New developments in artificial intelligence and robotics put 42 per cent of Canadian workers at high risk of seeing their jobs disappear or significantly changed in the next two decades, a new report concludes. While advancing computerization has already made some jobs obsolete, the rapid development of artificial intelligence is poised to become a new "inflection point" for more dramatic job change over the next 10 to 20 years, said Sean Mullin, executive director of the Brookfield Institute for Innovation Entrepreneurship at Ryerson University. Mr. Mullin said computers are expected to take on jobs that previously required higher "cognitive skills" as new technology allows machines to learn on their own and apply their knowledge. "If that even partially comes true, we're going to see a much more fundamental restructuring of the labour force and potentially a much higher percentage of jobs at risk than I think we've seen in the past," Mr. Mullin said. The new Brookfield Institute research report examined all major job categories in Canada and applied a methodology developed in 2013 at Oxford University in Britain.

MENLO PARK, CA--(Marketwired - June 15, 2016) - Trends Equity today announced that it has teamed up with deepsense.io, The workshop is focused on helping attendees understand the scope, breadth and depth of machine learning solutions available in today's marketplace. According to Eliot Weinman, CEO, Trends Equity and AI World conference chair, "Machine learning and deep learning are together one of the fastest growing software markets today, expected to reach 40B by 2024 (source: Tractica). AI World, which is committed to helping businesses understand how to harness AI and machine learning, has specifically developed this workshop with deepsense.io "We are very pleased to be working with AI World, and becoming the Strategic Machine Learning Workshop Partner for the conference.

MENLO PARK, CA--(Marketwired - June 15, 2016) - Trends Equity today announced that it has teamed up with deepsense.io, The workshop is focused on helping attendees understand the scope, breadth and depth of machine learning solutions available in today's marketplace. According to Eliot Weinman, CEO, Trends Equity and AI World conference chair, "Machine learning and deep learning are together one of the fastest growing software markets today, expected to reach 40B by 2024 (source: Tractica). AI World, which is committed to helping businesses understand how to harness AI and machine learning, has specifically developed this workshop with deepsense.io "We are very pleased to be working with AI World, and becoming the Strategic Machine Learning Workshop Partner for the conference.

Deep learning is rapidly'eating' artificial intelligence. But let's not mistake this ascendant form of artificial intelligence for anything more than it really is. The famous author Arthur C. Clarke wrote, "Any sufficiently advanced technology is indistinguishable from magic." And deep learning is certainly an advanced technology--it can identify objects and faces in photos, recognize spoken words, translate from one language to another, and even beat the top humans at the ancient game of Go. Oren Etzioni is the CEO of the Allen Institute for Artificial Intelligence and a computer scientist at the University of Washington.

Artificial intelligence can now cook you a meal, chat to you on your phone, and beat you in a game of rock, paper, scissors. But Andy Rubin, who co-founded Android, believes that AI in the future will go one step further - being so powerful that it underpins every connected device. Mr Rubin said a combination of quantum computing and AI advancements could yield a conscious intelligence that would control every internet-enabled gadget. According to recent studies, certain jobs are already at risk of being replaced by automated workers. Accountants are 99 per cent likely to lose their jobs to machines.

Machine learning is providing the needed algorithms, applications, and frameworks to bring greater predictive accuracy and value to enterprises' data, leading to diverse company-wide strategies succeeding faster and more profitably than before. The good news for businesses is that all the data they have been saving for years can now be turned into a competitive advantage and lead to strategic goals being accomplished. Revenue teams are using machine learning to optimise promotions, compensation and rebates to drive the desired behaviour across selling channels. Predicting propensity to buy across all channels, making personalised recommendations to customers, forecasting long-term customer loyalty and anticipating potential credit risks of suppliers and buyers are also key. Figure 1 provides an overview of machine learning applications by industry. Unlike advanced analytics techniques that seek out causality first, machine learning techniques are designed to seek out opportunities to optimise decisions based on the predictive value of large-scale data sets.

The market research firm expects the attach rate of AI-based systems in new vehicles to increase from 8 percent in 2015 (the vast majority of today's AI systems in cars are focused on speech recognition) to 109% in 2025. IHS sees multiple AI systems of various types to be installed in many cars. In the human-machine interface in vehicles, IHS believes AI will play a role in speech and gesture recognition, eye-tracking, driver monitoring and natural language interfaces. In the autonomous car, AI will advance machine vision systems, while it will also migrate in sensor fusion electronic control units (ECU). In a phone interview with EE Times, Luca De Ambroggi, principal analyst, automotive semiconductors at IHS told us, "AI is viewed as a key enabler for real autonomous vehicles. Everyone in the automotive supply chain is getting pretty bullish."

If you write marketing or advertising text for a living, you may want to get a second job skill. That's because software that writes text is here, and it is tackling a growing list of assignments. Several companies offer software that regularly churns out thousands of stories and reports based on structured data, like financial results. Ads that literally write themselves emerged last week, as IBM announced a new service based on its Watson supercomputer. A program called Quakebot has generated earthquake stories for the LA Times.

Apple announced today that it will be opening up Siri to third-party developers through an API, giving outside apps the ability to activate from Siri's voice commands, and potentially endowing Siri with a wide range of new skills and datasets. The move follows similar announcements by Amazon, Google, Facebook, and Microsoft, all of which are betting that voice commands and chatbots will be one of the next big computing paradigms. When Steve Jobs introduced Siri to the world five years ago, it felt like a revelatory advancement. Sure, there had been digital assistants before, but not one you speak to naturally or carry around in your pocket. In the time since, however, this kind of conversational AI proliferated out to lots of devices, with big offerings from most of Apple's major competitors.

In fact, unit shipments of artificial intelligence (AI) systems used in infotainment and ADAS systems are expected to rise from just 7 million in 2015 to 122 million by 2025, according to IHS Inc. (NYSE: IHS), the leading global source of critical information and insight. The attach rate of AI-based systems in new vehicles was 8 percent in 2015, and the vast majority were focused on speech recognition. However, that number is forecast to rise to 109 percent in 2025, as there will be multiple AI systems of various types installed in many cars. "An artificial-intelligence system continuously learns from experience and by its ability to discern and recognize its surroundings," said Luca De Ambroggi, principal analyst-automotive semiconductors, IHS Technology. "It learns, as human beings do, from real sounds, images, and other sensory inputs. The system recognizes the car's environment and evaluates the contextual implications for the moving car." Specifically in ADAS, deep learning -- which mimics human neural networks -- presents several advantages over traditional algorithms; it is also a key milestone on the road to fully autonomous vehicles.