A University of Maryland expert in machine learning is being funded by the National Institute of Standards and Technology (NIST) to develop metrics that will bridge the knowledge gap between empirical and certifiable defenses against adversarial attacks. Soheil Feizi, assistant professor of computer science with an appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS), is principal investigator of the $387K two-year project. An adversarial attack involves penetrating machine learning systems in order to make small changes to the input data to confuse the algorithm, resulting in flawed outputs. Some of these changes are so small they can fly under the radar undetected, posing a serious security risk for AI systems that are increasingly being applied to industrial settings, medicine, information analysis and more. Both empirical and certifiable defenses have recently gained attention in the machine learning community for showing success against adversarial attacks, says Feizi.

Artificial intelligence is no longer a buzz phrase -- it's doing real work for real companies. Even in the early stages of implementation, AI is providing enterprise organizations with benefits: Efficiency in operations, cybersecurity protections, digital innovation, and stronger customer relationships. Next up for AI in the enterprise is the ability to scale with more apps serving more departments. However, the race to implement AI and machine learning also raises citizen privacy concerns. There have been revelations about the potential for algorithmic bias reflected in data sources.

FBI agents have arrested a Hollywood man, accusing him of recklessly operating a drone and crashing it into a Los Angeles Police Department helicopter earlier this year. The collision damaged the chopper's fuselage and required the LAPD pilot to make an emergency landing following the September encounter. The drone, which authorities say was operated by Andrew Rene Hernandez, then tumbled from the sky and crashed into a vehicle. Hernandez, 22, was arrested Thursday and charged with unsafe operation of an unmanned aircraft after an investigation by the FBI, the LAPD and the Federal Aviation Administration. The potentially deadly collision occurred Sept. 18 after Los Angeles police officers responding to a predawn burglary call at a Hollywood pharmacy requested air support.

Right from the story's start, the game hints that something is off. You're placed into a mission in Vietnam that your character had no business participating in, purely in terms of timeline and narrative. Conversations happen in which you forget about things you've evidently done. TVs will turn on and off in your presence. It all culminates in a fascinating end-of-game twist, where it's revealed that your entire team has been lying to you, sometimes clumsily, through their teeth.

The UK has announced a massive boost in defense spending -- £16.5 billion ($21.8BN) over four years, the biggest such spending bump for 30 years -- in what prime minister Boris Johnson has described as a "once in a generation modernization" of the UK's armed forces and "the end of the era of retreat" on funding for defense. Overall the UK prime minister said the spending hike will create 40,000 jobs, adding that it will cement the country's position as the biggest military defense spender in Europe and the second largest in NATO after the US. Johnson said the focus for investment will be on cutting edge technologies that can "revolutionize" warfare -- implying a major role for artificial intelligence and sensor-laden connected hardware in "forging our military assets into a single network designed to overcome the enemy", as he put it in a statement to parliament, setting out the first conclusions from an the (ongoing) review of security, defense, development and foreign policy. "A soldier in hostile territory will be alerted to a distant ambush by sensors or satellites or drones instantly transmitting a warning using artificial intelligence to device the optimal response and offering an array of options -- from summoning an air strike to ordering a swarm attack by drones, or paralyzing the enemy with cyber weapons," Johnson told the House of Commons today, speaking via video conference as he continues to self isolate following a coronavirus contact. "New advances will surmount the old limits of logistics," he went on, fleshing out the rational for spending on upgrading military technology.

Modern day enterprise security is like guarding a fortress that is being attacked on all fronts, from digital infrastructure to applications to network endpoints. That complexity is why AI technologies such as deep learning and machine learning have emerged as game-changing defensive weapons in the enterprise's arsenal over the past three years. There is no other technology that can keep up. It has the ability to rapidly analyze billions of data points, and glean patterns to help a company act intelligently and instantaneously to neutralize many potential threats. Beginning about five years ago, investors started pumping hundreds of millions of dollars into a wave of new security startups that leverage AI, including CrowdStrike, Darktrace, Vectra AI, and Vade Secure, among others.

On Earth, deep time is an open book. By measuring trace radioactive compounds in rocks that decay with metronomic regularity, dating experts have learned when oceans opened, volcanoes erupted, and mass extinctions struck. But the story is muddled elsewhere in the Solar System because records are sparse. Scientists estimate ages on the Moon and the rocky planets from the number of craters that pock their surfaces. They have fixed dates from just nine places, all on the Moon: the six Apollo and three Soviet Luna sites from which samples were returned to laboratories on Earth. China's Chang'e-5 mission, set to launch on 24 November, aims to make it 10, by returning the first Moon rocks since the last Luna mission in 1976. Getting a firm date from another location will improve the shaky crater counting scheme, says Kentaro Terada, a cosmochemist at Osaka University. It will also sharpen the picture of the Moon's history. A fresh sample date “is the most important and exciting new finding [that will come] from the Chang'e-5 samples,” Terada says. Getting it will require a tour-de-force, round-trip space flight that has not been attempted for more than 40 years. Chang'e-5's target is Mons Rümker, a 70-kilometer-wide volcanic mound on the Moon's near side, which may have erupted as recently as about 1.3 billion years ago. It is “the youngest mare basalt on the Moon,” says Xiao Long, a planetary geoscientist at the China University of Geosciences, referring to the dark lava also seen in the Moon's maria, or seas. Brett Denevi, a planetary geologist at Johns Hopkins University's Applied Physics Laboratory and science chair of a NASA lunar analysis group, says China has picked a spot where it can have a big scientific impact. “Understanding the age of those samples and all of the Solar System–wide implications that flow from that result will be a big leap forward for planetary science,” she says. The crater counting method for determining age relies on the notion that surfaces scarred with fewer craters are younger than those that have accumulated more. Regions dated with Apollo and Luna samples have helped calibrate the method. But except for one young outlier, all of those dates cluster between 3.2 billion and 3.9 billion years, leaving the method unanchored, and highly uncertain, for surfaces younger than 3 billion years old, Terada says. “Chang'e-5 samples will provide another data point,” he says. Getting a firm date for Mons Rümker will also shed light on how lunar volcanism changed over time. Evidence suggests numerous eruptions in the first billion years of the Moon's existence blanketed the surface with volcanic basalts, forming the dark maria, before tapering off about 3 billion years ago. If Mons Rümker material proves to be just 1.3 billion years old, it will raise questions about how the interior of a small planetary body remained hot enough to erupt so long after formation, says Romain Tartese, a planetary scientist at the University of Manchester. Retrieving the samples will require a complex deep-space ballet. After launch from the Wenchang launch center in southern China, Chang'e-5 will arrive at the Moon about 3 days later, where an orbiter will release a lander. Over the course of 14 days, the lander's robotic arm will scoop up surface samples and a drill will retrieve cores down to 2 meters. Scientists are hoping for 2 kilograms of material. (NASA's Apollo program brought back more than 380 kilograms; three Soviet robotic Luna missions returned 301 grams.) An ascent vehicle will ferry the samples to the orbiter, where they will be packed into a re-entry capsule for return to Earth and a touchdown in the grasslands of Inner Mongolia. Xiao says international investigators will have access to the samples, but U.S. scientists may not because of limits on cooperation with China set by the U.S. Congress. Chang'e-5 is the latest in a set of increasingly ambitious Moon missions from the China National Space Administration, all named after Chang'e, a Chinese Moon goddess. A pair of orbiters, launched in 2007 and 2010, focused on mapping and remote observations. The lander-rover Chang'e-3 mission, in 2013, carried the first ground-penetrating radar to the lunar surface. In 2019, Chang'e-4, another lander-rover, was the first spacecraft to soft-land on the far side of the Moon. Three more Chang'e missions and a robotic scientific research station are planned by 2035. Results from Chang'e-4, still trundling along after having traveled nearly 600 meters, are raising questions for later missions. The craft landed in the South Pole–Aitken basin, the Moon's largest, deepest, and oldest impact crater, at perhaps 4 billion years. Scientists have calculated that the impacting body likely burrowed 70 kilometers into the Moon and churned material from the mantle up to the surface. In a study published in 2019 in Nature , one group of Chinese scientists said the rover's instruments had detected mantle minerals, but other groups, including Xiao's, have challenged that interpretation. Patrick Pinet, a planetary geophysicist at France's Astrophysics and Planetology Research Institute, says researchers are debating why such an enormous impact apparently did not exhume mantle material—or whether the mantle composition is somehow unexpected. Zou Yongliao, a geochemist at the Chinese Academy of Sciences's National Space Science Center, says China is making the South Pole the focus of its near-term lunar plans. And although the target site has not been revealed for Chang'e-6, another sample return mission, planetary scientists are rooting for South Pole–Aitken. A basin sample would provide clues to the mantle puzzle. It would also anchor the older end of the crater-counting curve, says Carolyn van der Bogert, a planetary geologist at the University of Münster, and “illuminate the early history of the Moon.”

BEGIN ARTICLE PREVIEW: Senvol was awarded a United States Army Research Laboratory (ARL) contract to apply its machine learning software, Senvol ML, to rapidly design additive manufactured parts. The software allows the Army to qualify parts across AM processes and platforms, thus reducing the Army’s supply chain lead time. By leveraging ML algorithms, the qualification plan will also be notably more efficient than more traditional qualification plans (i.e. require fewer builds and less time). Senvol’s partners on the program include Lockheed Martin Missiles and Fire Control, EWI, and Pilgrim Consulting. The contract is administered by the National Center for Manufacturing Sciences (NCMS) through the Advanced Manufacturing, Materials, and Processes Program (AMMP) program. Ms. Stephanie Koch, ARL’s Manager, said that “Additive manufacturing is a promising technology that could be used to enable multiple Army Modernization Priorities applications. Despite the poten

A jointly developed new report by Europol, the United Nations Interregional Crime and Justice Research Institute (UNICRI) and Trend Micro looking into current and predicted criminal uses of artificial intelligence (AI) was released today. The report provides law enforcers, policymakers and other organisations with information on existing and potential attacks leveraging AI and recommendations on how to mitigate these risks. "AI promises the world greater efficiency, automation and autonomy. At a time where the public is getting increasingly concerned about the possible misuse of AI, we have to be transparent about the threats, but also look into the potential benefits from AI technology." said Edvardas Šileris, Head of Europol's European Cybercrime Centre. "This report will help us not only to anticipate possible malicious uses and abuses of AI, but also to prevent and mitigate those threats proactively. This is how we can unlock the potential AI holds and benefit from the positive use of AI systems."

Last week Barclays' credit card business struck a deal with Amazon to offer seamless customised shopping and payment services in Germany. The announcement drew little attention amid the US election, pandemic pain -- and the cancellation of Ant Financial's putative $37bn initial public offering. But investors and regulators should pay attention. That is not because of what the deal shows about German shopping habits, Amazon's voracious expansion or Barclays strategy, per se. Instead, the German tie-up's real significance is as a tiny, but unusually visible, sign of a feverish race under way at banks and tech companies to find ways to use big data and artificial intelligence in finance. Essentially, Barclays and Amazon are linking data with AI analysis to approve credit (or not) and predict what customised services clients will want next.