Computers are getting pretty good at predicting the future. In many cases they do it better than people. That's why Amazon uses them to figure out what you're likely to buy, how Netflix knows what you might want to watch, the way meteorologists come up with accurate 10-day forecasts. Now a team of scientists has demonstrated that a computer can outperform human judges in predicting who will commit a violent crime. In a paper published last month, they described how they built a system that started with people already arrested for domestic violence, then figured out which of them would be most likely to commit the same crime again.

It is the goal of the proposed workshop to bring together researchers from the fields of machine learning and statistical physics in order to discuss the new challenges originating from dynamical data. Such data are modeled using a variety of approaches such as dynamic belief networks, continuous time analogues of these – as often used for disordered spin systems in statistical physics –, coupled stochastic differential equations for continuous random variables etc. The workshop provides a forum for exploring possible synergies between the inference and learning approaches developed for the various models. The experience from joint advances in the equilibrium domain suggests that there is much unexplored scope for progress on dynamical data.

March 21, 2016– AliveCor, Inc., the leader in FDA-cleared ECG technology for mobile devices, announced today the appointment of two former Google leads, Frank Petterson and Simon Prakash. Petterson joins AliveCor as the company's Vice President of Engineering and Prakash as Vice President of Products and Design. Together they will drive the development of products that will continue to enable people and doctors worldwide to proactively manage heart conditions, anywhere anytime. They will lead engineers and data scientists to disrupt the standard of cardiac care and support the company's expansion into the new Wearable MedTech space, pioneered by AliveCor. "I am inspired by AliveCor's mission and vision of bringing together healthcare, wearable technology, and machine learning to create the'Wearable MedTech' category and I look forward to contributing to the goal of creating technology that will make a difference in millions of lives around the world," said Frank Petterson, vice president of engineering of AliveCor.

Will a robot steal your job or help make you a better one? The evidence points to the increased role of automation in the workplace: as many as 70 per cent of executives plan to significantly increase their investments in AI-related technologies, according to consultant Accenture. What's the best way to take advantage of robotics, automation, and AI? And how can CIOs help the business to evaluate these opportunities and create a boost in productivity and performance? How can executives best understand the role of the robots?

Robots are very fascinating entities, and they have always been one of the foremost subjects of science fiction. The very name robot originated in science fiction writing, although one could argue that the notion of autonomous mechanical artifacts has a very long tradition that predates science fiction. The golden age of robots in science fiction was probably a few decades ago. Unfortunately as the developments in robotics have lagged well behind of what the sci-fi writers had made us to expect, the interest in robots has somewhat cooled off. However, the first low-scale commercial robots are finally making their mark, and the robotic parts are well within the reach of most casual hobbyists and enthusiasts.

Despite the various, and staggering, leaps made by computer scientists, critics argue that machines will never truly match humans until they gain consciousness. Considered a uniquely human trait, consciousness includes being sentient and self-aware, as well as aware of your surroundings. However, many scientists argue animals are as conscious as humans, and the theory of Phi could one day be used to determine if droids are capable of showing such behaviour. Matthew Davidson, PhD Candidate in the neuroscience of consciousness at Monash University has explained what the Phi theory is, and why it is significant, in an article for The Conversation. How and why circumstances may give rise to consciousness remain some of the most puzzling questions in science. Do you think that the machine you are reading this story on, right now, has a feeling of'what it is like' to be in its state?

Giant manta rays have been filmed checking out their reflections in a way that suggests they are self-aware. Only a small number of animals, mostly primates, have passed the mirror test, widely used as a tentative test of self-awareness. "This new discovery is incredibly important," says Marc Bekoff, of the University of Colorado in Boulder. "It shows that we really need to expand the range of animals we study." But not everyone is convinced that the new study proves conclusively that manta rays, which have the largest brains of any fish, can do this – or indeed, that the mirror test itself is an appropriate measure of self-awareness. Csilla Ari, of the University of South Florida in Tampa, filmed two giant manta rays in a tank, with and without a mirror inside.The fish changed their behaviour in a way that suggested that they recognised the reflections as themselves as opposed to another manta ray.

In this post I consider three learning approaches and argue that it could be a bad idea to avoid the mathematics and theory when starting out with machine learning. There are three approaches to starting out in machine learning that I have seen practiced. One is a bottom-up approach, in which the student starts with the mathematics and theory and then puts it into practice in either a high-level programming language -- such as Matlab, Python, R or Octave -- or by coding from scratch in a 3GL like Java, C# or C . The second is the top-down approach, in which machine learning tools and/or libraries are used to shelter the student from the coding, mathematics and theory. S/he is instructed to worry about how it all works later and to instead practice working with datasets.

Dan Chao is an avid cyclist who likes to train on a stationary bike. Lately while training he's been sporting a pair of trendy-looking headphones that also stimulate his brain. And he says the device has helped him improve his performance on his real bike. Chao is a cofounder and the CEO of a startup called Halo Neuroscience, which released the neurostimulating headphones, called Halo Sport, last month. The arch of the headphones contains two electrodes that deliver a very small amount of electric current to the wearer's head, aimed at the neurons in the motor cortex, a brain region that coördinates movement. The mild stimulation, called transcranial direct current stimulation, essentially makes it "slightly easier for the neurons to fire," says Chao.

This was the title of a very popular book published in 2012, featuring several job interview questions (brain teasers) asked by Google's hiring managers to candidates. They apparently dropped all these questions, as they found out that they were not good indicators of career success. Do you think you are smart enough to work for Google? I had one phone interview with Google long ago, and was rejected right away. The interviewer was just focused on very technical details, and spent all her time arguing about Lasso regression, and was clearly looking for a specialist, dismissing people with a broad range of skills and non-standard approach to solving tech problems.