As AI and machine learning systems advance, real-world applications are exposing limitations such as the inability to adapt to situations beyond the narrow tasks those systems were trained to perform. Indeed, some observers note that AI researchers still do not understand the mechanisms by which automated systems learn. As AI researchers grapple with these unknowns, the Defense Advanced Research Projects Agency (DARPA) launched a program last year aimed at advancing "lifelong machine learning." This week, the research agency announced funding for three university research teams that will tackle various components of the adaptability problem. Those efforts augment initial research at Columbia University focused on reproducing neural networks.

WASHINGTON – The European Union's executive branch, the European Commission, has announced that it will increase its investment in artificial intelligence (AI) research and development by €1.5 billion and called on member states to invest €20 billion as well. Congressman John K. Delaney (MD-6), the founder of the House AI Caucus, says that the European Union's action should get the attention of U.S. policymakers. "Our economic competitors in Europe and Asia are moving forward on AI, while we stand still. I sincerely hope that today's announcement from the EU gets the attention of Washington and serves as a wake-up call. If we want artificial intelligence technology to benefit our society, our economy and our workers, we've got to make sure that the United States remains the global leader – but make no mistake, we will have competition," said Congressman Delaney.

Metallurgists have long sought the Holy Grail of alloys, metallic glass that is strong and won't shatter. It is amorphous, with its atoms arranged every which way, much like the atoms of the glass in a window. Its glassy nature makes it stronger and lighter than today's best steel, plus it stands up better to corrosion and wear. Even though metallic glass would be useful as a protective coating or an alternative to steel, only a few thousand of the millions of possible combinations of ingredients have been evaluated over the past 50 years, and of those, only a handful developed to the point that they may become useful. Now a group led by scientists at the Department of Energy's SLAC National Accelerator Laboratory, the National Institute of Standards and Technology (NIST), and Northwestern University has reported a shortcut for discovering and improving metallic glass–and, by extension, other elusive materials–at a fraction of the time and cost.

The bank said in a note to employees on Thursday that it's hired Manuela Veloso as the company's first head of artificial intelligence research. Veloso comes to JPMorgan Chase from Carnegie Mellon University, where she's served as head of the machine learning department. Her employment was first reported by the Wall Street Journal. The move comes as big players in the finance industry race to roll out AI, which could eventually be used for services ranging from fraud detection to loan approval, while making internal operations more efficient. "There's essentially been a mandate [from the top of] many of these institutions that AI and process management is something that should be heavily invested in," said Jason Mars, a computer science professor at the University of Michigan and the CEO of Clinc, a company that's developing AI solutions for financial firms like USAA.

We study information elicitation without verification (IEWV) and ask the following question: Can we achieve truthfulness in dominant strategy in IEWV? This paper considers two elicitation settings. The first setting is when the mechanism designer has access to a random variable that is a noisy or proxy version of the ground truth, with known biases. The second setting is the standard peer prediction setting where agents' reports are the only source of information that the mechanism designer has. We introduce surrogate scoring rules (SSR) for the first setting, which use the noisy ground truth to evaluate quality of elicited information, and show that SSR achieve truthful elicitation in dominant strategy. Built upon SSR, we develop a multi-task mechanism, dominant truth serum (DTS), to achieve truthful elicitation in dominant strategy when the mechanism designer only has access to agents' reports (the second setting). The method relies on an estimation procedure to accurately estimate the average bias in the reports of other agents. With the accurate estimation, a random peer agent's report serves as a noisy ground truth and SSR can then be applied to achieve truthfulness in dominant strategy. A salient feature of SSR and DTS is that they both quantify the quality or value of information despite lack of ground truth, just as proper scoring rules do for the with verification setting. Our work complements both the strictly proper scoring rule literature by solving the case where the mechanism designer only has access to a noisy or proxy version of the ground truth, and the peer prediction literature by achieving truthful elicitation in dominant strategy.

The company decided to close its doors because it was losing clients and facing mounting legal fees in the Facebook investigation, according to people familiar with the matter. SCL Group and SCL Elections, which are affiliated with Cambridge Analytica, also are shutting down in the U.S. and the U.K. Cambridge Analytica and SCL Elections issued a joint statement on Wednesday confirming the companies' closures. "Over the past several months, Cambridge Analytica has been the subject of numerous unfounded accusations," the statement said. "The siege of media coverage has driven away virtually all of the company's customers and suppliers. As a result, it has been determined that it is no longer viable to continue operating the business."

Cambridge Analytica, the data firm at the centre of this year's Facebook privacy row, is closing and starting insolvency proceedings. The company has been plagued by scandal since the Observer reported that the personal data of about 50 million Americans and at least a million Britons had been harvested from Facebook and improperly shared with Cambridge Analytica. Cambridge Analytica denies any wrongdoing, but says that the negative media coverage has left it with no clients and mounting legal fees. "Despite Cambridge Analytica's unwavering confidence that its employees have acted ethically and lawfully, the siege of media coverage has driven away virtually all of the Company's customers and suppliers," said the company in a statement, which also revealed that SCL Elections Ltd, the UK entity affiliated with Cambridge Analytica, would also close and start insolvency proceedings. "As a result, it has been determined that it is no longer viable to continue operating the business, which left Cambridge Analytica with no realistic alternative to placing the company into administration."

Toronto's status as a burgeoning tech and artificial intelligence hub recently received a huge stamp of validation. The community made the final list of 20 cities in the running for Amazon's HQ2, earning that distinction without offering Amazon any tax breaks or financial incentives. Being a tech torch bearer is nothing new for Canada. In the early 2000s, BlackBerry and Nortel held sizable market shares in smartphones and telecom, respectively. Not long after that, though, an inability to gain a competitive advantage closed the door on each brand's chance to dominate the marketplace.

While the U.K. wants to lead the conversation around the ethical implications of AI, they definitely aren't the only contenders. The US and China are the dominating AI powers and Canada, like the U.K., has upped the resource flow. Last year, the Ontario government pledged $30 million to increase the number of graduates studying AI in their bid to sway Amazon. READ MORE: The future of AI depends on who's at the table Canada at large has adopted the Pan-Canadian Artificial Intelligence Strategy, worth $125-million, which will hopefully boost the country's reputation in field of AI. Canada's startups are also gaining global attention for their research on artificial intelligence. In the East, China is investing billions of dollars in preparation for an AI industry worth $150 billion dollars by 2030.

When Mark Zuckerberg told Congress Facebook would use artificial intelligence to detect fake news posted on the social media site, he wasn't particularly specific about what that meant. Given my own work using image and video analytics, I suggest the company should be careful. Despite some basic potential flaws, AI can be a useful tool for spotting online propaganda – but it can also be startlingly good at creating misleading material. Researchers already know that online fake news spreads much more quickly and more widely than real news. My research has similarly found that online posts with fake medical information get more views, comments and likes than those with accurate medical content.