Artificial Intelligence also brings with it, the ability to capture and exploit patterns that are unique to the loan portfolios of different lenders. Different lenders have different client acquisition channels, loan underwriting models and collections processes.

In the battle for the 21st century workplace, computers are winning. A January 2017 report from the McKinsey Global Institute estimated that roughly half of today's work activities could be automated by 2055, give or take 20 years. Bottom line is robots want our jobs. And no one is going to build a wall around them or tariff them out of existence. In a way this is nothing new.

Hephaestus, the Greek god of craftsmen and blacksmiths, was believed to have created automatons to work for him. Another mythological figure, Pygmalion, carved a statue of a beautiful woman from ivory, who he proceeded to fall in love with. Aphrodite then imbued the statue with life as a gift to Pygmalion, who then married the now living woman. Throughout history, myths and legends of artificial beings that were given intelligence were common. These varied from having simple supernatural origins (such as the Greek myths), to more scientifically-reasoned methods as the idea of alchemy increased in popularity. In fiction, particularly science fiction, artificial intelligence became more and more common beginning in the 19th century.

An introduction to the field of computer vision and image recognition, and how Deep Learning is fueling the fire of this hot topic. Computer Vision is an interdisciplinary field that focuses on how machines or computers can emulate the way in which humans' brains and eyes work together to visually process the world around them. Research on Computer Vision can be traced back to beginning in the 1960s. The 1970's saw the foundations of computer vision algorithms used today being made; like the shift from basic digital image processing to focusing on the understanding of the 3D structure of scenes, edge extraction and line-labelling. Over the years, computer vision has developed many applications; 3D imaging, facial recognition, autonomous driving, drone technology and medical diagnostics to name a few.

Levi Thatcher, Health Catalyst Director of Data Science and his team provide a live demonstration using healthcare.ai to implement a healthcare-specific machine learning model from data source to patient impact. Levi goes through a hands-on coding example while sharing his insights on the value of predictive analytics, the best path towards implementation, and avoiding common pitfalls. Frequently asked questions are answered during the session. During the webinar, we will: Describe and install healthcare.ai Build and evaluate a machine learning model Deploy interpretable predictions to SQL Server Discuss the process of deploying into a live analytics environment.

Though we've always assumed certain crafts will forever remain immune to automation, it seems nowadays nobody is safe from the looming artificial intelligence invasion. While a few years back the prospect of robots snatching jobs from humans might have seemed like a hackneyed plot twist from a cheap science fiction flick, this scenario actually turned into reality for the staff of Japanese insurance firm Fukoku Mutual Life. Last year, Facebook's VP of Design thought the TNW Conference main stage was the best she'd ever been on. The BBC reports the company has made an executive decision to lay off more than 30 employees and replace them with an artificial intelligence system that can calculate insurance payouts. With this move, Fukoku Mutual estimates it will increase productivity by an impressive 30 percent.

Video: Like owners and pets, are you to blame if your robot hurts you? Who is accountable for an artificial intelligence or robot which performs an action that brings harm to people? That action might be accidental but it's one of many questions society might need to ask itself about the autonomy and accountability of AI when more advanced forms of it such as driverless vehicles -- likely to be the first robots we learn to trust -- drones, and even military weapons become more widely deployed. AI and legal experts are attempting to figure it out, but there's no simple answer. Google's next big step for AI: Getting robots to teach each other new skills Robots haven't reached human intelligence yet, but Google's researchers are showing how they're closing the gap using downloadable intelligence.

When citizens want to know when to put out recycling or alternate-side parking information, they often turn to their city's 311 information systems for help, making a phone call or searching the web for answers. For more complicated questions, many cities unfortunately still rely on systems that are antiquated and pieced together. But recently, the city of Surrey, British Columbia, made their 311 services a whole lot easier when they turned to artificial intelligence solutions. Launched in 2015, the mobile app helps citizens access information that was traditionally dispensed by a call center or websites. With their My Surrey app (nicknamed "Siri for Cities")– a mobile, cognitive computing application powered by IBM Watson -- the city can quickly answer citizens' frequently asked questions and reduce the cost of providing that service.

Imagine a future where the CEO of a manufacturing firm turns to his Chief Innovation Officer and asks: "Bob, how can we innovate on our product and save 10 per cent of production cost to stay competitive against low-cost firms?" So far this seems to be a normal conversation that occurs daily across organisations around the world. Except that'Bob' is really an AI computer program on the CEO's iPhone. A study from Oxford University says that A.I. will replace up to 45 per cent of jobs within 20 years. There is a lot of talk about how such intelligent systems and chatbots will eliminate low level jobs, customer service and repetitive tasks.

Artificial intelligence is a young field full of nearly unlimited potential that remains largely misunderstood by most people. We've come a long way since Watson won Jeopardy in 2011 and IBM formed the business unit with over $1 billion in investments. AI is no longer a one-trick pony. AI technology from IBM Watson and multiple companies such as WayBlazer and SparkCognition has moved firmly into the real world. We have no doubt come a good distance on what is indeed a very long road.