Amid surging investment in artificial intelligence over the past few years and continuing concern about the implications of the technology, the White House announced on Tuesday that it intends to hold a series of workshops and form an inter-agency working group to examine the benefits and risks of AI. In a blog post, Ed Felten, Deputy US Chief Technology Officer, framed the issue in a way that excludes speculative scenarios presenting AI as a threat to humanity, a concern raised by the likes of Stephen Hawking and Elon Musk. While worries about runaway malevolent AI are often raised in public discussions of the technology, real AI research is more mundane, as in Google's effort to improve the conversational capabilities of its software by feeding it romance novels. "Today's AI is confined to narrow, specific tasks, and isn't anything like the general, adaptable intelligence that humans exhibit," said Felten. "Despite this, AI's influence on the world is growing. The rate of progress we have seen will have broad implications for fields ranging from healthcare to image- and voice-recognition."

Last week, the White House released a report chronicling the Obama administration's concerns over Big Data and artificial intelligence. Many prominent thinkers and scientists have come out recently with warnings about the dangers of unchecked artificial intelligence. However, the A.I. the White House report refers to is not of the Terminator ilk -- rather, Obama has concerns over algorithmic artificial intelligence operating without human oversight. The report, "Big Data: A Report on Algorithmic Systems, Opportunity, and Civil Rights," catalogs the growing sphere of influence represented by Big Data in society, including employment, higher education, and criminal justice. "As data-driven services become increasingly ubiquitous, and as we come to depend on them more and more, we must address concerns about intentional or implicit biases that may emerge from both the data and the algorithms used as well as the impact they may have on the user and society. Questions of transparency arise when companies, institutions, and organizations use algorithmic systems and automated processes to inform decisions that affect our lives, such as whether or not we qualify for credit or employment opportunities, or which financial, employment and housing advertisements we see." "If feedback loops are not thoughtfully constructed, a predictive algorithmic system built in this manner could perpetuate policing practices that are not sufficiently attuned to community needs and potentially impede efforts to improve community trust and safety. For example, machine learning systems that take into account past arrests could indicate that certain communities require more policing and oversight, when in fact the communities may be changing for the better over time."

In a conference on Monday, U.S. Deputy Defense Secretary Bob Work outlined a key component of modern warfare strategy called Third Offset. The military intends to take advantage of cutting-edge R&D to incorporate AI-human teams to overcome an enemy's network. At the 2016 Global Strategy forum on Monday, Mr. Work noted that products with potential military applications are fast-tracked to enter the global market. "R&D is going down in the public sector, but up in the private sector. Most things that have to do with AI [artificial intelligence] and autonomy are happening in the private sector. And so all competitors are going to have access to it, it's going to be a world of fast-followers. You're going to have an instance where you're not going to have a lasting advantage."

Artificial intelligence has gained serious attention as a solution for complex problems, but the head of the Defense Advanced Research Projects Agency cautions against viewing it as a panacea. "When we look at what's happening with artificial intelligence, we see something that is very, very powerful, very valuable for military applications, but we also see a technology that is still quite fundamentally limited," DARPA Director Arati Prabhakar said at the Atlantic Council on May 2. Image analysis, Prabhakar said, reveals some of the technology's limitations. While AI and machine learning systems are statistically better than humans at identifying images because they can sift through thousands of images in seconds, "the problem is that when they're wrong, they are wrong in ways that no human would ever be wrong," she said. In one case, a picture of a baby holding a toothbrush was identified by a machine as a baby with a baseball bat. "I think this is a critically important caution about where and how we would use this generation of artificial intelligence," she said.

French officials have unveiled a humanoid diving robot that they hope will give a big artificial hand to the practice of underwater archaeology. Ocean One, which looks like something out of a scuba-diving sequel to "Transformers," is the work of a team of roboticists, including Oussama Khatib of Stanford University. It is intended to help researchers explore underwater archaeological sites that are too deep to be explored by human divers. It was unveiled by culture officials on Thursday in the French city of Marseille following a trial sifting through the wreckage of "The Moon," a 17th century warship, where it had managed to collect a delicate ceramic pot and bring it back to the surface.

NEW ORLEANS--The problem with robots on the battlefield today, according to Marine Corps Colonel Jim "Jinx" Jenkins, is that they still have to be driven by humans. That's why the Marine Corps and the Department of Defense are researching ways for robots to act more like teammates on the battlefield than just another piece of hardware. Jenkins, who serves as director of science and technology at the Marine Corps' Warfighting Lab at Quantico, Virginia, said in a presentation at the Association for Unmanned Systems International's XPONENTIAL conference that while robots such as those used for explosive ordnance disposal and other roles on the battlefield take soldiers and Marines out of some dangerous situations, they take their operators out of the fight. "A marine is driving, so we haven't improved our manpower situation, and sometimes it costs more manpower," he noted, since operators have to pay such close attention to what they're doing with the robot that they need someone watching their back. "We need to move toward autonomy" for robots and other uncrewed systems, he said.

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.