Cameras--especially phone cameras--are terrible at taking pictures in the dark. The tiny image sensors in most modern cameras can only absorb a small amount of light, which often results in dark, grainy images. To try to solve this problem without inventing a new image sensor, researchers at Intel and the University of Illinois Urbana-Champlain taught an artificial intelligence algorithm how to take the data from darker images and reconstruct them so that they're brighter and clearer, according to research published this month and to be presented in June at an industry conference. To train the algorithm, the researchers showed it two version of more than 5,000 images taken in low-light scenarios: One set that was taken to be purposefully too dark, and one set that was taken with a longer exposure time, meaning the sensor is given more time to collect light and better expose the image. The Intel and UIUC team claims the algorithm can now amplify low-light images the equivalent of up to 300 times the exposure, without the same noise and discoloration that programs like Photoshop might introduce or having to take two separate images. While the team did build a custom algorithm to do the task, the most innovative aspect of the work is the dataset they created.

In this age of disinformation, where fake news thrives and the public has trust issues with technology, Google designed a machine that can deceive humans. Gosh, what could go wrong? Google's engineers used artificial intelligence to give birth to something called Duplex -- a digital assistant that can call a local business to make appointments on your behalf over the phone. And the receptionists on the other end of the call have no idea they are conversing back and forth with a robot. Not only is the typical robotic voice gone, but Google took extra steps to disguise the system to sound more like a human.

The Data Capture lab is for building labled datasets for time series events that can be used for supervised learning tasks. The toolkit generates optimized c code for embedded devices so that you can do local classification on the microcontroller attached to a sensor instead of needing to stream data back to a central server for processing.

Today's top Amazon deals will help you live your best life. If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA Today's newsroom and any business incentives. It's Thursday, which means we're so close to the weekend. But Thursdays can really drag along, and I know something that can make today a little more bearable.

Music written by teams, David Byrne once wrote, is arguably more accessible than that written by a sole composer. Collaborations, he mused, may result in more "universal" sentiments. Now music producers are enlisting AI to crank out hits. Created by Sony's Computer Science Laboratories, Flow Machines analyzes tracks from around the world, then suggests scores that artists--including electropop musician ALB and jazz vocalist Camille Bertault--interpret into songs. For its debut album, Hello World, the AI also surveyed syllables and words from existing music to create original (albeit gibberish) vocals.

ActiveCampaign is focused on providing value with features that ultimately save time. With the introduction of Win Probability, users are armed with actionable insights that enable them to sell more efficiently and effectively, giving users more time to focus on business initiatives. "Machine learning is often seen as a black box where users aren't sure what's happening behind the scenes," said Jason VandeBoom, Founder and CEO of ActiveCampaign. "Win Probability is built to give our users visibility into what's driving the predictions as they know their business better than we ever could. By giving users the ability to customize the inputs, they can uncover the actions that make the most impact and better allocate their resources based on the likelihood of winning a deal."

"Music isn't just what we listen to, it's who we are." This is Google's hypothesis, as laid out in marketing materials for YouTube Music – a revamped streaming service it hopes will rival Spotify and Apple Music. And who knows who people really are better than Google? Through its blanket dominance in everything from email and search, to maps and calendars, Google knows its users' location, habits, tastes and future plans. By accessing the vast amounts of data swept up by these digital services, Google wants to offer a new type of personalised music streaming service. Combining this personal knowledge with the AI-powered Google Assistant, YouTube Music should in theory be able to offer listening suggestions suitable to whatever the situation – be it falling asleep or a morning commute.

The rise of artificial intelligence is fast disrupting the financial universe and establishing new paradigms of understanding and action. Computers now drive market velocity, and because the volume of available financial information has expanded exponentially over the last few decades, machines have become indispensable to deciphering these mountains of megabytes in order to create clear-cut actionable intelligence. Given the large data sets and quantitative nature of the modern-day financial services sector, artificial intelligence (AI) has innumerable applications that are poised to revolutionize the industry over the next few years. AI saves companies time and money through the use of algorithms to generate insights, improve customer service and make calculated performance predictions. Because of the ability to foresee market trends and deliver analysis and insights far better than humans, information behemoths and financial titans such as S&P Global Inc. (NYSE: SPGI), Euronext NV (OTC: EUXTF), The Blackstone Group, L.P. (NYSE: BX) and Thomson Reuters Corp (NYSE: TRI) are integrating and increasingly acquiring machine-learning, artificial intelligence technologies such as those provided by AnalytixInsight Inc. (TSX-V: ALY) (OTC: ATIXF) (ATIXF Profile), which offers investors a compelling opportunity to participate in this industry shift.

The film only earned $57 million domestically, but it still topped 2016's Assassin's Creed, which earned $54 million in the US with a $240 million cumulative box office. And here's the thing: Tomb Raider was really good. Alicia Vikander's Lara Croft is really good. It's one of the best video game movies I've ever seen, and if you missed it at the movie theater, you should definitely check it out from the comfort of your own home. "Best video game movie" is a fairly low bar, but I genuinely enjoyed Tomb Raider as a movie---not just as a video game movie. It certainly has more than a few similarities to the rebooted video game franchise.

BBC Radio 1 Newsbeat's Gaming Reporter Steffan Powell has been given exclusive access to the new device and met some of those it's designed to help.