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.

Tech giants are making acquisitions in the AI space, and an increasing number of startups are working with the technology. Speaking at The Europas, a European startup conference held in London today, John Henderson, principal at Whitestar Capital, spoke about the overwhelming competition in the space and noted the need for young tech firms to stand out from the crowd. "When it comes to investing in AI startups what we look for and what is hard to find is defensibility," he said. DeepMind – acquired by Google in 2014 – Henderson argued was "a one-off". "It [DeepMind] was acquired for the research talent. Startups out there need to think about AI as an enabling technology or a platform, as opposed to every startup building their own AI technology," added Henderson.

IBM'S ARTIFICIAL INTELLIGENCE (AI) will be mixed with Cisco's data analytics to help make sense of the data hoovered up by the Internet of Things (IoT). The partnership will use the IBM Watson AI with Cisco's ability to carry out data analysis on at the edge of IoT networks rather than waiting for all that information to be pushed back to a central point. The companies explained that this will make data analysis in the IoT faster and allow customers to act on the information as soon as possible. Organisations are trying to make better use of data as devices become more intelligent and connected to corporate networks, and one of the problems is the process of actually gathering the data, according to IBM. "Today, in a typical industrial deployment, only one per cent of IoT data is actually analysed. Legacy processes and drawbacks in current IoT platforms make it too expensive and slow to analyse the other 99 per cent," said Chris O'Connor, general manager for IoT at IBM, on the firm's blog.

The best minds in the business--Yann LeCun of Facebook, Luke Nosek of the Founders Fund, Nick Bostrom of Oxford University and Andrew Ng of Baidu--on what life will look like in the age of the machinesThe traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

In this presentation, Mate plans to talk about the base of all NP-complete problems, the satisfiability problem, how these problems are being solved with state-of-the-art SAT solvers, and how that is relevant to our everyday lives. SAT solvers have enjoyed a boom thanks to massive improvements through the use of lazy data structures, tricky graph algorithms, proof verification, and heuristics. This allowed SAT solvers to thrive in many different tasks such as hardware verification,software fuzzing, cryptography, and math proofs. In this talk we will examine some of the core data structures and algorithms used by SAT solvers, as well as show some example use-cases for them in different fields.

This week, in a public test, we put the Triage capability of babylon's new AI function to test against some of the UK's top triage nurses and junior doctors. Professor Irwin Nazareth, The Academic Doctoral Research Committee Chair of the Health Education England and NIHR examined one of Britain's most senior A&E nurses, an Oxford-educated Junior Doctor and babylon's new'Check' feature to see who provided the most accurate and fastest triage assessment in front of the UK's top consumer, health and technology media. This was a live demonstration of an extensive set of tests published in an academic research paper, that showed babylon's'Check'feature to be safe in 100% of cases, 13% more accurate than a doctor, 17% more accurate than a nurse, and performing significantly faster 89% of the time. "Check a Symptom" is already the most popular feature on the babylon app. In the UK alone, it has been used around 20,000 times in just three weeks (that is about 3% of the usage of nhs 111 nationally in the same period).

Apple's Siri made a big splash when the wisecracking digital assistant debuted on the iPhonefive years ago. But as other tech giants jockey to build intelligent "chat bots" and voice-controlled home systems capable of more challenging artificial-intelligence feats, Siri at times no longer seems cutting edge. On Monday, Apple is expected to demonstrate an upgrade to Siri's smarts as it kicks off its annual software conference. It's a potentially momentous time for the company; sales of its flagship iPhone are slowing, and AI is emerging as a key tech battleground. Apple, Google, Facebook and others are racing to create digital services that consumers will find indispensable for shopping, chatting, controlling other appliances and simply getting through their daily lives. And while Siri has gained new abilities over the years, some experts believe Apple still lags in the AI race, hindered in part by its unwillingness to pry too deeply into your personal information.

Chatbots can order flowers for you on Facebook. An intelligent assistant can schedule a meeting. Now, a new update for your iPhone will be packed with new automations to make our lives easier and maybe even reduce stress, and it won't cost you a cent when it debuts this fall (unless you need to get a new iPhone). This week at a developer conference in California, Apple announced iOS 10 and focused mostly on how to make your phone "think differently" by thinking for you and saving time. There are some brilliant new updates, but here are the ones that impressed me the most and offer the most automation.

In the future, or so some people think, it will become possible to upload your consciousness into a computer. Software emulations of human brains – ems, for short – will then take over the economy and world. This sort of thing happens quite a lot in science fiction, but The Age of Em is a fanatically serious attempt, by an economist and scholar at Oxford's Future of Humanity Institute, to use economic and social science to forecast in fine detail how this world (if it is even possible) will actually work. The future it portrays is very strange and, in the end, quite horrific for everyone involved. It is an eschatological vision worthy of Hieronymus Bosch.

Everyone seemingly is complaining about the spread of ransomware, and now somebody is trying to do something about it using machine learning-based behavioral analytics techniques to track suspicious behavior on company networks. As the scale of the ransomware threat grows, including ransom payments by hospitals and universities and growing fears that it will soon spread to other sectors, a Silicon Valley security intelligence firm has rolled out an approach for detecting ransomware via machine learning. Exabeam, a specialist in user and "entity" behavior analytics based in San Mateo, Calif., unveiled its analytics approach to detecting ransomware attacks during a security conference this week. The early warning system is touted as being able to spot ransomware activity on corporate networks without relying on third-party security controls. The platform also can spot suspicious activity within cloud services, servers and, increasingly, personal devices connected to corporate and other enterprise IT infrastructure.