Artificial intelligence, once relegated to the realm of science fiction, is now found in everything from translation services to virtual assistants to video games. And as companies race to develop self-driving cars and offer increasingly personalized online experiences, they're building on research that was largely pioneered by a group of Canadian researchers who are still attracting plenty of attention and investment dollars. Montreal, in particular, has developed a concentration of expertise in the area of AI, largely thanks to the efforts of Universite de Montreal professor Yoshua Bengio, head of the Montreal Institute for Learning Algorithms (MILA). "(AI) will affect pretty much every economic sector; right now is just the tip of the iceberg," Bengio told The Canadian Press. "One of the things we are going to see more of is how these technologies affect how we interact with computers."

"We now have a new computing model to power AI and solve what was once unsolvable, with superhuman speed and intelligence." "It's like the Ratatouille movie, but instead of'anyone can cook' it's'anyone can do machine learning.'" "Focus on your company's challenges and what it is that you want to achieve." - Beena Ammanath, General Electric VP Data and Analytics "The biggest constraint is people's ability to understand the potential of what they can do." "Think of AI like a rocketship, where data is the fuel and neural networks are the engine." "Startups, consulting orgs, big players all want and try to do this but it's complex like playing 3D chess, so we have to be an extreme pattern matcher to plan, anticipate, execute many moves ahead to win." - Steve Ardire, Advisor for Software Startups

Over the past four years, readers have doubtlessly noticed quantum leaps in the quality of a wide range of everyday technologies. Most obviously, the speech-recognition functions on our smartphones work much better than they used to. When we use a voice command to call our spouses, we reach them now. We aren't connected to Amtrak or an angry ex. In fact, we are increasingly interacting with our computers by just talking to them, whether it's Amazon's Alexa, Apple's Siri, Microsoft's Cortana, or the many voice-responsive features of Google.

Facial recognition software is most commonly known as a tool to help police identify a suspected criminal by using machine learning algorithms to analyze his or her face against a database of thousands or millions of other faces. The larger the database, with a greater variety of facial features, the smarter and more successful the software becomes – effectively learning from its mistakes to improve its accuracy. Now, this type of artificial intelligence is starting to be used in fighting a specific but pervasive type of crime – illegal fishing. Rather than picking out faces, the software tracks the movement of fishing boats to root out illegal behavior. And soon, using a twist on facial recognition, it may be able to recognize when a boat's haul includes endangered and protected fish.

Internet of @ThingsExpo, taking place June 6-8, 2017at Javits Center, New York City, is co-located with the 20th International @CloudExpo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago. All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. Help plant your flag in the fast-expanding business opportunity that is the Internet of Things: submit your speaking proposal today!

Artificial intelligence, once relegated to the realm of science fiction, is now found in everything from translation services to virtual assistants to video games. And as companies race to develop self-driving cars and offer increasingly personalized online experiences, they're building on research that was largely pioneered by a group of Canadian researchers who are still attracting plenty of attention and investment dollars. Montreal, in particular, has developed a concentration of expertise in the area of AI, largely thanks to the efforts of University of Montreal professor Yoshua Bengio, head of the Montreal Institute for Learning Algorithms (MILA). "(AI) will affect pretty much every economic sector; right now is just the tip of the iceberg,'' Bengio told The Canadian Press. "One of the things we are going to see more of is how these technologies affect how we interact with computers.''

The saying goes: 'Never judge a book by its cover,' but that's exactly what new AI technology has been designed to do. A controversial paper has been released, which investigates whether a computer can detect if a human could be a criminal, by analysing their facial features. The results suggest that it is bad news for people with smaller mouths, curvier upper lips and closer-set eyes, as apparently these features suggest you could be a crook. The paper investigates whether a computer can detect if a human could be a criminal, by analysing their facial features. The researchers singled out three features that they suggest can tell whether someone will be a criminal or not – lip curvature, eye inner corner distance, and the angle from the tip of the nose to the corners of the mouth.

Lately, tech companies have gone absolutely crazy for machine learning. They say it solves the problems only people could crack before. Machine learning is of special interest in IT security, where the threat landscape is rapidly shifting and we need to come up with adequate solutions. Some go as far as calling machine learning'artificial intelligence' just for the sake of it. Technology comes down to speed and consistency, not tricks.

With the development and integration of artificial intelligence (AI) into our daily lives, ethics and bias quickly become main concerns. Both ethics and bias also make implementing artificial intelligence in a practical sense that more complicated. Whose definition of what is ethical are corporations programming their AI systems to default to? It's highly unlikely that there will be a standard answer to this question across companies, industries and countries; especially considering the lack of diversity in the AI design world. The question of ethics, security and privacy is relevant enough, that IEEE (the world's largest organization dedicated to advancing technology for the benefit of humanity) has formed an initiative to examine ethics in the design of artificial intelligence systems.

When encountering novel object, humans and other animals are able to infer a wide range of physical properties such as mass, friction and deformability by interacting with themin a goal driven way. This process of active interaction is in the same spirit of a scientist performing an experiment to discover hidden facts. The study, entitled Learning to perform physics experiments via deep reinforcement learning, explained that while recent advances in AI have achieved'superhuman performance' in complex control problems and other processing tasks, the machines still lack a common sense understanding of our physical world – 'it is not clear that these systems can rival the scientific intuition of even a young child.' "We found," the team concluded, "that state of art deep reinforcement learning methods can learn to perform the experiments necessary to discover these hidden properties of the physical world. By systematically manipulating the problem difficulty and the cost incurred by the AI agent for performing experiments, we found that agents learn different strategies that balance the cost of gathering information against the cost of making mistakes in different situations."