I think that is the main reason for getting acknowledgement from the jury.

Summary: For those of you traditional data scientist who are interested in AI but still haven't given it a deep dive, here's a high level overview of the data science technologies that combine into what the popular press calls artificial intelligence (AI). We and others have written quite a bit about the various types of data science that make up AI. Still I hear many folks asking about AI as if it were a single entity. AI is a collection of data science technologies that at this point in development are not even particularly well integrated or even easy to use. In each of these areas however, we've made a lot of progress and that's caught the attention of the popular press.

The artificial intelligence (AI) revolution has begun, and it's going to take all of us -- government, businesses and employees -- to steer through the resulting workforce disruption. More than just helping our kids avoid jobs that machines will take over in the future -- from driving trucks and reading X-rays to picking stocks and balancing the books -- we need to look at ways of retraining the millions of adults who will be displaced by machines and get them back doing meaningful, relevant work. Change is happening so fast that waves of today's professionals -- educated, established, many in mid-career -- may see their jobs swept away with the technological tide. These white-collar workers with six-figure lifestyles, long the backbone of the knowledge economy, face what the World Economic Forum calls the fourth industrial revolution. What happens when their jobs disappear?

Computer vision is ready for its next big test: seeing in 3D. The ImageNet Challenge, which has boosted the development of image-recognition algorithms, will be replaced by a new competition next year that aims to help robots see the world in all its depth. Since 2010, researchers have trained image recognition algorithms on the ImageNet database, a go-to set of more than 14 million images hand-labelled with information about the objects they depict. The algorithms learn to classify the objects in the photos into different categories, such as house, steak or Alsatian. Almost all computer vision systems are trained like this before being fine-tuned on a more specific set of images for different tasks.

Educational, training institutions and eLearning content publishers must adapt themselves to the new technological landscape in order to keep their courses and learning materials relevant to today's learners. The development of educational mobile apps provides exciting new ways to develop educational courses that are both effective in reaching educational objectives for teachers and rewarding to the online learner. This presentation will serve as a guide for managers at learning organizations into ways to adapt courses for the multi-screen and multi-device app based environment that today's learners engage in. Mobile devices are outpacing traditional desktop environments when it comes to accessing the web. In fact, 60% of search queries are now done through mobile devices (source: SearchEngineLand).

Legal services are notoriously complicated, not to mention costly for those who need to access them. However, Chrissie Lightfoot, a leading futurist, entrepreneur and lawyer, has come up with an innovative solution. Instead of forking out for a human advisor, clients can now use Robot Lawyer LISA, an impartial Legal Intelligence Support Assistant, to draw up Non-Disclosure Agreements. The artificially intelligent platform can create legally binding documents in under seven minutes at absolutely no cost to the user. Allowing individuals and businesses to use LISA to protect themselves without any prior legal knowledge. LISA is also the first law robot to provide unbiased and objective assistance to both parties, allowing users to avoid having to engage traditional human lawyers on either side.

Artificial intelligence is gaining widespread momentum at a rapid rate. Machines recently attained voice and image recognition. Think Apple's Siri or Amazon's Alexa as well as Facebook and Google accounts. AI can be broadly-described as a computer system designed to interact with the world through capabilities and intelligent behaviors. AI's developing usefulness is striking, especially in light of some recent successes.

Artificial intelligence is one of the heralds of a smarter tech world -- but could it help us be a more compassionate one, as well? The University of Southern California thinks so. Last fall, it christened its Center on Artificial Intelligence in Society, dedicated to deploying AI toward humanitarian ends. In particular, it's aiming toward two social entrepreneurship challenges: the Grand Challenges for Social Work initiative from the American Academy of Social Work and Social Welfare and the United Nations' Sustainable Development Goals. How can AI help these noble projects?

Robots are coming for our jobs, and Justin Trudeau is ready. The prime minister of Canada answered a question on Quora this week about how governments, especially Canada's, should prepare for automation. "We know that the job market is changing, and instead of resisting in vain, we're focused on funding research and innovation, like in AI and quantum computing, that'll help lead the change here in Canada," Trudeau wrote in his response. "And while we do that, we're preparing Canadians to find good jobs through investments in education and training." Trudeau answered a few questions on Quora: about artificial intelligence, feminism, engineering jobs in Canada, and Brexit.