If you're also single and looking for love, then Maple Match – a new matchmaking website that promises to "Make dating great again" – may be the catch-all solution you've been waiting for. According to its website, Maple Match aims to make it "easy for Americans to find the ideal Canadian partner to save them from the unfathomable horror of a Trump presidency." "After more than 35,000 hits and more than 4,500 signups in just four days, we are confident that Maple Match will fulfill a clear need in the dating space," site founder and CEO Joe Goldman told Tech Times. He added that the site aims to be operational "as soon as possible." Even Canadians – who are known for being unflinchingly polite – have been vocal about their dislike for Donald Trump, though perhaps that dislike is more out of concern than anything else.

Researchers recently demonstrated how an informatics-based adaptive design strategy, tightly coupled to experiments, can accelerate the discovery of new materials with targeted properties, according to a recent paper published in Nature Communications. "What we've done is show that, starting with a relatively small data set of well-controlled experiments, it is possible to iteratively guide subsequent experiments toward finding the material with the desired target," said Turab Lookman, a physicist and materials scientist in the Physics of Condensed Matter and Complex Systems group at Los Alamos National Laboratory. Lookman is the principal investigator of the research project. "Finding new materials has traditionally been guided by intuition and trial and error," said Lookman."But with increasing chemical complexity, the combination possibilities become too large for trial-and-error approaches to be practical." To address this, Lookman, along with his colleagues at Los Alamos and the State Key Laboratory for Mechanical Behavior of Materials in China, employed machine learning to speed up the process. They developed a framework that uses uncertainties to iteratively guide the next experiments to be performed in search of a shape-memory alloy with very low thermal hysteresis (or dissipation).

Then you might have a hard time getting those right swipes. For almost two months, dating app Bumble has been letting users put special election filters onto their profile to let potential matches know where they stand on the political spectrum. Aside from Hillary Clinton, Bernie Sanders, Donald Trump and Ted Cruz (who has since dropped out of the race), as well as the overarching Democratic or Republican filters, the options also include fictional candidates like Frank Underwood from "House of Cards," Kanye West and, naturally, pizza. For users who couldn't care less about the election, there was also a #IDGAF filter. Bumble offered its 5 million users the option to choose from these 10 filters, and though using them was not required, the company told The Huffington Post that 1.8 million filters were swiped on daily.

SeaDrone, the underwater robot coming out of a new company founded by two Stanford AI lab veterans, is aiming to make fish farming a lot easier--particularly for smaller aquaculture operations--by making underwater inspection cheaper and easier. The ocean ROV's story is not an unusual one for Silicon Valley: two Stanford students meet over a lab bench, get an idea that something they'd been tinkering around with for their themselves could be turned into a product and the basis of a company. It's a story Silicon Valley loves. Eduardo Moreno met Shuyun Chung in the Stanford AI lab in 2013. Moreno, in the thick of his studies for a master's degree in mechanical engineering, was working on underwater robot hardware in collaboration with King Abdullah University of Science and Technology in Saudi Arabia.

The White House is going to spend the summer researching how the government should deal with artificial intelligence. When you consider that we've got drones flying everywhere, robots automating jobs out of existence, and self-driving cars right around the corner, it's about time. The administration is pitching its new AI research program as an "interagency working group" that will "learn more about the benefits and risks of artificial intelligence," which is a welcome move--researchers in the field have been calling for a "Federal Robotics Commission" for the last couple years, and this at least looks like a small step toward that future. With companies like Google, Uber, and Tesla getting close to wanting to put self-driving cars on the road, drone companies hoping to begin to automate the devices, and AI-driven software taking jobs left and right, it's clear AI is going to have a significant impact on our society. AI is going to continue to make everything a lot more seamless, which is great, but we're also probably going to have to start thinking about things like a basic income for people whose jobs are automated away.

Sad, mad, glad, confused about the presidential race so far? Well, if you are really lost on who to vote for, IBM may have a solution, depending on your mood. Watson Elections, one of the surprisingly few political applications for IBM's supercomputer, debuted on stage this morning at TechCrunch's Disrupt Hackathon in Brooklyn, New York to help us decided the best candidate fitting our feelings. If you are angry and disgusted right now, you may want to go for Donald Trump. A little less angry and just sadder fits a vote for Bernie Sanders.

IBM's Watson supercomputer hardly needs any more resumé-padding. It's already won Jeopardy, written a cookbook, and dabbled in revolutionizing healthcare. Today, IBM announced that Watson is taking its cognitive learning chops to the cloud, where it'll apply them to analyzing, identifying, and (hopefully) preventing cybersecurity threats. But first, it's going to have to learn. There are already plenty of computer-enhanced approaches to combating cybercrime, most of which involve identifying outliers or abnormalities--like when a user logs a few too many failed password attempts--and determining whether those constitute some sort of threat.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Most of us have struggled to prise the lid off a jar of jam or been frustrated by the tricky safety caps on bottles of pills, but now there is robotic help at hand - literally. Engineers have developed a machine with two highly dexterous arms that are capable of unscrewing even the trickiest of lids. The talents of the RE2 Robotics High Dexterous Manipulation System extend even to tying knots, opening zips, making balloon animals and cutting snowflakes out of folded paper. A pair of robotic arms developed by engineers at RE2 Robotics is so dexterous it can unscrew the lids of jars (pictured) and even use a pair of scissors to cut out shapes from folded paper. Yet despite its handiness around the home, the robot is additionally capable of lifting three times its own weight, and the company behind it said it could be used to dismantle unexploded bombs.

It's no secret that much of the wisdom of the world lies in unstructured data, or the kind that's not necessarily quantifiable and tidy. So it is in cybersecurity, and now IBM is putting Watson to work to make that knowledge more accessible. Towards that end, IBM Security on Tuesday announced a new year-long research project through which it will collaborate with eight universities to help train its Watson artificial intelligence system to tackle cybercrime. Knowledge about threats is often hidden in unstructured sources such as blogs, research reports and documentation, said Kevin Skapinetz, director of strategy for IBM Security. "Let's say tomorrow there's an article about a new type of malware, then a bunch of follow-up blogs," Skapinetz explained.