To date, the instability of prognostic predictors in a sparse high dimensional model, which hinders their clinical adoption, has received little attention. Stable prediction is often overlooked in favour of performance. Yet, stability prevails as key when adopting models in critical areas as healthcare. Our study proposes a stabilization scheme by detecting higher order feature correlations. Using a linear model as basis for prediction, we achieve feature stability by regularising latent correlation in features. Latent higher order correlation among features is modelled using an autoencoder network. Stability is enhanced by combining a recent technique that uses a feature graph, and augmenting external unlabelled data for training the autoencoder network. Our experiments are conducted on a heart failure cohort from an Australian hospital. Stability was measured using Consistency index for feature subsets and signal-to-noise ratio for model parameters. Our methods demonstrated significant improvement in feature stability and model estimation stability when compared to baselines.

They are the APAC and Australian leaders of some of the largest, or fastest rising marketing tech, adtech and ecommerce companies. And they are passionate about helping their clients understand their own consumers using data analytics. So we figured it was time to turn the lens around. We used IBM's Personality Insight services in the Watson Developer Cloud to tell us a little bit about the personality of each of the following executives; Karen Stocks from Twitter, Ben Sharp from AdRoll, Liam Walsh from Amobee, Jodie Sangster from ADMA, Paul Robson from Adobe, Derek Laney from Salesforce, Paul Cross from Oracle, Matt Barrie from Freelancer and Ruslan Kogan from Kogan. Given their commitment to the cause of data-driven marketing we are sure they won't mind at bit.

Taban Deng Gai, who is now first vice president of South Sudan, speaks to reporters in Ethiopia's capital Addis Ababa on Jan. 8, 2014. In an interview airing on Monday's PBS NewsHour, South Sudan Vice President Taban Deng Gai responded to a report that the country's top leaders were profiting off the five-year conflict by saying it's under investigation, but the report might be false. Human rights group The Sentry this month released the results of a two-year investigation that found South Sudanese politicians were spending international aid on mansions and fancy cars, and giving expensive contracts to family members. "They say that my president, for example, they accuse him of having a house in one of the suburbs of Nairobi city. I don't think a crime for a president -- a sitting president for more than 10 years" to have a house there, Deng told PBS NewsHour Weekend anchor Hari Sreenivasan.

Researchers from New Zealand have restored the very first recording ever made of computer generated music. The three simple melodies, laid down in 1951, were generated by a machine built by the esteemed British computer scientist Alan Turing. Computer scientist Alan Turing is primarily remembered for being the father of artificial intelligence and for hacking the Nazi Enigma machine during the Second World War, but as the co-purveyor of the Church-Turing thesis, he recognized the ability of computers to do just about anything--including making music. With the help of BBC broadcasters, Turing made history by being the first person to use a computer to generate music, and then record that music to a storage medium--in this case a 12-inch acetate disc. Turing created the music at the Computing Machine Laboratory in Manchester, England, on a primitive device that occupied nearly an entire floor.

Researchers from New Zealand have restored the earliest known recording of computer-generated music, which was created nearly 65 years ago on a gigantic computer devised by the famous Alan Turing. Researchers from the University of Canterbury in Christchurch restored the recording created in 1951 using a BBC outside-broadcasting unit and a portable acetate disk. The recording, which begins with the United Kingdom's "God Save the Queen," also includes the nursery rhyme "Baa Baa Black Sheep" and the Glenn Miller hit "In The Mood." "Today all that remains of the recording session is a 12-inch single-sided acetate disc, cut by the BBC's technician while the computer played. The computer itself was scrapped long ago, so the archived recording is our only window on that historic soundscape," the researchers said in a statement Monday. The recording captured on the acetate disk was originally played on a massive computer, which occupied most of the ground floor of Turing's Computing Machine Laboratory.

A robot has been detained by police at a political rally in Moscow, with authorities attempting to handcuff the machine. The rally was for Valery Kalachev, a candidate for the Russian Parliament, who had rented the robot for his campaign. Police have not confirmed why they detained the machine named Promobot, but local media was reporting the company behind the robot said police were called because it was "recording voters' opinions on [a] variety of topics for further processing and analysis by the candidate's team". A Promobot representative suggested it was detained because "perhaps this action wasn't authorised". Mr Kalachev has featured the robot at previous campaign stops.

Disruption in the workforce is hardly a new phenomenon. Mechanisation of manufacturing, mass production and the advent of the internet and computers have all changed the way that work is done. Earlier waves of industrialisation have primarily affected low-skilled manual labour and past improvements in technology have typically made jobs at the lower end of the skills spectrum obsolete – for example, flight navigators but not pilots; typists but not data analysts. There is wide acceptance that this has led to productivity improvements and higher economic growth – new jobs were generated that led to improvements in standards of living. The benefits have overwhelmingly outweighed the costs and there has never been a better time to be a human being. The current wave, characterised by automation becoming smarter, machine-to-machine communication, artificial intelligence and continued technological improvements – and otherwise described at the fourth industrial revolution – still brings uncertainty and threatens a broader range of occupations and skill levels.

One of the most important takeways from Davos that quickly became widely spread news, was that the world was about to enter the fourth industrial revolution, resulting from a convergence of a number of big technology changes (autonomous vehicles, sensors, biotechnology, 3D printing, robotics, artificial intelligence). One of the most important technological disruption taking us fast to that extraordinary moment is Deep learning. Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex structures or otherwise, composed of multiple non-linear transformations. Making an analogy with the way the brain works, deep-learning software tries to imitate what happens in our brains, more exactly in the layers of neurons in the neocortex, where thinking takes place. Ultimately deep learning software aims to recognize patterns in digital representations of sounds, images, and other data.

Internet experts and highly engaged netizens participated in answering an eight-question survey fielded by Elon University and the Pew Internet Project from late November 2013 through early January 2014. Self-driving cars, intelligent digital agents that can act for you, and robots are advancing rapidly. Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025? Describe your expectation about the degree to which robots, digital agents, and AI tools will have disrupted white collar and blue collar jobs by 2025 and the social consequences emerging from that. Among the key themes emerging from 1,896 respondents' answers were: - Advances in technology may displace certain types of work, but historically they have been a net creator of jobs. This page holds the content of the survey report, which is an organized look at respondents elaborations derived from 250 single-spaced pages of responses from ...

Intelligence is shaped by the survival requirements that an animal must face during its everyday life, according to cognitive ecology. Some birds can remember where they buried tens of thousands of nuts and seeds, which allows them to find them during the long winter months; a burrowing rodent can learn a complex underground maze with hundreds of tunnels in just two days; and a crocodile can have the presence of mind to carry sticks on her head and float them just below an area where herons are nesting, then pounce when an unwary bird swoops down to collect nesting material. Notwithstanding the liberties taken by filmmakers in popular movies like The Little Mermaid, Finding Nemo, and its sequel, Finding Dory, can fishes really think? When the tide goes out, frillfins like to stay near shore, nestled in warm, isolated tide pools where they may find lots of tasty tidbits. But tide pools are not always safe havens from danger. Predators such as octopuses or herons may come foraging, and it pays to make a hasty exit. But where is a little fish to go? Frillfin gobies deploy an improbable maneuver: They leap to a neighboring pool. How do they do it without ending up on the rocks, doomed to die in the sun? With prominent eyes, slightly puffy cheeks looking down on a pouting mouth, a rounded tail, and tan-gray-brown blotchy markings along a 3-inch, torpedo-shaped body, the frillfin goby hardly looks like a candidate for the Animal Einstein Olympics.