It was just a friendly little argument about the fate of humanity. Demis Hassabis, a leading creator of advanced artificial intelligence, was chatting with Elon Musk, a leading doomsayer, about the perils of artificial intelligence. They are two of the most consequential and intriguing men in Silicon Valley who don't live there. Hassabis, a co-founder of the mysterious London laboratory DeepMind, had come to Musk's SpaceX rocket factory, outside Los Angeles, a few years ago. They were in the canteen, talking, as a massive rocket part traversed overhead. Musk explained that his ultimate goal at SpaceX was the most important project in the world: interplanetary colonization. Hassabis replied that, in fact, he was working on the most important project in the world: developing artificial super-intelligence. Musk countered that this was one reason we needed to colonize Mars--so that we'll have a bolt-hole if A.I. goes rogue and turns on humanity. Amused, Hassabis said that A.I. would simply follow humans to Mars. This did nothing to soothe Musk's anxieties (even though he says there are scenarios where A.I. wouldn't follow). An unassuming but competitive 40-year-old, Hassabis is regarded as the Merlin who will likely help conjure our A.I. children. The field of A.I. is rapidly developing but still far from the powerful, self-evolving software that haunts Musk. Facebook uses A.I. for targeted advertising, photo tagging, and curated news feeds. Microsoft and Apple use A.I. to power their digital assistants, Cortana and Siri. Google's search engine from the beginning has been dependent on A.I. All of these small advances are part of the chase to eventually create flexible, self-teaching A.I. that will mirror human learning. Some in Silicon Valley were intrigued to learn that Hassabis, a skilled chess player and former video-game designer, once came up with a game called Evil Genius, featuring a malevolent scientist who creates a doomsday device to achieve world domination.

Here are some incredibly smart people that are pushing boundaries and/or doing some incredibly inventive things in emerging technology and other areas. Whether it's healthcare, news or immersive technologies - these are the people you'll be hearing a lot more from - collaborate with them now and be a bigger part of the future. Burrell was described as "offering new thinking and fresh ideas to strengthen the future of broadcasting" after taking top honors at the National Association of Broadcasters Innovation Pilot Award for "In Your Shoes" (a broadcast and 360 VR series), Recently working with heavy-hitters like Steven Spielberg's virtual reality company ('The VR Company'), Burrell's work with Oculus has been considered for an Interactive Emmy ("Take Back the Mic: The World Cup of Hip Hop"). Recently returning from South Africa where she created a partnership with Ndaba Mandela (grandson to Nelson Mandela and Founder of Africa Rising), to bring the coding, robotics and emerging technology program permanently to the continent. IN HER OWN WORDS: "There's a strong feeling of uncertainty in the world right now, but when we ask ourselves, 'how can I use the the tools of today and the technology of tomorrow to harness something meaningful and good', we are empowered to reshape our experience of the world."

Inspired by biophysical principles underlying nonlinear dendritic computation in neural circuits, we develop a scheme to train deep neural networks to make them robust to adversarial attacks. Our scheme generates highly nonlinear, saturated neural networks that achieve state of the art performance on gradient based adversarial examples on MNIST, despite never being exposed to adversarially chosen examples during training. Moreover, these networks exhibit unprecedented robustness to targeted, iterative schemes for generating adversarial examples, including second-order methods. We further identify principles governing how these networks achieve their robustness, drawing on methods from information geometry. We find these networks progressively create highly flat and compressed internal representations that are sensitive to very few input dimensions, while still solving the task. Moreover, they employ highly kurtotic weight distributions, also found in the brain, and we demonstrate how such kurtosis can protect even linear classifiers from adversarial attack.

We study a variant of the source identification game with training data in which part of the training data is corrupted by an attacker. In the addressed scenario, the defender aims at deciding whether a test sequence has been drawn according to a discrete memoryless source $X \sim P_X$, whose statistics are known to him through the observation of a training sequence generated by $X$. In order to undermine the correct decision under the alternative hypothesis that the test sequence has not been drawn from $X$, the attacker can modify a sequence produced by a source $Y \sim P_Y$ up to a certain distortion, and corrupt the training sequence either by adding some fake samples or by replacing some samples with fake ones. We derive the unique rationalizable equilibrium of the two versions of the game in the asymptotic regime and by assuming that the defender bases its decision by relying only on the first order statistics of the test and the training sequences. By mimicking Stein's lemma, we derive the best achievable performance for the defender when the first type error probability is required to tend to zero exponentially fast with an arbitrarily small, yet positive, error exponent. We then use such a result to analyze the ultimate distinguishability of any two sources as a function of the allowed distortion and the fraction of corrupted samples injected into the training sequence.

Bill Nye the Science Guy became popular for being able to explain science in a simpler fashion. Maybe you've heard the following philosophical question, "if a tree falls in a forest and no one is around to hear it, does it make a sound?" Similarly, if you make a scientific discovery, but no one else understands it, is it really a discovery? Herein lies the importance of scientific communication, especially these days when real science seems to be increasingly the neglected spouse of society, ignored and even under attack from different directions. Dr. Beth Linas, epidemiologist, American Association for the Advancement of Science (AAAS) Science and Technology Policy Fellow at the National Science Foundation, and scientific communication advocate, recently sent me the following Tweet: This furthers the need of training scientists to communicate their science rather than just publishcc @bruce_y_lee https://t.co/2i9XRpfU88 The study that Meg Parker refers to is one by Pontus Plaven-Sigray, Granville James Matheson, Björn Christian Schiffler, and William Hedley Thompson from the Karolinska Institutet entitled "The Readability Of Scientific Texts Is Decreasing Over Time" and posted on bioRxiv from Cold Spring Harbor Laboratory.

But behind every good strategy is good data. Take Korean War veteran and US Air Force officer John Boyd as an example. He was tasked with analysing the outcome of dogfights – aerial battles between fighter planes conducted at close range – and come up with a way to save the lives of more American pilots. What Boyd created was a framework for decision-making that is known as the OODA loop. OODA refers to the recurring cycle of four actions: observe, orient, decide and act.

As Washington fiddles, China is investing billions in U.S. startups with cutting-edge products that could have military applications at the same time it is dialing back investments in less critical American industries such as entertainment. A New York Times story this week says that among the startups are companies working on artificial intelligence for military robots, rocket engines, ship sensors and printers that could produce high-tech components such as computer screens for military jets. Many of the firms making such investments are owned by companies controlled by the Chinese government or connected to its leaders. A blog post last December on the website of CB Insights, which tracks startup investments, says that China poured $9.9 billion into new Silicon Valley firms in 2015 and made an additional $3.5 billion in tech investments in the first nine months of last year. The number and size of those tech investments in startups developing military applications were not broken out.

Washington (AFP) - Are robots coming for your job? Although technology has long affected the labor force, recent advances in artificial intelligence and robotics are heightening concerns about automation replacing a growing number of occupations, including highly skilled or "knowledge-based" jobs. Just a few examples: self-driving technology may eliminate the need for taxi, Uber and truck drivers, algorithms are playing a growing role in journalism, robots are informing consumers as mall greeters, and medicine is adapting robotic surgery and artificial intelligence to detect cancer and heart conditions. Of 700 occupations in the United States, 47 percent are at "high risk" from automation, an Oxford University study concluded in 2013. A McKinsey study released this year offered a similar view, saying "about half" of activities in the world's workforce "could potentially be automated by adapting currently demonstrated technologies."

For centuries, humans have been fretting over "technological unemployment" or the loss of jobs caused by technological change. Never has this sentiment been accentuated more than it is today, at the cusp of the next industrial revolution. With developments in artificial intelligence continuing at a chaotic pace, fears of robots ultimately replacing humans are increasing. However, while AI continues to master an increasing number of tasks, we're still decades away from human jobs going extinct. With AI finding its way into more and more domains, the demand for tech talent is growing.

TORONTO, March 22, 2017 /CNW/ - The Government of Canada is funding a Pan-Canadian Artificial Intelligence Strategy for research and talent that will cement Canada's position as a world leader in AI. The $125 million strategy will attract and retain top academic talent in Canada, increase the number of post-graduate trainees and researchers studying artificial intelligence, and promote collaboration between Canada's main centres of expertise in Montreal, Toronto-Waterloo and Edmonton. The program will be administered through CIFAR, the Canadian Institute for Advanced Research. The new program was announced in the federal budget released on Wednesday. "The Canadian government clearly recognizes the importance of artificial intelligence as a platform technology that cuts across many areas of innovation today," says Dr. Alan Bernstein, President and CEO of CIFAR.