Banks around the world are being confronted with a record number of regulations, and those falling short of institutional obligations are paying a high price for their errors. In response, major financial institutions are grasping big data solutions in a bid to comply with often dense regulations and reduce regulatory breaches. "Considering many banks have grown organically, often via merger and acquisition, their data is not always consistent and well organised," according to James Arnett, a partner at business and technology consulting firm Capco. Mr Arnett believes that new tools can be created through the application of data analytics, which will transform banks compliance programmes from manual, non-scalable projects into lower-cost and automated processes. "There is a real opportunity for banking clients to embrace data analytics to answer the underlying theme of regulation strategically rather than to treat each regulation as a'tick-the-box' exercise," he says.

Web users searching for photos and cops looking for suspects in video already benefit from software that understands the content of images. Chris Gibson says it can also make it easier to find treatments for diseases not targeted by existing drugs. "By combining robotics and machine vision, we can work at large scale on hundreds of diseases simultaneously, using a small number of people," says Gibson, who is CEO and cofounder of the 40-person startup Recursion Pharmaceuticals. Recursion uses software to read out the results of high-throughput screening, which automates drug testing in cells. That isn't a new idea, but Recursion uses algorithms that inspect cells at an unusual level of detail.

The increasing use of artificial intelligence (AI) to analyze large patient data sets promises to change the face of population health management in a way that will be far reaching across the industry and a game changer to the way physicians monitor and care for their patients. AI's ability to raise the level of evidence-based medicine can help primary care physicians make better decisions in several areas. These include the ability to determine appropriate treatments for their patients and to how best to monitor their care during and after hospitalization, to improving efficiency and productivity in care team workflows and finding better ways to reduce overall costs associated with patient care. Supercomputers that compare and analyze large groups of patients' clinical data, diagnostic images and claims data, are capable of identifying subtle patterns and changes in health and wellness that can foreshadow the start of an illness, monitor the effectiveness of drug treatments and identify patients' health risks. For example, when researchers at the MRC London Institute of Medical Sciences, wanted to find out which patients with pulmonary hypertension had the greatest risk of heart failure, they used AI software to analyze images of patients' hearts and constructed a smart 3D heart that predicts patient survival rates.

Earlier this month we had CES 2017 in Las Vegas, a techie's mecca of new whiz-bang products set to hit the market, in some cases later this year, but in others in 2018 and beyond. A person tracking the CES trade shows over the years likely remembers the changes in inputs from clunky keyboards and standalone number pads to rollerball driven mice to laser based ones, which gave way to trackpads and touchscreen technology. Among the sea of announcements this year, there were a number that focused on one aspect of our Disruptive Technology investing theme that is shaping up to be the next big change in interface technology -- voice recognition technology. Over the years, there have been a number of fits and starts with voice technology dating all the way back to 1992 when Apple's own "Casper" voice recognition system that then CEO John Sculley debuted on "Good Morning America." As the years have gone by and the technology has been further refined, we've seen more uses for voice recognition technology in a variety of applications and environments ranging from medical offices to interacting with a car's infotainment system.

Shivaram Kalyanakrishnan is an assistant professor in the department of computer science and engineering at the Indian Institute of Technology-Bombay. He specialises in artificial intelligence (AI) and is the only author from India who is part of an 18-member study panel of the Stanford University-hosted report titled Artificial Intelligence and Life. Kalyanakrishnan's expertise broadly fits in the area of machine learning. Called reinforcement learning, it defines what actions software agents should take to maximize a certain type of reward after learning from reward and punishment. In an interview, he urges people to be more optimistic about the things AI can do rather than be obsessed with the fear around AI machines.

IBM has produced a glossy multimedia website (see below) to expound the possibilities under the label "IBM 5 in 5: five innovations that will help change our lives within five years." And analog, MEMS and sensors are prominent. But digital electronics will also have its say in the form of big data and artificial intelligence. The full list is artificial intelligence; hyperspectral imaging; microfluidic lab-on-chips, networks of novel sensors and something IBM calls "macroscoping." Amongst the developments IBM researchers are predicting – and a slightly disconcerting prediction at that – is that what we say and write could be monitored and used as indicators of our mental health and physical well-being. Patterns of speech and writing and how they change over time, analysed by cognitive systems, could provide tell-tale signs of early-stage developmental disorders, mental illness and degenerative neurological diseases.

You're young and want to get ahead. You work weekends and message colleagues with inspired trading ideas at all hours. You've just marked yourself as a potential rogue trader. Welcome to the brave new world of trader surveillance, where former Goldman Sachs research analyst Erkin Adylov is building a library of banking villainy based on the behaviors of hundreds of past miscreants such as UBS Group's Tom Hayes and Societe Generale's Jerome Kerviel. Using thousands of inputs, from stress levels in voice recordings to the frequency of visits to the staff canteen, Adylov and his team at startup Behavox grade employees on how likely they are to go bad before they do anything wrong. While that may sound like something out of a Philip K. Dick science-fiction novel, hedge fund Marshall Wace and interdealer broker TP ICAP are already using the software to monitor employees, and some of the biggest investment banks and commodities dealers in the world have begun testing it.

What initially began as a Facebook event has morphed into a cultural moment, a juxtaposition of the previous day's inauguration of America's 45th president, Donald Trump. Heather Whaling is CEO of Geben Communication, a PR and social media agency with offices in Columbus, Ohio, and Chicago. She serves on the board of The Women's Fund of Central Ohio, mentors women entrepreneurs, and is a vocal advocate for paid parental leave. On the issues, it's increasingly difficult to find commonalities between Trump supporters and the marchers who will flock to DC and other cities around the country. Yet both groups share at least one tool in their toolbox: A mastery of social media as the go-to channel to amplify viewpoints and shape perceptions.

When psychologist Dr. Paul Ekman visited the Fore tribe in the highlands of Papua New Guinea in 1967, he probably didn't imagine that his work would become the foundation for some of the latest developments in artificial intelligence (AI). After studying the tribe, which was still living in the preliterate state it had been in since the Stone Age, Ekman believed he had found the blueprint for a set of universal human emotions and related expressions that crossed cultures and were present in all humans. A decade later he created the Facial Action Coding System, a comprehensive tool for objectively measuring facial movement. Ekman's work has been used by the FBI and police departments to identify the seeds of violent behavior in nonverbal expressions of sentiment. He has also developed the online Atlas of Emotions at the behest of the Dalai Lama.

Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.