We introduce the concept of local bucket error for the mini-bucket heuristics and show how it can be used to improve the power of AND/OR search for combinatorial optimization tasks in graphical models (e.g. MAP/MPE or weighted CSPs). The local bucket error illuminates how the heuristic errors are distributed in the search space, guided by the mini-bucket heuristic. We present and analyze methods for compiling the local bucket-errors (exactly and approximately) and show that they can be used to yield an effective tool for balancing look-ahead overhead during search. This can be especially instrumental when memory is restricted, accommodating the generation of only weak compiled heuristics. We illustrate the impact of the proposed schemes in an extensive empirical evaluation for both finding exact solutions and anytime suboptimal solutions.

You've probably heard that a robot is going to take your job. It's an oft-repeated refrain, heralded in article headlines and speeches from luminaries such as Elon Musk and Stephen Hawking. Some experts predict that anywhere from 38 to 57 percent of jobs could be automated in the next few decades, depending on who you ask, and the jobs aren't limited to any one industry. Automation threatens to eliminate or limit jobs such as waitstaff, truck drivers, factory workers, accountants, cashiers, and retail employees, according to a recent report from PBS. But to other experts, these apocalyptic predictions are overblown.

Russia has a new battle suit that seems to be visually inspired by Star Wars's Imperial Shadow Stormtroopers. While Russia's version likely doesn't come with a cloaking device, the high-tech armor does have a few tricks up its sleeves, including nuclear blast resistant tech. The suit was developed by Rostec and is called the Ratnik-3. The latest upgrade to the new armor includes a reportedly nuclear blast resistant watch. According to a statement released by the press office, the Chief Designer for the Life Support System of the Soldier Combat Outfit at the Central Scientific Research Institute for Precision Machine Engineering, Oleg Faustov, says "The watch, which we have included in the Ratnik outfit, retains its properties upon the impact of radiation and electromagnetic impulses, for example, upon a nuclear blast."

"The new government will catapult the UAE into its prosperous centenary which aims for fostering knowledge, science and research as well as engaging the youth in the leadership of the nation," Shaikh Mohammad said. Shaikh Mohammad tweeted that a new shake-up came after the government's recent annual meetings and the launch of the UAE Centennial Plan 2071. The reshuffle was approved by President His Highness Shaikh Khalifa Bin Zayed Al Nahyan and came after consultation with "my brother [His Highness Shaikh] Mohammad Bin Zayed [Al Nahyan, Abu Dhabi Crown Prince and Deputy Supreme Commander of the UAE Armed Forces]," Shaikh Mohammad said. The new government -- the 13th in the UAE's history -- sees the appointment of Omar Bin Sultan Al Olama, 27, as the State Minister for Artificial Intelligence. "We want the UAE to become the world's most prepared country for artificial intelligence," Shaikh Mohammad said.

The ambush in Niger earlier this month that left four U.S. troops dead has been the subject of immense speculation, not only concerning President Trump's public response to the tragedy but also about what actually happened on the ground that day. Asked by Fox News on Capitol Hill if the administration has been forthcoming about the attack, Armed Services Committee Chairman Sen. John McCain, R-Ariz., replied, "of course not" and added, "it may require a subpoena." Defense Secretary Jim Mattis said Thursday that the attack is under investigation. A dozen U.S. Army soldiers, mostly Green Berets, along with 30 Nigerians, traveled 125 miles north of Niger's capital, Niamey, in unarmored trucks on a routine mission and to meet with local village elders in Tonga Tonga, near the border with Mali, on Oct. 4. U.S. Army Sergeant La David Johnson was killed when his patrol was ambushed in Niger.

The U.S. Federal Aviation Administration's Small UAS Rule (also known as Part 107) has provisions to obtaining waivers to the usual requirements for flying drones in the United States. For example, you're not generally allowed to fly drones at night, although the FAA has granted quite a few waivers allowing flight after dark. But another rule is that you can't fly drones over people who are not part of your operations, and until about a week ago, the FAA hadn't waived that rule for anybody. Now it has, for CNN. The FAA is allowing the cable news network to use a drone to obtain video over uninvolved people, even crowds assembled at places like sporting events.

It's time we start talking about AI regulation. As the technology progresses at a rapid pace, it is a critical time for governments and policymakers to think about how we can safeguard the effects of Artificial Intelligence on a social, economic and political scale. Artificial Intelligence is not inherently good or bad, but the way we use it could well be one or the other. Unfortunately, there has been little attention paid by such governing bodies as yet in regard to the impact of this technology. We're going to see huge changes to employment, privacy, and arms to name a few, that if managed incorrectly or not at all, could spell disaster.

Since the 2013 Target breach, it's been clear that companies need to respond better to security alerts even as volumes have gone up. With this year's fast-spreading ransomware attacks and ever-tightening compliance requirements, response must be much faster. Adding staff is tough with the cybersecurity hiring crunch, so companies are turning to machine learning and artificial intelligence (AI) to automate tasks and better detect bad behavior. In a cybersecurity context, AI is software that perceives its environment well enough to identify events and take action against a predefined purpose. AI is particularly good at recognizing patterns and anomalies within them, which makes it an excellent tool to detect threats.

Artificial Intelligence (AI) presents a significant opportunity to solve problems previously either not easy to solve or worse, not possible to solve. The combination of AI along with today's Graphics Processing Unit (GPU) technology provides an added boost to those leveraging sophisticated algorithms in their deep learning solutions. These sophisticated systems are able to train deep learning models and ultimately lead to predictive insights. The objective is to move from reactive to proactive and finally to predictive insights. The breadth of opportunities that AI presents is wide, however, a significant opportunity is in the Cybersecurity space.

Nature has a way of making complex shapes from a set of simple growth rules. The curve of a petal, the swoop of a branch, even the contours of our face are shaped by these processes. What if we could unlock those rules and reverse engineer nature's ability to grow an infinitely diverse array of shapes? Scientists from Harvard's Wyss Institute for Biologically Inspired Engineering and the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have done just that. In a paper published in the Proceedings of the National Academy of Sciences, the team demonstrates a technique to grow any target shape from any starting shape.