Canada's rankings in innovation has lagged that of other peer nations for decades despite government efforts to address this issue. Considering its success in developing research programs at its universities, its mediocre rankings overall in technology development is disappointing. Those programs alone have not been enough to translate into entrepreneurial innovation. A 2017 C.D. Howe Institute study points out that, even though Canadians have been at the forefront of breakthroughs in emerging technologies, in many cases, the chief beneficiaries of those breakthroughs have been other nations' economies. Canada needs to take a stronger role in building an environment in which Canadian know-how spurs Canadian business growth. According to a 2017 PwC global survey, Canadian companies stand significantly ahead of their global counterparts in having a dedicated team for digital innovation, with 54% of Canadian respondents reporting that their company does, as opposed to 43% of global respondents. Looking deeper, though, shows a far less innovative spirit, as 47% of respondents said that their pursuit of digital innovation takes the form of seeking to copy others' innovations rather than pursuing their own. Already a decade ago, experts recognized factors that constrain Canadian innovation growth. A 2009 study by the Council of Canadian Academies pointed to two key issues that have held Canadian businesses back from prioritizing innovation in their business strategies. The first issue deals with what has been called "the resource curse." Canada is largely "upstream" in the international supply chain, providing raw materials for other businesses that create products that are in turn passed down the value chain until they reach the stage of finished products sold to end customers. That places Canada in a position far distant from end customers, whose evolving needs spur businesses at the downstream end of the supply chain to adapt, which, in turn, spurs innovation.

Technology futurist and entrepreneur Elon Musk has frequently mused on the threats of AI, most recently in a talk at the South by Southwest technology conference in which he called AI "more dangerous than nuclear warheads." While mainstream technologists and social scientists may dismiss Musk's foreboding proclamations, it's worth thinking about the current state of the integration of machine learning and artificial intelligence into everyday applications and to ask whether we are ready to rely on algorithms. AI is not a new phenomenon. Research on AI started back in the late 1950s, with various stops and starts throughout the past six decades. In that time, many machine learning approaches and algorithms have been developed.

The unique topic of artificial intelligence (AI) for humanitarian assistance and disaster relief (HA/DR) was in the spotlight last week, as leading minds from academia, industry and the federal government met to discuss how modern technology can help victims of disasters around the globe. The Artificial Intelligence and Autonomy for Humanitarian Assistance and Disaster Relief Workshop–co-hosted by the Office of Naval Research (ONR) and Carnegie Mellon University (CMU)–took place at the university's Pittsburgh campus Aug. 2-3. "The problem of catastrophes affecting humanity will unfortunately always be among us," said Chief of Naval Research Rear Adm. David J. Hahn. "The great minds in this room are here to figure out how we can best leverage artificial intelligence and autonomy to better deliver resources and people to those in urgent need." As Hahn addressed the group, pictures of naval relief efforts over many years scrolled behind him, including Sailors and Marines assisting victims in Haiti after an earthquake, Japan after an earthquake and tsunami, New Orleans and New York after hurricanes, and more.

Chinese People's Liberation Army (PLA) Air Force officers march past Tiananmen Square in a show of military strength Last month, some of the biggest names in technology signed a pledge promising not to develop lethal autonomous weapons. Coming just after the recent employee-led protest over Google's Project Maven, some have praised these initiatives as ethical and moral victories. For Sandro Gaycken, a senior advisor to Nato, such initiatives are supremely complacent and risk granting authoritarian states an asymmetric advantage. "These naive hippy developers from Silicon Valley don't understand – the CIA should force them," says Gaycken, founder of the digital society institute at ESMT, a Berlin-based business school. Gaycken's hard advice reveals a schism emerging in the future development of AI for military purposes. On the one side are those that believe pursuing the development of military AI will lead to an unstoppable arms race. On the other side, people like Gaycken believe the AI arms-race has already begun.

Abstract-- Open-Source Projects and Libraries are being used in software development while also bearing multiple security vulnerabilities. This use of third party ecosystem creates a new kind of attack surface for a product in development. An intelligent attacker can attack a product by exploiting one of the vulnerabilities present in linked projects and libraries. In this paper, we mine threat intelligence about open source projects and libraries from bugs and issues reported on public code repositories. We also track library and project dependencies for installed software on a client machine. We represent and store this threat intelligence, along with the software dependencies in a security knowledge graph. Security analysts and developers can then query and receive alerts from the knowledge graph if any threat intelligence is found about linked libraries and projects, utilized in their products. I. INTRODUCTION In the normal course of software development, developers and coders rely on various open source projects and libraries. Open source projects and libraries comprise of source code that is open for anyone to inspect, modify, update or enhance [17].

U.S. Bank's Chief Analytics Officer Bill Hoffman thinks the term "artificial intelligence" is a bit of a misnomer – he prefers to think about AI as a customized experience. "The'A' in AI should be'augmented,' not artificial," he said in an interview last year with CMO Australia. "There's nothing artificial about building a high quality, personalized relationship with a customer." Hoffman's less artificial approach to AI is transforming how U.S. Bank interacts with its customers and builds quality relationships with people. Hoffman was instrumental in U.S. Bank's adoption of Einstein, an AI platform offered by Salesforce, late last year.

Apple could be forced to drop the charging port in the bottom of its iPhones as part of new plans to help users. The company may be required to use another standard like USB-C instead, so that ports can be standardised across manufacturers. The European Union is looking at new ways of making phone companies all use the same phone chargers, which could include forcing companies to decide on a standard and use it in all phones. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

A customer examines the iPhone X at an Apple Store in Atlanta on Nov. 3 2017. The iPhone only listens to users when triggered by the phrase "Hey Siri," Apple said in a letter to lawmakers explaining how it guards consumer privacy. The letter was written in response to a one sent by leaders of the House's Energy and Commerce Committee seeking answers on how the tech giant safeguards privacy. A similar letter was sent to Larry Page, the CEO of Google parent company Alphabet, which produces the Android operating system. The letter from lawmakers sought information on how Apple collects and uses consumer data, as well as how the microphones work on iPhones.

Last month, members of the House Energy and Commerce Committee fired off a letter to Apple following reports that phones and other devices, such as smart speakers, can listen in on conversations. Now, the tech giant has sent the Representatives its response: iPhones, it says, don't listen to people's conversations and don't share people's spoken words with third-parties. In what could be interpreted as a dig at its staunchest competitors, Cupertino explains in the letter (courtesy of CNET) that the customer is not its product and that its business model "does not depend on collecting vast amounts of personally identifiable information to enrich targeted profiles marketed to advertisers." In the original letter the lawmakers sent, they specifically noted reports that third-party apps could access the data devices supposedly collect while listening for their "trigger words," such as "Hey, Siri, "OK Google" and "Hey, Alexa." During Facebook's congressional hearing back in April, Senator Gary Peters (D-MI) even asked Mark Zuckerberg whether the social network listens in on people through their phone mics in order to serve relevant ads.

New research from Eset shows IT decision makers think AI is the'silver bullet' needed to address cybersecurity challenges, but marketing hype is causing confusion among teams. The interest in AI and machine learning (ML) has spiked in recent times. Many people look to the new technologies as a kind of saviour for their long-standing industry problems. This is especially evident in the cybersecurity field, where the hope is that AI could be the'silver bullet' the it needs. A global survey from Eset found 75pc of IT decision makers believe AI will solve their cybersecurity challenges.