Google is on a spree to strengthen its cloud offerings after it combined its cloud and corporate software divisions under a single entity. This time around, Google has acquired yet another firm called Qwiklabs that deals in end-to-end cloud platform services and training on how to use them. The acquisition will provide a lab learning on Google's Cloud Platform, G Suite and other products for the developers. The acquisition deal amount has not been disclosed. Separately, it invested in AI research at the Montreal Institute for Learning Algorithms, and is also opening an AI research group at its Montreal office.

It's become clear that the algorithms Facebook and Google designed to deliver news to their users have failed. But while fake news is a headache for those tech giants right now, the underlying research question--whether and how machines tell truth from lies on the internet--is one that will persist as long as the world wide web stays an open forum. Facebook and Google's sizable machine learning divisions have created algorithms that effectively surface information that users want to see. But they've been unable to actually understand or vet that info--and in fact, experts across the tech industry say it's unrealistic to expect any AI or machine learning algorithm to do this task well. All our best efforts so far are built on research in natural language processing, which teaches AI to read a piece of text, understand the concepts within, and provide insight about its meaning. "Modern machine learning for natural language processing is able to do things like translate from one language to another, because everything it needs to know is in the sentence its processing," says Ian Goodfellow, a researcher at OpenAI.

Amazon, Baidu, Facebook, Google and Microsoft, among other technology companies, have been investing heavily in artificial intelligence and related disciplines like machine learning because they see the technology enabling services that become a source of revenue. Consultancy Accenture earlier this week quantified this enthusiasm, predicting that AI "could double annual economic growth rates by 2035 by changing the nature of work and spawning a new relationship between man and machine" and by boosting labor productivity by 40 per cent. Certainly things could work out well for Accenture, which a day later announced a partnership with Google to help companies deploy Google technology like machine learning. It's as if the global services firm has a stake in the future it foresees. But the machine learning algorithms underpinning this harmonious union of people and circuits aren't secure. In a paper [PDF] presented in August at the 25th Annual Usenix Security Symposium, researchers at École Polytechnique Fédérale de Lausanne, Cornell University, and The University of North Carolina at Chapel Hill showed that machine learning models can be stolen and that basic security measures don't really mitigate attacks.

The potential for artificial intelligence (AI) to cut the power consumption of datacentres is an area of growing interest in the industry, as operators seek new ways to reduce costs and drive up the performance of their facilities. A collection of our most popular articles on datacentre management, including: Cloud vs. Colocation: Why both make sense for the enterprise right now; AWS at 10: How the cloud giant shook up enterprise IT and Life on the edge: The benefits of using micro datacenters This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers. You also agree that your personal information may be transferred and processed in the United States, and that you have read and agree to the Terms of Use and the Privacy Policy.

The future is here and so are mounting fears about artificial intelligence (AI). A growing concern due to the way that AI is portrayed in movies and TV shows, is that jobs will be replaced by robots. According to presentations at MIT Technology Review's EmTech conference, we shouldn't have anything to worry about. Current robots, with even the most advanced AI capabilities, are not equipped with the hardware or software to be intelligent enough to even maneuver themselves out of a corner. Robots can be programmed to make our lives easier, but they certainly couldn't take over our jobs.

Artificial intelligence and machine learning systems are made up of code and algorithms, and as such, they work as fast as computers can process them. Often this means massive amounts of learning can be accomplished every second without stop 24x7x365. Code doesn't need to take weekends off, holidays, or sick time. It can recognize complex patterns, areas of potential improvement and problems in real-time (aka digital-time). Given these available computing capabilities and speeds, what are executives to do with AI and machine learning, when we live and operate in relatively slow human-time, and work within organizations that work at an even slower pace of organizational-time.

The Carnegie Endowment for International Peace (CEIP) and Carnegie Mellon University held the first part of the two-part joint Carnegie Colloquium on Digital Governance and Security in Washington D.C. on Oct. 31. The first part of the colloquium was titled "The Rise of Artificial Intelligence: Implications for Military Operations and Privacy," and the second part, titled "The Future of the Internet: Governance and Conflict," will be held this year in Pittsburgh on Dec. 2. CEIP is a series of foreign policy-based research centers located in Russia, China, Europe, the Middle East, India, and the United States, with headquarters in Washington D.C., that collects itself under the phrase, "The Global Think Tank." It was established in 1960 by Andrew Carnegie and, according to a report by the University of Pennsylvania, is the third most influential think tank in the world. The colloquium, held for the benefit of both Carnegie Mellon and the CEIP, aimed to allow for communication between the academics at Carnegie Mellon and the foreign policy and ethics experts from all the CEIP stations across the world to discuss the implication of artificial intelligence on foreign policy and the challenges posed by it. The second part of the colloquium will focus on cyber-security norms and internet governance. "Designing safe software systems and attempting to create the learning abilities of the human brain are natural progressions towards the two of the modern world's most pressing concerns -- cyber security and privacy," said President Subra Suresh, in the welcome address.

According to the Financial Times, Pablo Picasso once said, "Computers are useless. They can only give you answers." Unfortunately for us, computers may now be asking more questions than they answer. As a result, the possibilities are rather overwhelming, with answers more ambiguous and uncertain than straightforward. Similarly, we might ask ourselves where we draw the line when it comes to what we find ethically acceptable in terms of artificial intelligence (AI) as it relates to composition/creation in the worlds of art, writing, performing arts and music--as well as liberal arts education. Most of us are aware of music streaming services that select songs for us based on data about users' listening preferences.

Toronto-based IT software developer announced today the pilot program, Karen by Karen.ai, a cognitive recruiting chatbot that engages candidates throughout the application process, matches candidates to alternative positions and provides screening support before, during and after the recruiting process. "Karen derives concepts and personality traits from candidates' resumes and cover letters and assesses the level of engagement and gains deeper insights through a simple text chat conversation. This conversation improves the candidate's experience of the recruitment process and represents the company's brand," said founder Noel Webb. Webb also noted Karen can follow up with candidates during and after the requisition and provide alternative options within the company for which they may be better suited. While automated solutions have existed in recruitment for nearly a decade, Karen takes these automations one step further, because Karen can learn from conversations with candidates and predict other positions for which they might be a match.

Google and the Royal Free London NHS Foundation Trust have announced a fresh five-year collaboration today, which will see the former's DeepMind AI used to improve patient care across the trust's various hospital sites. The partnership will focus on Streams, a mobile app the pair have been working on since late last year that's been approved as a medical device by the UK's health regulator. DeepMind will analyse blood test results as they come in and flag when patients might be at risk of acute kidney injury, proactively alerting carers through the Streams app. It'll go live across the trust in early 2017, and there are plans to expand the blood analysis to look for signs of sepsis and other causes of organ failure. The pair hope to add messaging and task management features over the course of the collaboration too, and Streams is said to be built on open standards that will allow other developers to easily add new services.