"I would be shocked if we do not achieve full self-driving safer than a human this year," said Tesla chief executive, Elon Musk, in January. For anyone who follows Musk's commentary, this might sound familiar. In 2020, he promised autonomous cars the same year, saying: "There are no fundamental challenges." In 2019, he promised Teslas would be able to drive themselves by 2020 – converting into a fleet of 1m "robotaxis". He has made similar predictions every year going back to 2014.

A new app is looking to help health-care professionals and the public make better-informed decisions about COVID-19 for their patients, their families and themselves by collecting peer-reviewed scientific papers and hosting them in one place. The new app, called COVID AIKnowledgeEnable (COVID KE), uses artificial intelligence to search multiple peer-reviewed medical data sources in combination with collective insights of health-care professionals to deliver the most relevant findings and advice to users. The application, created by Canadian medical software developer Real Time Medical (RTM), also features confidence ratings and commentary from doctors to further assist users in determining which articles are the most helpful for them. "It really is a tool that attempts to combine both artificial intelligence and collective intelligence in real time on a single integrated platform to help users engage in research and education by helping them locate trustworthy articles," RTM CEO and co-founder Ian Maynard told CTVNews.ca. Maynard explained in a phone interview last week that COVID KE only uses trusted peer-reviewed sources including The Lancet, New England Journal of Medicine, the U.S. Centers for Disease Control and others, along with the latest federal health guidelines for Canada to help "users cut through the information clutter associated with COVID." The app is the first of its kind in the world to combine the power of artificial intelligence with the collective knowledge of experts to sort through misinformation, according to the company.

Are you ready for Skynet? What about synths destroying the colonies of Mars as seen in Picard? With so much fiction bleeding apocalyptic images of artificial intelligence (AI) gone wrong, we'll take a look at some possible scenarios of what could actually happen in the rise of artificial intelligence. While many researchers and computer experts aren't worried, new technologies need risk-assessment. But, some high profile scientists like Elon Musk and the late Stephen Hawking sounded the alarm years ago, and there is some reason for concern.

Teams that work with open data may feel like they face an explosion of information these days, but there are resources being brought to bear to process such data and stem the tide. Last week's FICO World conference in New York revealed some of the varied ways the credit niche of the financial world tries to apply big data analytics and so-called decision technology. The conference was largely a showcase for data analytics company FICO, but some presentations spoke to a broader context -- using machine learning and other resources to process vast amounts of data. Peter Maynard, senior vice president of data and analytics for strategic client and partner engagement at Equifax spoke about a partnership between his consumer credit reporting agency and FICO. He was joined by Tom Johnson, senior director with FICO, to discuss their joint effort combining data in a platform for decision making.

If you had your very own home robot, what would you want it to do, exactly? Yeah, me too, but that kind of robot is a long, long ways off. Consider Jibo, essentially a dancing Amazon Alexa. And Kuri, a miniaturized R2-D2 that roams around your house taking pictures. If that doesn't sound particularly impressive to you, well, the market felt the same way.

Moving to a new country can be hard. You don't know the language. Cultural differences create conversational landmines. And you just can't be sure that everyone will like you. As it turns out, that as true for people as it is for Amazon's Alexa voice assistant, which officially sets up residence in France today.

Yes, although the real work is happening not on the slopes of Davos, but on a hill overlooking the Golden Gate Bridge. The location, in Presidio National Park, illustrates how the Forum and key member companies have shifted their focus in recent years to the promise and perils of emerging technologies. After all, San Francisco has become the global capital of a tech industry with companies that are as influential as countries. "The tech companies were having an increasing impact on pretty much every foreign policy issue that we were dealing with," says Zvika Krieger, who served as the U.S. State Department's envoy to Silicon Valley in the Obama administration's final year. In early 2017, the WEF recruited Krieger and Silicon Valley entrepreneur Murat Sönmez to establish its first major office outside Switzerland, bearing the ambitious name World Economic Forum Center for the Fourth Industrial Revolution.

The financial services industry has been slow to embrace deep learning for fear of this black box, Maynard said. Nobody doubts that advanced techniques, like neural networks, could help financial companies make better decisions. But, for Equifax, regulations force them to give verbal explanations for why people receive the credit scores that they do. Simply saying, "because a neural net said so," isn't good enough. So Maynard and his team have developed a new type of neural network model that gives reason codes along with scores.

In the quarter century since Volvo rolled my ruby-red 240 wagon off an assembly line, its creator has gone from a modest Swedish independent automaker to part of a massive American conglomerate to an arm of a Chinese automaker that's pushing driverless cars and racing to go fully electric in the next two years. It's been a funky journey for a funky automaker, but it's no mere aberration or footnote. If you want to understand the car industry of the past 25 years--and maybe the next 25--study Volvo's journey. For a niche player best known for shuttling liberals and hippies, Volvo has long played an outsized role in the evolution of the auto industry. It invented and made standard the three-point seat belt.

Summary: Count yourself lucky if you're not in one of the regulated industries where regulation requires you to value interpretability over accuracy. This has been a serious financial weight on the economy but innovations in Deep Learning point a way out. As Data Scientists we tend to take as gospel that more accuracy is better. There are some practical limits to this. It may not be profitable to continue to work a model for many days or weeks when the improvement to be had is minor.