI) capabilities by 2020 and exceed them by 2030. A DOD spokesperson declined to elaborate on the potential joint office. But according to the Pentagon's new national defense strategy, AI is one of a host of technology areas that need more investment to ensure the U.S. military keeps its edge.

Pentagon technology chief Mike Griffin last week announced US military plans to form an office dedicated to procuring and deploying artificial intelligence technology. Meanwhile, the White House still doesn't have a science adviser. The US military appears to embrace AI at every strategic level, and the creation of a new office to manage the burgeoning technology is further evidence that machine learning is the future of warfare. According to Federal News Radio's Eric White, Under Secretary Griffin and fellow top brass are "alarmed at recent advances" in the field of artificial intelligence and seek to form the office as a matter of national security. US House members are also concerned about such developments, having recently introduced a bill that would allocate millions of dollars toward researching artificial intelligence with the intent of providing a study for the president to review next year. The White House, for its part, has been peculiarly silent on the subject of AI, leaving some to speculate the idea of operating a democracy without a qualified science adviser is a bad one.

Members of the House of Lords have called for an artificial intelligence code of conduct in the UK. The House of Lords Select Committee on Artificial Intelligence, in a report titled AI in the UK: Ready, Willing and Able?, argued that the UK can lead the world in AI, as long as it puts ethics at the centre of its plans. The Committee recommended five principles guiding how researchers and businesses develop artificially intelligent systems in the UK. As part of its report, the Lords have called for these principles to be formulated into a cross-sector AI code to be adopted internationally as well as in the UK. Commenting on the report, the Committee's chairman, Lord Clement-Jones, said: "The UK has a unique opportunity to shape AI positively for the public's benefit and to lead the international community in AI's ethical development, rather than passively accept its consequences."

An artificial intelligence device that can detect diabetic eye problems has been approved by The Food and Drug Administration (FDA) of the United States. It allows the doctors to diagnose the condition without the need for any data or images. An artificial intelligence algorithm is used by the device to analyze images of the eye, taken with a retinal camera Topcon NW400. The image is then uploaded to a cloud server on which IDx-DR software is installed. The IDx-DR software scans the image and subsequently responds to the condition of the patient's eye.

Data breaches and cyber attacks have become harder to deter over the last few years. According to Cisco's 2018 Annual Cybersecurity Report, for example, the expanded volume of both legitimate and malicious encrypted traffic on the web has made it more difficult for security professionals to recognize and monitor potential threats. As a result, many security professionals are looking to leverage machine learning to advance cybersecurity. Before exploring the ways machine learning can improve cybersecurity, it is important to first understand what machine learning actually is. To begin with, machine learning is not one in the same with artificial intelligence (A.I.), which is part of a broader initiative to enable computers to reason, solve problems, perceive and understand language.

The most desirable career of the 21st century, with numerous advantages over other fast-growing occupations such as hospice carer and rickshaw driver, is being a billionaire. Prior to the incorporation of US Steel in 1901, the world didn't have a single billion-dollar company, much less a billion-dollar individual. Today, more people than ever are becoming billionaires – 2,000 and counting have made the great leap upward, according to the "global wealth team" at Forbes. And the US's hottest billionaire factory is located in the most hyped yet least understood swath of suburban sprawl in the world: Silicon Valley. Despite what you may have heard, hard work in your chosen trade is absolutely the stupidest way to join the billionaires club. In Silicon Valley, the world's most brilliant MBAs and IT professionals discovered a shortcut to fabulous riches. Ambitious Ivy Leaguers who once flocked to Wall Street are now packing up and heading west. The Valley's startup founders, investors, equity-holding executives and fee-taking middlemen have thrived above all. Inspired by their success, my idea was to move to Silicon Valley, pitch a startup and become obscenely rich. I left home with some homemade business cards showing my new email address, futurebillionaire@aol.com, The first thing I needed was a place to stay.